Skip to main content
Log in

A Review of Transmission Rate over Wireless Fading Channels: Classifications, Applications, and Challenges

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

To address the explosive traffic demands, the capacity of the fading channel is increasingly becoming a prime concern in the designing of the wireless communication system. The channel capacity is an extremely important quantity, since it allows the transmission of the data through the channel with an arbitrarily small probability of error. In other words, capacity dictates the maximum rate of information transmission, called as ‘capacity’ of channel, determined by the intrinsic properties of the channel and is independent of the content of the transmitted information. In this paper, we present a comprehensive survey of the existing work related to the channel capacity model over various fading channels. With an elaborated explanation of the theory of channel capacity, definitions of channel capacity based on the channel state information are reviewed. To compliment this, review of the technique to enhance the channel capacity is discussed and reviewed. An effective capacity model to overcome the channel capacity limitation is also explained. Furthermore, as the secure transmission of data is of utmost importance, to address this physical layer security model is also reviewed. We also summarize the work related to channel capacity in various types of wireless networks. We finally cover the future research directions, including less explored aspects of the channel capacity that can be studied to design efficient communication systems.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Figure. 12

Similar content being viewed by others

Data Availability

N/A

Code availability

N/A

References

  1. Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27, 623–656.

    Article  MathSciNet  MATH  Google Scholar 

  2. Shannon, C. E., & Weaver, W. (1949). The Mathematical Theory of Communication. University of Illinois Press.

    MATH  Google Scholar 

  3. Shannon, C. E. (1949). Communications in the presence of noise. Proceedings of the IRE, 37(1), 10–21.

    Article  MathSciNet  Google Scholar 

  4. Singh, J., Dabeerand, O., Madhow, U. (2008). Capacity of the discrete-time AWGN channel under output quantization. In IEEE International Symposium on Information Theory, Toronto, ON.

  5. Ling, C., & Belfiore, J. (2014). Achieving AWGN channel capacity with lattice gaussian coding. IEEE Transactions on Information Theory, 60(10), 5918–5929. https://doi.org/10.1109/TIT.2014.2332343

    Article  MathSciNet  MATH  Google Scholar 

  6. Alouini, M., and Goldsmith, A. (1997) Capacity of Nakagami multipath fading channels. 1997 IEEE 47th Vehicular Technology Conference. Technology in Motion, Phoenix, AZ, USA, 1997, (vol.1, pp. 358–362). https://doi.org/10.1109/VETEC.1997.596380.

  7. Lee, W. C. Y. (1990). Estimate of channel capacity in Rayleigh fading environment. IEEE Transactions on Vehicular Technology, 39(3), 187–189. https://doi.org/10.1109/25.130999

    Article  Google Scholar 

  8. Kumar, S., Soni, S. K., & Jain, P. (2018). Micro-diversity analysis of error probability and channel capacity over hoyt/gamma fading. Radio Engineering Journal, 26(4), 1096–1103.

    Google Scholar 

  9. Kumar, S., Soni, S.K., Jain, P. (2017). Performance analysis of Hoyt-lognormal composite fading channel. In International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), (pp. 2503–2507), Chennai, India.

  10. Shankar, P. M. (2012). Fading and shadowing in wireless systems (1st ed.). Springer.

    Book  MATH  Google Scholar 

  11. Sobolewski, J. S. (2003). “Data Transmission Media”, in Encyclopedia of Physical Science and Technology (3rd ed., pp. 277–303). USA, Academic Press.

    Book  Google Scholar 

  12. Simon, M. K., & Alouini, M. S. (2004). Digital Communications over Fading Channels: A Unified Approach to Performance Analysis (2nd ed.). John Wiley & Sons.

    Book  Google Scholar 

  13. Kaur, M., Kansal, V., & Singh, S. (2019). A review paper on composite fading models. Compliance Engineering Journal, 10(9), 354–357.

    Google Scholar 

  14. Chavan, M. S., Chile, R., & Sawant, S. (2011). Multipath fading channel modeling and performance comparison of wireless channel models. International Journal of Electronics and Communication Engineering, 4(2), 189–203.

    Google Scholar 

  15. Amjad, M., Musavian, L., & Rehmani, M. H. (2019). Effective capacity in wireless networks: A comprehensive survey. IEEE Communications Surveys & Tutorials, 21(4), 3007–3038. https://doi.org/10.1109/COMST.2019.2929001 Fourthquarter 2019.

    Article  Google Scholar 

  16. Du, Q., & Sun, L. (2018). A review of physical layer security techniques for internet of things: Challenges and solutions. Entropy, 20(10), 1–21.

    Google Scholar 

  17. Wu, Y., et al. (2018). A survey of physical layer security techniques for 5G wireless networks and challenges ahead. IEEE Journal on Selected Areas in Communications, 36(4), 679–695. https://doi.org/10.1109/JSAC.2018.2825560.

    Article  Google Scholar 

  18. Liu, Y., Chen, H. H., & Wang, L. (2017). Physical layer security for next generation wireless networks: Theories, technologies, and challenges. IEEE Communications Surveys & Tutorials, 19(1), 347–376.

    Article  Google Scholar 

  19. Akyildiz, F., Kak, A., & Nie, S. (2020). 6G and beyond: The future of wireless communications systems. IEEE Access, 8, 133995–134030.

    Article  Google Scholar 

  20. Chen, X., et al. (2020). Massive Access for 5G and Beyond, arXiv:2002.03491.

  21. Abou-Faycal, I. C., Trott, M. D., & Shamai, S. (2001). The capacity of discrete-time memoryless Rayleigh-fading channels. IEEE Transactions on Information Theory, 47(4), 1290–1301. https://doi.org/10.1109/18.923716

    Article  MathSciNet  MATH  Google Scholar 

  22. Gursoy, M. C., Poor, H. V., & Verdu, S. (2005). The noncoherent rician fading Channel-part I: Structure of the capacity-achieving input. IEEE Transactions on Wireless Communications, 4(5), 2193–2206. https://doi.org/10.1109/TWC.2005.853970

    Article  Google Scholar 

  23. Chowdhury, M., and Goldsmith, A. (2016). Capacity of block Rayleigh fading channels without CSI. 2016 IEEE International Symposium on Information Theory (ISIT), (pp.1884–1888), Barcelona. https://doi.org/10.1109/ISIT.2016.7541626

  24. Marzetta, T. L., & Hochwald, B. M. (1999). Capacity of a mobile multiple-antenna communication link in Rayleigh flat fading. IEEE Transactions on Information Theory, 45(1), 139–157. https://doi.org/10.1109/18.746779

    Article  MathSciNet  MATH  Google Scholar 

  25. Yang, X. (2020). Capacity of Fading Channels without Channel Side Information, https://arxiv.org/pdf/1903.12360.pdf. Accessed Sep 2020.

  26. McEliece, R., & Stark, W. (1984). Channels with block interference. IEEE Transactions on Information Theory, 30(1), 44–53. https://doi.org/10.1109/TIT.1984.1056848

    Article  MATH  Google Scholar 

  27. Goldsmith, A. J., & Varaiya, P. P. (1997). Capacity of fading channels with channel side information. IEEE Transactions on Information Theory, 43(6), 1986–1992. https://doi.org/10.1109/18.641562

    Article  MathSciNet  MATH  Google Scholar 

  28. Berger, T., & Cheng, J. (2003). Capacity of Nakagami-q (Hoyt) fading channels with channel side information. International Conference on Communication Technology Proceedings ICCT, 2, 1915–1918.

    Google Scholar 

  29. Caire, G., & Shamai, S. (1999). On the capacity of some channels with channel state information. IEEE Transactions on Information Theory, 45(6), 2007–2019. https://doi.org/10.1109/18.782125

    Article  MathSciNet  MATH  Google Scholar 

  30. Huang, H., and Yuan, C. (2020). Ergodic Capacity of Composite Fading Channels in Cognitive Radios with Series Formula for Product of κ-μ and α-μ Fading Distributions, https://arxiv.org/ftp/arxiv/papers/1712/1712.04124.pdf. Accessed Sep 2020.

  31. Sagias, N. C., Tombras, G. S., & Karagiannidis, G. K. (2005). New results for the Shannon channel capacity in generalized fading channels. IEEE Communications Letters, 9(2), 97–99.

    Article  Google Scholar 

  32. Da Costa, D. B., & Yacoub, M. D. (2007). Average channel capacity for generalized fading scenarios. IEEE Communications Letters, 11(12), 949–951. https://doi.org/10.1109/LCOMM.2007.071323

    Article  Google Scholar 

  33. Morales-Jimenez, D., & Paris, J. F. (2010). Outage probability analysis for Nakagami-q (Hoyt) fading channels under rayleigh interference. IEEE Transactions on Wireless Communications, 9(4), 122–1276.

    Google Scholar 

  34. Tjhung, T. T., Chai, C. C., & Dong, X. (1997). Outage probability for lognormal-shadowed Rician channels. IEEE Transactions on Vehicular Technology, 46(2), 400–407. https://doi.org/10.1109/25.580779

    Article  Google Scholar 

  35. Yoo, K., et al. (2019). A comprehensive analysis of the achievable channel capacity in $\mathcal{F}$ composite fading channels. IEEE Access, 7, 34078–34094. https://doi.org/10.1109/ACCESS.2019.2898767

    Article  Google Scholar 

  36. Lei, H., Ansari, I. S., Gao, C., Guo, Y., Pan, G., & Qaraqe, K. A. (2016). Physical-layer security over generalised-K fading channels. IET Communications, 10(16), 2233–2237. https://doi.org/10.1049/iet-com.2015.0384

    Article  Google Scholar 

  37. Lei, H., Ansari, I. S., Gao, C., Guo, Y., Pan, G., & Qaraqe, K. A. (2016). On physical-layer security over SIMO generalized- K fading channels. IEEE Transactions on Vehicular Technology, 65(9), 7780–7785.

    Article  Google Scholar 

  38. Chauhan, P. S., Kumar, S., & Soni, S. K. (2020). On the physical layer security over Beaulieu-Xie fading channel. AEU - International Journal of Electronics and Communications. https://doi.org/10.1016/j.aeue.2019.152940

    Article  Google Scholar 

  39. He, B., Zhou, X., & Swindlehurst, A. L. (2016). On secrecy metrics for physical layer security over quasi-static fading channels. IEEE Transactions on Wireless Communications, 15(10), 6913–6924. https://doi.org/10.1109/TWC.2016.2593445

    Article  Google Scholar 

  40. Hyadi, A., Rezki, Z., & Alouini, M. (2016). An overview of physical layer security in wireless communication systems with CSIT uncertainty. IEEE Access, 4, 6121–6132. https://doi.org/10.1109/ACCESS.2016.2612585

    Article  Google Scholar 

  41. Srinivasan, M., & Kalyani, S. (2018). Secrecy capacity of κ-μ shadowed fading channels. IEEE Communications Letters, 22(8), 1728–1731.

    Article  Google Scholar 

  42. Alouni, M., & Goldsmith, A. J. (1999). Capacity of Rayleigh fading channels under different adaptive transmission and diversity-combining techniques. IEEE Transactions on Vehicular Technology, 48(4), 1165–1181.

    Article  Google Scholar 

  43. Wung, D., & Negi, R. (2003). Effective capacity: A wireless link model for support of quality of service. IEEE Transactions on Wireless Communications, 2(4), 630–643.

    Google Scholar 

  44. Chauhan, P. S., Kumar, S., Upadhayay, V. K., & Soni, S. K. (2021). Unified approach to effective capacity for generalised fading channels. Physical Communication. https://doi.org/10.1016/j.phycom.2021.101278

    Article  Google Scholar 

  45. Hamood, H. A., and Al-Raweshidy, H. (2020). Effective rate analysis over Fluctuating Beckmann fading channel. https://arxiv.org/pdf/1903.07026.pdf, Mar 2020.

  46. Yadav, P., Kumar, S., & Kumar, R. (2021). Analysis of EC over gamma shadowed α-η-µ fading channel. IOP Conference Series: Materials Science and Engineering, 1020, 012010.

    Article  Google Scholar 

  47. Yadav, P., Kumar, S., and Kumar, R. (2020). Effective Capacity Analysis over α-κ-μ/Gamma Composite Fading Channel. In 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), (pp. 587–592), Greater Noida, India, 2020.

  48. Yadav, P., Kumar, R., & Kumar, S. (2020). Effective capacity analysis over generalized lognormal shadowed composite fading channels. Internet Technology Letters. https://doi.org/10.1002/itl2.171

    Article  Google Scholar 

  49. Lien, S., Tseng, C., Chen, K., and Su, C. (2010). Cognitive Radio Resource Management for QoS Guarantees in Autonomous Femtocell Networks. In 2010 IEEE International Conference on Communications, (pp. 1–6), Cape Town. https://doi.org/10.1109/ICC.2010.5502784.

  50. Glisic, S., Nikolic, Z., Milosevic, N., and Pirinnen, P. (2005). Effective capacity of advanced wireless cellular networks. In 2005 IEEE 16th International Symposium on Personal, Indoor and Mobile Radio Communications, (Vol. 4, pp. 2771–2780). Berlin. https://doi.org/10.1109/PIMRC.2005.1651947.

  51. Xianquan, S., & Qingxin, C. (2015). Effective capacity of cognitive radio systems in asymmetric fading channels. The Journal of China Universities of Posts and Telecommunications, 22(3), 18–25.

    Article  Google Scholar 

  52. Piran, M. J. (2020). Multimedia communication over cognitive radio networks from QoS/QoE perspective: A comprehensive survey. Journal of Network and Computer Applications. https://doi.org/10.1016/j.jnca.2020.102759

    Article  Google Scholar 

  53. Zhang, X., & Du, Q. (2007). Cross-layer modeling for QoS-driven multimedia multicast/broadcast over fading channels in advances in mobile multimedia. IEEE Communications Magazine, 45(8), 62–75.

    Article  Google Scholar 

  54. Wang, Q., Fan, P., Wu, D. O., & Letaief, K. B. (2011). End-to-end delay constrained routing and scheduling for wireless sensor networks. In IEEE International Conference on Communications (ICC).

  55. Chen, Y., & Darwazeh, I. (2011). End-to-end delay performance analysis in IEEE 802.16j Mobile Multi-hop Relay (MMR) networks. In 2011 18th International Conference on Telecommunications, (pp. 488–492). Ayia Napa. https://doi.org/10.1109/CTS.2011.5898974.

  56. Zhang, X., & Wang, J. (2017). Heterogeneous QoS-Driven Resource Allocation over MIMO-OFDMA Based 5G Cognitive Radio Networks. In 2017 IEEE Wireless Communications and Networking Conference (WCNC) (pp. 1-6). San Francisco, CA. https://doi.org/10.1109/WCNC.2017.7925876

  57. Lin, S.-C., & Chen, K.-C. (2016). Cognitive and opportunistic relay for QoS guarantees in machine-to-machine communications. IEEE Transactions on Mobile Computing, 15(3), 599–609.

    Article  Google Scholar 

  58. Du, Q., Huang, Y., Ren, P., & Zhang, C. (2011). Statistical Delay Control and QoS-Driven Power Allocation over Two-Hop Wireless Relay Links. In IEEE Global Telecommunications Conference - GLOBECOM (2011). Houston, TX, USA.

  59. Chen, Y., & Darwazeh, I. (2013). An estimator for delay distributions in packet-based wireless digital communication systems. In 2013 IEEE Wireless Communications and Networking Conference (WCNC) (pp. 825-829). Shanghai. https://doi.org/10.1109/WCNC.2013.6554670

  60. Chamberland, J., & Liu, L. (2008). On the effective capacities of multiple-antenna Gaussian channels. In IEEE International Symposium on Information Theory. Toronto.

  61. Wang, J., & Zhang, X. (2017). Statistical QoS-Driven Cooperative Power Allocation Game over Wireless Cognitive Radio Networks. In 2017 IEEE Wireless Communications and Networking Conference (WCNC) (pp. 1-6). San Francisco. https://doi.org/10.1109/WCNC.2017.7925502

  62. Khalek, A. A., Caramanis, C., & Heath, R. W. (2013). Video quality maximizing resource allocation and scheduling with statistical delay guarantees. In IEEE Global Communications Conference (GLOBECOM) (pp. 1736–1740).

  63. Hosseiny, H., Baniasadi, M., Shah-Mansouri, V., & Ghanbari, M. (2016). Power allocation for statistically delay constrained video streaming in femtocell networks based on Nash bargaining game. In IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC) (pp. 1–6).

  64. Feng, Z., & Wen, G. (2013). QoS guarantees of multiuser video streaming over wireless links: Delay constraint and packet priority drop. China Communications, 10(3), 133–144.

    Article  Google Scholar 

  65. Chen, Y., Darwazeh, I., Philip, N., & Istepanian, R. (2013). End-to-end delay distributions in wireless tele-ultrasonography medical systems. IEEE Global Communications Conference (GLOBECOM) (pp. 2592–2597).

  66. Ezhil, P. S., & Selvaradjou, K. (2019). Performance Evaluation of Energy Efficient MAC Protocol for Wireless Body Area Network. In IEEE International Conference on System, Computation, Automation and Networking (ICSCAN). Pondicherry, India.

  67. Liu, B., Yan, Z., & Chen, C. W. (2017). Medium access control for wireless body area networks with QoS provisioning and energy efficient design. IEEE Transactions on Mobile Computing, 16(2), 422–434.

    Article  Google Scholar 

  68. Alotaibi, I., Abido, M. A., Khalid, M., & Savkin, A. V. (2020). A comprehensive review of recent advances in smart grids: A sustainable future with renewable energy resources. Energies. https://doi.org/10.3390/en13236269

    Article  Google Scholar 

  69. You, M., Mou, X., & Sun, H. (2015). Effective capacity analysis of smart grid communication networks. In IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD) (pp. 196–200). Guildford, UK.

  70. Sun, L., & Du, Q. (2017). Physical layer security with its applications in 5G networks: A review. China Communications, 14(12), 1–14.

    Article  Google Scholar 

  71. Hyadi, A., Rezki, Z., & Alouini, M. (2016). On the secrecy capacity of the multiple-antenna wiretap channel with limited CSI feedback. In Proceedings of the IEEE Information Theory Workshop (ITW) (pp. 1–6). San Diego, CA, USA.

  72. Liu, X. (2016). Average secrecy capacity of the Weibull fading channel. In 13th IEEE Annual Consumer Communications & Networking Conference (CCNC). Las Vegas, NV.

  73. Yadav, P., Kumar, S., & Kumar, R. (2021). A comprehensive survey of physical layer security over fading channels: Classifications, applications, and challenges. Transactions on Emerging Telecommunication Technologies. https://doi.org/10.1002/ett.4270.

  74. Li, X., et al. (2019). Security analysis of multi-antenna NOMA networks under I/Q imbalance. Electronics, 8(1327), 1–17.

    Google Scholar 

  75. Cao, Y., et al. (2019). Secrecy analysis for cooperative NOMA networks with multi-antenna full-duplex relay. IEEE Transactions on Communications, 67(8), 5574–5587.

    Article  Google Scholar 

  76. Xie, W., et al. (2020). Secrecy performance analysis of the NOMA system on high-speed railway. Security and Communication Networks, 2020, 6. https://doi.org/10.1155/2020/8868550 Article ID 8868550.

    Article  Google Scholar 

  77. Xu, L., Yu, X., Wang, H., et al. (2020). Physical layer security performance of mobile vehicular networks. Mobile Networks and Applications, 25, 643–649.

    Article  Google Scholar 

  78. Wang, J., Liu, C., Wang, J., Dai, J., Lin, M., & Chen, M. (2018). Secrecy Outage Probability Analysis over Malaga-Malaga Fading Channels. In IEEE International Conference on Communications (ICC). Kansas City.

  79. Zhao, H., Liu, Z., Yang, L., & Alouini, M.-S. (2019). Secrecy analysis in DF relay over generalized-K fading channels. IEEE Transactions on Communications, 67(10), 7168–7182.

    Article  Google Scholar 

  80. Yadav, S. (2020). Secrecy performance of cognitive radio sensor networks over $\alpha -\mu$ fading channels. IEEE Sensors Letters, 4(9), 1–4.

    Article  Google Scholar 

  81. Bayat, E., & Colak, A. S. (2021). Secrecy capacity analysis of an underlay cognitive radio network in the presence of co-channel and primary network interference. Electrica, 21(1), 105–114.

    Article  Google Scholar 

  82. Song, Y., Yang, W., Xiang, Z., Liu, Y., & Cai, Y. (2019). Secure transmission in mmwave wiretap channels: On sector guard zone and blockages. Entropy, 21(4), 427.

    Article  MathSciNet  Google Scholar 

  83. Ouyang, C., Wu, S., Jiang, C., Ng, D. W. K., & Yang, H. (2020). Secrecy performance for finite-alphabet inputs over fluctuating two-ray channels in FDA communications. IEEE Wireless Communications Letters, 9(10), 1638–1642.

    Article  Google Scholar 

  84. Yuan, C., et al. (2019). Analysis on secrecy capacity of cooperative non-orthogonal multiple access with proactive jamming. IEEE Transactions on Vehicular Technology, 68(3), 2682–2696.

    Article  Google Scholar 

  85. Cui, M., Zhang, G., & Zhang, R. (2019). Secure wireless communication via intelligent reflecting surface. IEEE Wireless Communications Letters, 8(5), 1410–1414. https://doi.org/10.1109/LWC.2019.2919685

    Article  Google Scholar 

  86. Zhang, Q. T., & Liu, D. P. (2002). A simple capacity formula for correlated diversity Rician fading channels. IEEE Communications Letters, 6(11), 481–483.

    Article  Google Scholar 

  87. T.R. Rasethuntsa, S.Kumar and M. Kaur, “A Comprehensive Performance Evaluation of a DF-Based Multi-Hop System Over α–κ–μ and α–κ–μ-Extreme Fading Channels,” arXiv:1903.09353v1 [cs.IT] 22 Mar 2019, 2019.

  88. Rasethuntsa, T. R., Kaur, M., Kumar, S., Chauhan, P. S., & Singh, K. (2021). On the performance of DF-based multi-hop system over α − κ − μ and α − κ − μ-extreme fading channels. Digital Signal Processing, 109(2021), 102909. https://doi.org/10.1016/j.dsp.2020.102909

    Article  Google Scholar 

  89. Chauhan, P. S., Kumar, S., & Soni, S. K. (2021). Performance analysis of non-identical cascaded α – μ fading channels. Wireless Personal Communications, 116(4), 3553–3566.

    Article  Google Scholar 

  90. da Costa, D. B., & Yacoub, M. D. (2007). Channel Capacity for Single Branch Receivers Operating in Generalized Fading Scenarios. In 2007 4th International Symposium on Wireless Communication Systems (pp. 215-218). Trondheim. https://doi.org/10.1109/ISWCS.2007.4392333.

  91. Sagias, N. C., Zogas, D. A., Karagiannidis, G. K., & Tombras, G. S. (2004). Channel capacity and second-order statistics in Weibull fading. IEEE Communications Letters, 8(6), 377–379.

    Article  Google Scholar 

  92. Ansari, I. S., & Alouini, M. (2015). Asymptotic Ergodic Capacity Analysis of Composite Lognormal Shadowed Channels. In 2015 IEEE 81st Vehicular Technology Conference (VTC Spring) (pp. 1-5). Glasgow. https://doi.org/10.1109/VTCSpring.2015.7145711

  93. Chatzidiamantis, N. D., Sandalidis, H. G., Karagiannidis, G. K., & Kotsopoulos, S. A. (2011). On the inverse-Gaussian shadowing. In International Conference on Communications and Information Technology (ICCIT). Aqaba,Jordan.

  94. Trigui, I., Laourine, A., Affes, S., & Stephenne, A. (2012). The inverse gaussian distribution in wireless channels: Second-order statistics and channel capacity. IEEE Transactions on Communications, 60(11), 3167–3173.

    Article  Google Scholar 

  95. Yoo, S., Cotton, S., Zhang, L., & Sofotasios, P. (2019). The Inverse Gamma Distribution: A New Shadowing Model. In 8th Asia-Pacific Conference on Antennas and Propagation(APCAP). Incheon, Rebublic of Korea.

  96. Lopez-Martinez, Pablo Ram´ırez-Espinosa, & Javier, F. (2019). On the Utility of the Inverse Gamma Distribution in Modeling Composite Fading Channels. In IEEE Global Communications Conference (GLOBECOM). Waikoloa, HI, USA.

  97. Pant, D., Chauhan, P. S., & Soni, S. K. (2019). Error probability and channel capacity analysis of wireless system over inverse gamma shadowed fading channel with selection diversity. International journal of communication system, 32(16), e4083.

    Article  Google Scholar 

  98. Laourine, A., Stephenne, A., & Affes, S. (2009). On the capacity of log-normal fading channels. IEEE Transactions on Communications, 57(6), 1603–1607.

    Article  Google Scholar 

  99. Kostic, I. M. (2005). Analytical approach to performance analysis for channel subject to shadowing and fading. IEE Proceedings - Communications, 152(6), 821–827.

    Article  Google Scholar 

  100. Laourine, A., Alouini, M., Affes, S., & Stephenne, A. (2008). On the Performance Analysis of Composite Multipath/Shadowing Channels Using the G-Distribution. In 2008 IEEE International Conference on Communications (pp. 1333–1338). Beijing. https://doi.org/10.1109/ICC.2008.259.

  101. Chen, C., Shu, M., Wang, Y., & Zhang, C. (2016). Outage probability analysis for MRC in κ-μ shadowed fading channels with co-channel interference. In 2016 IEEE International Conference on Information and Automation (ICIA) (pp. 270–275). Ningbo.

  102. Paris, J. (2013). Outage probability in η−μ/η−μ and κ−μ/η−μ interference- limited scenario. IEEE Transactions on Communication, 61(1), 335–343.

    Article  Google Scholar 

  103. Chauhan, P. S., Rana, V., Kumar, S., Soni, S. K., & Pant, D. (2019). Performance analysis of wireless communication system over nonidentical cascaded generalised gamma fading channels. International Journal of Communication Systems, 32(13), e4004.

    Article  Google Scholar 

  104. Chauhan, P. S., Kumar, S., Soni, S. K., Upaddhaya, V. K., & Pant, D. (2020). Average Channel Capacity over Mixture Gamma Distribution. In International Conference on Electrical and Electronics Engineering (ICE3). Gorakhpur, India.

  105. Al-Hmood, H. (2017). A mixture gamma distribution based performance analysis of switch and stay combining scheme over α- κ-μ shadowed fading. In Proceedings IEEE Annual Conference on New Trends in Information & Communications Technology.

  106. Magableh, A. M., & Matalgah, M. M. (2015). Closed-form expressions for the average channel capacity of the α-μ Fading model under different adaptive transmission protocols. Wireless communications and Mobile Computing, 15(1), 1–9.

    Article  Google Scholar 

  107. Yilmaz, F., & Alouini, M. (2010). A new simple model for composite fading channels: Second order statistics and channel capacity. In 7th International Symposium on Wireless Communication Systems (pp. 676–680). York. https://doi.org/10.1109/ISWCS.2010.5624350.

  108. Singh, R., Soni, S. K., Raw, R. S., & Kumar, S. (2016). A new approximate closed-form distribution and performance analysis of a composite weibull/log-normal fading channel. Wireless Personal Communications. https://doi.org/10.1007/s11277-016-3583-3

    Article  Google Scholar 

  109. Barman, N., Das, P., Ahmed, R., & Subadar, R. (2015). Channel capacity of adaptive transmission techniques over rice (Nakagami-n) fading channels. Advanced Research in Electrical and Electronic Engineering, 2(13), 18–21.

    Google Scholar 

  110. Sofotasios, P. C., et al. (2018). Capacity analysis under generalized composite fading conditions. In 2018 International Conference on Advanced Communication Technologies and Networking (CommNet) (pp. 1–10). Marrakech. https://doi.org/10.1109/COMMNET.2018.8360282.

  111. Aldalgamouni, T., Magableh, A. M., Mater, S., & Badarneh, O. S. (2017). Capacity analysis of α − η − μ channels over different adaptive transmission protocols. IET Communications, 11(7), 1114–1122.

    Article  Google Scholar 

  112. Moualeu, J. M., da Costa, D. B., Lopez-Martinez, F. J., & d Souza, R. A. A. (2019). On the performance of α – η – κ – μ fading channels. IEEE Communications Letters, 23(6), 967–970.

    Article  Google Scholar 

  113. Zhang, J., Matthaiou, M., Tan, Z., & Wang, H. (2012). Performance analysis of digital communication systems over composite $\eta{-}\mu$/Gamma fading channels. IEEE Transactions on Vehicular Technology, 61(7), 3114–3124.

    Article  Google Scholar 

  114. Efthymoglou, G. P., Ermolova, N. Y., & Aalo, V. A. (2010). Channel capacity and average error rates in generalised-K fading channels. IET Communications, 4(11), 1364–1372.

    Article  MathSciNet  MATH  Google Scholar 

  115. Pant, D., Chauhan, P. S., Soni, S. K., & Naithani, S. (2020). Channel Capacity Analysis of Wireless System under ORA scheme over $\kappa-\mu/$ Inverse Gamma and $\eta-\mu/$ Inverse Gamma Composite Fading Models. In International Conference on Electrical and Electronics Engineering (ICE3). Gorakhpur.

  116. Sarangi, A. K., & Datta, A. (2018). Capacity Comparison of SISO, SIMO, MISO & MIMO Systems. In Second International Conference on Computing Methodologies and Communication (ICCMC). Erode, India.

  117. Chiurtu, N., Rimoldi, B., & Telatar, E. (2001). On the capacity of multi-antenna Gaussian channels. In IEEE International Symposium on Information Theory (IEEE Cat. No.01CH37252). Washington. https://doi.org/10.1109/ISIT.2001.935916.

  118. Barbin, S. E., & Vargara, V. M. (2011). On mimo capacity of weibull fading channels. In IEEE Radio and Wireless Symposium. Phoenix, AZ, USA.

  119. Zhong, C., Wong, K. K., & Jin, S. (2008). On the ergodic capacity of MIMO Nakagami-fading channels. In IEEE International Symposium on Information Theory. Toronto, ON, Canada.

  120. Ansari, I. S., & Alouini, M.-S. (2015). On the performance analysis of digital communications over Weibull-Gamma channels. In Proceedings of the IEEE 81st Vehicular Technology Conference (VTC '15). Glasgow, UK.

  121. Tiwari, K., Saini, D. S., & Bhushan, S. V. (2016). Performance improvement in spatially multiplexed MIMO systems over Weibull-Gamma fading channel. Frequenz, 70(11–12), 547–553.

    Google Scholar 

  122. Pradhan, B. R. L. (2018). Performance assessment of correlated Rayleigh/Inverse Gaussian fading channel over distributed MIMO systems with ZF detectors. IET Communications, 12(15), 1822–1833.

    Article  Google Scholar 

  123. Zhao, X., et al. (2019). Analysis of a distributed MIMO channel capacity under a special scenario. Journal of Wireless Communications Network, 2019, 189. https://doi.org/10.1186/s13638-019-1515-0

    Article  Google Scholar 

  124. Zhang, S., & Liu, J. (2019). Ergodic capacity analysis on MIMO communications in internet of vehicles. Mobile Networks and Applications. https://doi.org/10.1007/s11036-019-01352-1

    Article  Google Scholar 

  125. Hammouda, M., Akın, S., Gursoy, M. C., & Peissig, J. (2018). Effective capacity in MIMO channels with arbitrary inputs. IEEE Transactions on Vehicular Technology, 67(4), 3252–3268.

    Article  Google Scholar 

  126. Goldsmith, A. (1999). Adaptive modulation and coding for fading channels. In Proceedings of the 1999 IEEE Information Theory and Communications Workshop (pp. 24–26).

  127. Hadi, S. S., & Tiong, T. C. (2015). Adaptive modulation and coding for LTE wireless communication. IOP Conference Series Materials Science and Engineering, 78(1), 1–6.

    Google Scholar 

  128. Djordjevic, G. T., & Djordjevic, I. B. (2009). Adaptive modulation and coding for generalized fading channels. In 2009 9th International Conference on Telecommunication in Modern Satellite, Cable, and Broadcasting Services (pp. 418–422). https://doi.org/10.1109/TELSKS..

  129. Bandiri, S. Y. M., Braga, R. M. S., & Spadito, D. H. (2017). Analytical comparison of the performance of adaptive modullation and coding in wireless network under Rayleigh fading. Journal of Microwaves, Optoelectronics and Electromagnetic Applications, 16(3), 723–735.

    Article  Google Scholar 

  130. Zhao, Y. (1998). Theoretical study of link adaptation algorithms for adaptive modulation in wireless mobile communication systems. In IEEE International Conference on Universal Personal Communications. Florence, Italy.

  131. Sámano-Robles, A. G. R. (2014). A performance model for maximum ratio combining receivers with adaptive modulation and coding in Rice fading correlated channels. In 19th IEEE Symposium on Computers and Communications (ISCC). Funchal, Portgul.

  132. López-Benítez, M. (2016). Throughput performance models for adaptive modulation and coding under fading channels. In Proceedings IEEE Wireless Communications and Networking Conference. (WCNC 2016). Doha, Qatar.

  133. López-Benítez, M. (2018). Performance analysis of SNR threshold-setting strategies for adaptive modulation and coding under fading channels. Physical Communication, 30, 154–166.

    Article  Google Scholar 

  134. Aboharba, I. M., Rahman, Q. M., & Rao, R. (2019). Adaptive OFDM-IM system over faded shadowing channel. American Journal of Networks and Communications, 8(1), 32–46.

    Article  Google Scholar 

  135. Rappaport, T. S. (1996). Wireless Communication—Principle and Practice. New Jersy, Prantice Hall PTR: Upper saddle River.

    Google Scholar 

  136. Goldsmith, A. (2005). Wireless communications (5th ed.). Cambridge University Press.

    Book  Google Scholar 

  137. Katiyar, H., Jana, R., & Bhattacharjee, R. (2010). Performance analysis of two-hop regenerative relay network with generalized selection combining at multi-antenna relay. In Annual IEEE India Conference (INDICON). Kolkata.

  138. Kong, N., & Milstein, L. B. (1999). Average SNR of a generalized diversity selection combining scheme. IEEE Communications Letters, 3(3), 57–59.

    Article  Google Scholar 

  139. Chauhan, P. S., Kumar, S., & Soni, S. K. (2019). New approximate expressions of average symbol error probability, probability of detection and AUC with MRC over generic and composite fading channels. AEU - International Journal of Electronics and Communications, 99, 119–129.

    Article  Google Scholar 

  140. Chauhan, P. S., & Soni, S. K. (2018). New analytical expressions for ASEP of modulation techniques with diversity over Lognormal fading channels with application interference limited environment. Wireless Personal Communications, 99, 695–716.

    Article  Google Scholar 

  141. Stefanovic, M., Milovic, D., Mitic, A., & Jakovljevic, M. (2008). Performance analysis of system with selection combining over correlated Weibull fading channels in the presence of cochannel interference. AEU-International Journal of Electronics and Communications, 62(9), 695–700.

    Google Scholar 

  142. Tiwari, D., Soni, S. K., & Chauhan, P. S. (2017). A new closed-form expressions of channel capacity with MRC, EGC and SC over lognormal fading channels. Wireless Personal Communications, 97, 4183–4197.

    Article  Google Scholar 

  143. Yilmaz, F., & Alouini, M. (2012). A unified MGF-based capacity analysis of diversity combiners over generalized fading channels. IEEE Transactions on Communications, 60(3), 862–875.

    Article  Google Scholar 

  144. Hamood, H. A., & Al-Raweshidy, H. S. (2020). Selection Combining Scheme over Non-identically Distributed Fisher-Snedecor F Fading Channels. https://arxiv.org/abs/1905.05595. Accessed Sep 2020.

  145. Shankar, H., & Kansal, A. (2019). MGF-based analysis of maximum ratio combining receiver over Fisher-Snedecor composite fading channel. International Journal of Innovative Technology and Exploring Engineering (IJITEE), 8(9), 1–8.

    Google Scholar 

  146. Kaur, M., & Yadav, R. (2020). Performance analysis of Beaulieu-Xie fading channel with MRC diversity reception. Emerging Telecommunication Technologies, 31(7), e3949.

    Google Scholar 

  147. Kumar, S., Soni, S. K., & Jain, P. (2018). Performance of MRC receiver over Hoyt-lognormal composite fading channel. Internation Journal of Electronics, 105(9), 1433–1450.

    Article  Google Scholar 

  148. Olutayo, A., Cheng, J., & Holzman, J. F. (2020). Performance bounds for diversity receptions over a new fading model with arbitrary branch correlation. Journal on Wireless Communications and Networking, 2020, 97. https://doi.org/10.1186/s13638-020-01705-5

    Article  Google Scholar 

  149. Singh, R., Soni, S. K., Verma, P. K., & Kumar, S. (2015). Performance Analysis of MRC Combiner Output in Log Normal Shadowed Fading. In IEEE International Conference on Computing,Communication and Automation.

  150. Bithas, P. S., Mathiopoulos, P. T., & Kotsopoulos, S. A. (2007). Diversity reception over generalized-K (KG) fading channels. IEEE Transactions on Wireless Communications, 6(12), 4238–4243.

    Article  Google Scholar 

  151. Mohamed, R., Ismail, M. H., Newagy, F. A., & Mourad, H. M. (2012). Capacity of the alpha-mu fading channel with SC diversity under adaptive transmission techniques. In 19th International Conference on Telecommunications (ICT). Jounieh.

  152. Salahat, E., & Qasaimeh, M. (2020). Unified Analytical Modeling of the Error Rates and the Ergodic Channel Capacity in η-μ Generalized Fading Channels with Integer μ and Maximal Ratio Combining Receiver. https://arxiv.org/abs/1511.03039: Accessed Sep 2020.

  153. Morales-Jimenez, D., Paris, J. F., & Lozano, A. (2012). Outage probability analysis for MRC in n-u fading channels with co-channel interference. IEEE Communications Letters, 16(5), 674–677.

    Article  Google Scholar 

  154. Ahmed, I., Nasri, A., Schober, R., & Mallik, R. K. (2012). Asymptotic performance of generalized selection combining in generic noise and fading. IEEE Transactions on Communications, 60(4), 916–922.

    Article  Google Scholar 

  155. Tellambura, A., & Annamalai, C. (2001). A new approach to performance evaluation of generalized selection diversity receivers in wireless channels. In Proceedings IEEE Vehicular Technology Conference (VTC) (pp. 2309–2313). Fall.

  156. Bithas, P. S., Sagias, N. C., & Mathiopoulos, P. T. (2007). GSC diversity receivers over generalized-gamma fading channels. IEEE Communications Letters, 11(12), 964–966.

    Article  Google Scholar 

  157. Deng, Y., Wang, L., Elkashlan, M., Kim, K. J., & Duong, T. Q. (2015). Generalized selection combining for cognitive relay networks over Nakagami- fading. IEEE Transactions on Signal Processing, 63(8), 1993–2006.

    Article  MathSciNet  MATH  Google Scholar 

  158. Alouni, M., & Simon, M. K. (2001). Performance of generalized selection combining over Weibull fading channels. In IEEE 54th Vehicular Technology Conference. Atlantic City, NJ, USA.

  159. Peppas, K. P. (2009). Performance evaluation of triple-branch GSC diversity receivers over generalized-K fading channels. IEEE Communications Letters, 13(11), 829–831.

    Article  Google Scholar 

  160. Ribeiro, A. (2012). Optimal resource allocation in wireless communication and networking. Journal on Wireless Communications and Networking. https://doi.org/10.1186/1687-1499-2012-272

    Article  Google Scholar 

  161. Perović, N. S., Renzo, M. D. & Flanagan, M. F. (2020). Channel Capacity Optimization Using Reconfigurable Intelligent Surfaces in Indoor mmWave Environments. In IEEE International Conference on Communications (ICC). Dublin, Ireland.

  162. Mangoud, M. A. (2009). Optimization of channel capacity for indoor MIMO systems using genetic algorithm. Progress In Electromagnetics Research, 7(2009), 137–150.

    Article  Google Scholar 

  163. Wang, Q., Nuygen, T., & Wang, A. X. (2014). Channel capacity optimization for an integrated wi-fi and free-space optic communication system (WiFiFO). In Proceedings of the 17th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems.

  164. Nagy, L. (2012). Modified MIMO cube for enhanced channel capacity. International Journal of Antennas and Propagation, 2012, 10. https://doi.org/10.1155/2012/734896

    Article  Google Scholar 

  165. Saidi, A., & Kim, J. Y. (2007). Dynamic Resource Allocation with Outage Probability Constraint for Fading Wireless Channels. In IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications. Athens, Greece.

  166. Liang, Y., Veeravalli, V. V., & Poor, H. V. (2007). Resource allocation for wireless fading relay channels: Max-min solution. IEEE Transactions on Information Theory, 53(10), 3432–3453.

    Article  MathSciNet  MATH  Google Scholar 

  167. Hu, Y., & Ribeiro, A. (2011). Optimal transmission over a fading channel with imperfect channel state information. In Global Telecommunications Conference. Houston, TX.

  168. Zhang, H., et al. (2015). Resource allocation for cognitive small cell networks: A cooperative bargaining game theoretic approach. IEEE Transactions on Wireless Communications, 14(6), 3481–3493.

    Article  Google Scholar 

  169. Mokari, N., Parsaeefard, S., Saeedi, H., & Azmi, P. (2014). Cooperative secure resource allocation in cognitive radio networks with guaranteed secrecy rate for primary users. IEEE Transactions on Wireless Communications, 13(2), 1058–1073.

    Article  Google Scholar 

  170. Mokari, N., Parsaeefard, S., Saeedi, H., Azmi, P., & Hossain, E. (2015). Secure robust ergodic uplink resource allocation in relay-assisted cognitive radio networks. IEEE Transactions on Signal Processing, 63(2), 291–304.

    Article  MathSciNet  MATH  Google Scholar 

  171. Awoyemia, B., Maharaj, B., & Alif, A. (2017). Optimal resource allocation solutions for heterogeneous cognitive radio networks. Digital Communications and Networks, 3(2), 129–139.

    Article  Google Scholar 

  172. Nguyen, T. M., Ha, V. N., & Le, L. B. (2015). Resource allocation optimization in multi-user multi-cell massive MIMO networks considering pilot contamination. IEEE Access, 3, 1272–1287.

    Article  Google Scholar 

  173. Zhang, A. et al. (2021). Analysis and Optimization of Channel Capacity Based on Modified IFR Algorithm. In International Conference on Applied Mathematics,Modelling and Intelligent Computing (CAMMIC). Guilin, China.

  174. Sanguinetti, L., Zappone, A., & Debbah, M. (2019). Deep Learning Power Allocation in Massive MIMO. https://arxiv.org/pdf/1812.03640.pdf.

  175. Khammari, H., & Ahmed, I. (2018). Joint Machine Learning Based Resource Allocation and Hybrid Beamforming Design for Massive MIMO Systems. In IEEE Globecom Workshops (GC Workshops), Abu Dhabi, UAE.

  176. Darsena, D., Gelli, G., & Verde, F. (2020). Beamforming and Precoding Techniques. https://doi.org/10.1002/9781119471509.w5GRef020.

  177. Qaisar, Z. H., et al. (2020). Effective beamforming technique amid optimal value for wireless communication. Electronics, 9(1869), 1–17.

    Google Scholar 

  178. Ali, E., et al. (2017). Beamforming techniques for massive MIMO systems in 5G: Overview, classification, and trends for future research. Frontiers of Information Technology & Electronic Engineering, 18, 753–772.

    Article  Google Scholar 

  179. Vouyioukas, D. A Survey on Beamforming Techniques for Wireless MIMO Relay Networks. https://doi.org/10.1155/2013/745018.

  180. Cui, S., Goldsmith, A., & Bahai, A. (2005). Energy-constrained modulation optimization. IEEE Transactions on Wireless Communications, 4, 2349–2360.

    Article  Google Scholar 

  181. Rizwan, M., Gong, T., & Janjua, K. (2018). Analysis of efficient beamforming and power optimization in wireless communication. Journal of Telecommunications System & Management, 7, 2.

    Google Scholar 

  182. Hefnawi, M. (2019). Hybrid beamforming for millimeter-wave heterogeneous networks. Electronics, 8, 2. https://doi.org/10.3390/electronics8020133

    Article  Google Scholar 

  183. Jiang, W., Zhang, Y., Zhao, J., Xiong, Z., & Ding, Z. (2021). Joint Transmit Precoding and Reflect Beamforming Design for IRS-Assisted MIMO Cognitive Radio Systems. eprint arXiv:2102.01414.

  184. Wang, J., Liao, X., & Liu, Y. (2021). Joint active and passive beamforming optimization for multigroup multicast system aided by intelligent reflecting surface. IET Communications, 15(4), 642–652.

    Article  Google Scholar 

  185. Liang, Z. W., Li, Z., Zhang, H., Wang, S., & Bie, R. (2014). Vehicular ad hoc networks: Architectures, research issues, methodologies, challenges, and trends. International Journal of Distributed Sensor Networks, 11(8), 1–4.

    Google Scholar 

  186. Khairnar, V. D., & Kotecha, K. (2013). Performance of vehicle-to-vehicle communication using IEEE 802.11p in vehicular ad-hoc network environment. International Journal of Network Security & Its Applications (IJNSA), 5(2), 143–170.

    Article  Google Scholar 

  187. Saraereh, O. A., Ali, A., Khan, I., & Rabie, K. (2020). Interference analysis for vehicle-to-vehicle communications at 28 GHz. Electronics, 9(262), 1–12. https://doi.org/10.3390/electronics9020262

    Article  Google Scholar 

  188. Verdone, R. (1997). Outage probability analysis for short-range communication systems at 60 GHz in ATT urban environments. IEEE Transactions on Vehicular Technology, 46(4), 1027–1039. https://doi.org/10.1109/25.653076

    Article  Google Scholar 

  189. He, X., Shi, W., & Luo, T. (2018). Transmission capacity analysis for vehicular ad hoc networks. IEEE Access, 6, 30333–30341. https://doi.org/10.1109/ACCESS.2018.2843333

    Article  Google Scholar 

  190. Eshteiwi, K., Kaddoum, G., Ben Fredj, K., Soujeri, E., & Gagnon, F. (2019). Performance analysis of full-duplex vehicle relay-based selection in dense multi-lane highways. IEEE Access, 7, 61581–61595. https://doi.org/10.1109/ACCESS.2019.2903453

    Article  Google Scholar 

  191. Valdivieso, C., Novillo, F., Gomez, J., & Dik, D. (2016). Performance evaluation of channel capacity in Wireless Sensor Networks using ISM band in dense urban scenarios. In 2016 IEEE Ecuador Technical Chapters Meeting (ETCM) (pp. 1-6). Guayaquil. https://doi.org/10.1109/ETCM.2016.7750826

  192. Hassan, D., Kirsal, Y., & Redif, S. (2016). Channel capacity improvement for cooperative MIMO wireless sensor networks via adaptive MIMO-SVD. In 2016 HONET-ICT (pp. 49-53). Nicosia. https://doi.org/10.1109/HONET.2016.7753449

  193. Ahmad, M., Dutkiewicz, E., & Huang, X. (2008). Performance analysis of MAC protocol for cooperative MIMO transmissions in WSN. In Proceedings of International Symposium on Personal, Indoor and Mobile Radio Communications. France.

  194. Sachan, V. K., Imam, S. A., & Beg, M. T. (2012). Performance analysis of STBC encoded cooperative MIMO system for wireless sensor networks. In 2012 IEEE International Conference on Signal Processing, Computing and Control (pp. 1–6). Waknaghat Solan. 10.11.

  195. Puccinelli, D., & Haenggi, M. (2016). Multipath fading in wireless sensor networks: measurements and interpretation. In Proceedings of the International Conference on Wireless Communications and Mobile Computing, IWCMC 2006, Vancouver, British Columbia, Canada, July 3–6, 2006.

  196. Chen, R., Shi, T., & Lv, X. (2017). Transmission performance analysis of wireless sensor networks under complex railway environment. In 2017 29th Chinese Control And Decision Conference (CCDC) (pp. 2970-2947). Chongqing. https://doi.org/10.1109/CCDC.2017.7979018.

  197. Torabi, M., & Haccoun, D. (2010). Capacity analysis of opportunistic relaying in cooperative systems with outdated channel information. IEEE Communications Letters, 14(12), 1137–1139. https://doi.org/10.1109/LCOMM.2010.12.101179

    Article  Google Scholar 

  198. Beaulieu, N. C., & Hu, J. (2006). A closed-form expression for the outage probability of decode-and-forward relaying in dissimilar Rayleigh fading channels. IEEE Communications Letters, 10(12), 813–815. https://doi.org/10.1109/LCOMM.2006.061048

    Article  Google Scholar 

  199. Lee, I., & Kim, D. (2007). BER analysis for decode-and-forward relaying in dissimilar Rayleigh fading channels. IEEE Communications Letters, 11(1), 52–54. https://doi.org/10.1109/LCOMM.2007.061375

    Article  Google Scholar 

  200. Sun, Z., Akyildiz, I. F., & Hancke, G. P. (2011). Capacity and outage analysis of mimo and cooperative communication systems in underground tunnels. IEEE Transactions on Wireless Communications, 10(11), 3793–3803. https://doi.org/10.1109/TWC.2011.080611.102077

    Article  Google Scholar 

  201. Gheth, W., Alfitouri, A., Rabie, K. M., Adebisi, B., & Hamdi, K. A. (2019). Performance Analysis of Cooperative Diversity in Multi-user Environments. In 8th International Conference on Modeling Simulation and Applied Optimization (ICMSAO). Manama, Bahrain.

  202. Dimitriou, I., & Pappas, N. (2020). Performance Analysis of a Cooperative Wireless Network with Adaptive Relays. https://arxiv.org/abs/1710.05748: Accessed Sep, 2020.

  203. Asshad, M., Kavak, A., Kucuk, K., & Khan, S. A. (2020). Comparative performance analysis of cooperative and multi dual-hop relay networks using MGF approach. International Journal of Communication Systems, 33(15), 4545.

    Article  Google Scholar 

  204. Panajotović, A., Sekulović, N., Cvetković, A., & Milović, D. (2020). System performance analysis of cooperative multihop relaying network applying approximation to dual-hop relaying network. International Journal of Communication Systems, 33, 14.

    Article  Google Scholar 

  205. Khan, I., Rajatheva, N., Tanoli, S. A., & Jan, S. (2013). Performance analysis of cooperative network over Nakagami and Rician fading channels. International Journal of Communication Systems, 27(11), 2703–2722.

    Google Scholar 

  206. Venkatraman, H., & Muntean, G.-M. (2012). Cognitive Radio and its Application for Next Generation Cellular and Wireless Networks. Springer.

    Book  Google Scholar 

  207. Khoshafa, M. H., & Al-Ahmadi, S. (2017). On the capacity of underlay cognitive radio networks over shadowed multipath fading channels. Arabian Journal for Science and Engineering, 42, 5191–5199.

    Article  Google Scholar 

  208. Kang, X., Liang, Y., Nallanathan, A., Garg, H. K., & Zhang, R. (2009). Optimal power allocation for fading channels in cognitive radio networks: Ergodic capacity and outage capacity. IEEE Transactions on Wireless Communications, 8(2), 940–950.

    Article  Google Scholar 

  209. liu, Y., Xu, D., Feng, Z. & Zhang, P. (2012). Outage capacity of cognitive radio in rayleigh fading environments with imperfect channel information. Journal of Information & Computational Science, 955–968.

  210. Namdar, M., İlhan, H., & Durak-Ata, L. (2013). Spectrum sensing for cognitive radio with selection combining receiver antenna diversity. In 21st Signal Processing and Communications Applications Conference (SIU) (pp. 1–4). Haspolat. https://doi.org/10.1109/SIU.2013.

  211. Kumar, S. (2018). Performance of ED based spectrum sensing over α–η–μ fading channel. Wireless Personal Communications 100 (4): 1845–1857.

  212. Qaraqe, K. A., Ekin, S., Agarwal, T., & Serpedin, E. (2013). Performance analysis of cognitive radio multiple-access channels over dynamic fading environments. Wireless Personal Communications, 68, 1031–1045.

    Article  Google Scholar 

  213. Agarwal, R., Srivastava, N., & Katiyar, H. (2018). Theoretical Investigation of Different Diversity Combining Techniques in Cognitive Radio. Journal of Telecommunication and Information Technology. https://doi.org/10.26636/jtit.2018.124618.

  214. Kumar, V., Minz, S., & Kumar, V. (2016). Performance analysis of cognitive radio networks under spectrum sharing using queuing approach. Computers & Electrical Engineering. https://doi.org/10.1016/j.compeleceng.2016.04.010

    Article  Google Scholar 

  215. Chauhan, P. S., Tiwari, D., Soni, S. K., & Kumar, S. (2019). Energy detector performance over log-normal fading channel with diversity reception. Journal of Electromagnetic Waves and Applications, 33(17), 2242–2256.

    Article  Google Scholar 

  216. Kim, M., & Lee, J. (2018). Outage Probability of UAV Communications in the Presence of Interference. In 2018 IEEE Global Communications Conference (GLOBECOM) (pp. 1-6). Abu Dhabi, United Arab Emirates. https://doi.org/10.1109/GLOCOM.2018.8647521

  217. Goddemeier, N., & Wietfeld, C. (2015). Investigation of Air-to-Air Channel Characteristics and a UAV Specific Extension to the Rice Model. In 2015 IEEE Globecom Workshops (GC Wkshps) (2015). San Diego, CA. https://doi.org/10.1109/GLOCOMW.2015.7414180

  218. Gao, X., Chen, Z., & Hu, Y. (2013). Analysis of unmanned aerial vehicle MIMO channel capacity based on aircraft attitude. WSEAS Transactions on Information Science and Applications, 10(2), 58–67.

    Google Scholar 

  219. Tarihi, M., Noori, M. M., & Madani, M. (2020). Improving the performance of HALE UAV communication link through MIMO cooperative relay strategy. Wireless Personal Communications, 113, 1051–1071.

    Article  Google Scholar 

  220. Sharma, P. K., Deepthi, D., & Kim, D. I. (2020). Outage probability of 3-D mobile UAV relaying for hybrid satellite-terrestrial networks. IEEE Communications Letters, 24(2), 418–422.

    Article  Google Scholar 

  221. Abualhaol, I. Y., & Matalgah, M. M. (2006). Outage Probability Analysis in a Cooperative UAVs Network Over Nakagami-m Fading Channels. IEEE Vehicular Technology Conference (pp. 1–4), Montreal, Que. https://doi.org/10.1109/VTCF.2006.564.

  222. Ahn, C., Ahn, B., Kim, S., & Choi, J. (2012). Experimental outage capacity analysis for off-body wireless body area network channel with transmit diversity. IEEE Transactions on Consumer Electronics, 58(2), 274–277. https://doi.org/10.1109/TCE.2012.6227423

    Article  Google Scholar 

  223. Alkhayyat, A., & Mahmoud, M. S. (2019). Outage Probability Reduction through Inter-WBAN Cooperation. In 2019 2nd International Conference on Engineering Technology and its Applications (IICETA) (pp. 73–78). Al-Najef, Iraq. https://doi.org/10.1109/IICETA47481.2019.9012978.

  224. Tran, L. C., Mertins, A., Huang, X., & Safaei, F. (2016). Comprehensive performance analysis of fully cooperative communication in WBANs. IEEE Access, 4, 8737–8756. https://doi.org/10.1109/ACCESS.2016.2637568

    Article  Google Scholar 

  225. Thabit, A., Mahmoud, M. S., Alkhayyat, A., & Abbasi, Q. (2019). Energy harvesting Internet of Things health-based paradigm: Towards outage probability reduction through inter–wireless body area network cooperation. Internation Journal of Distributed Sensor Networks, 15(10), 1–12.

    Google Scholar 

  226. Nadeem, Q., Alwazani, H., Kammoun, A., Chaaban, A., Debbah, M., & Alouini, M. (2020). Intelligent reflecting surface-assisted multi-user MISO communication: Channel estimation and beamforming design. IEEE Open Journal of the Communications Society, 1, 661–680. https://doi.org/10.1109/OJCOMS.2020.2992791

    Article  Google Scholar 

  227. Zhang, S., & Zhang, R. (2020). Capacity characterization for intelligent reflecting surface aided MIMO communication. IEEE Journal on Selected Areas in Communications, 38(8), 1823–1838. https://doi.org/10.1109/JSAC.2020.3000814

    Article  Google Scholar 

  228. Özdogan, Ö., Bjornson, E., & Larsson, E. G. (2020). Using Intelligent Reflecting Surfaces for Rank Improvement in MIMO Communications. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Barcelona, Spain.

  229. Hou, T., Liu, Y., Song, Z., Sun, X., Chen, Y., & Hanzo, L. (2020). MIMO Assisted Networks Relying on Large Intelligent Surfaces: A Stochastic Geometry Model. https://arxiv.org/abs/1910.00959:Accessedoct 2020.

  230. Abdullah, Z., Chen, G., Lambotharan, S., & Chambers, J. A. (2020). A hybrid relay and intelligent reflecting surface network and its ergodic performance analysis. IEEE Wireless Communications Letters, 9(10), 1653–1657. https://doi.org/10.1109/LWC.2020.2999918

    Article  Google Scholar 

  231. Han, Y., Tang, W., Jin, S., Wen, C., & Ma, X. (2019). Large intelligent surface-assisted wireless communication exploiting statistical CSI. IEEE Transactions on Vehicular Technology, 68(8), 8238–8242. https://doi.org/10.1109/TVT.2019.2923997

    Article  Google Scholar 

  232. Hu, S., Rusek, F., & Edfors, O. (2015). Beyond massive MIMO: The potential of data transmission with large intelligent surfaces. IEEE Transactions on Signal Processing, 66(10), 2746–2758. https://doi.org/10.1109/TSP.2018.2816577

    Article  MathSciNet  MATH  Google Scholar 

  233. Wu, Q., & Zhang, R. (2020). Towards smart and reconfigurable environment: Intelligent reflecting surface aided wireless network. IEEE Communications Magazine, 58(1), 106–112. https://doi.org/10.1109/MCOM.001.1900107

    Article  Google Scholar 

  234. Ying, X., Demirhan, U., & Alkhateeb, A (2020). Relay Aided Intelligent Reconfigurable Surfaces:Achieving the Potential Without So Many Antennas. arXiv:2006.06644v1 [cs.IT] 11 Jun 2020.

  235. Guo, C., Cui, Y., Yang, F., & Ding, L. (2020). Outage probability analysis and minimization in intelligent reflecting surface-assisted MISO systems. IEEE Communications Letters, 24(7), 1563–1567. https://doi.org/10.1109/LCOMM.2020.2975182

    Article  Google Scholar 

  236. Hu, X., Wang, J., & Zhong, C. (2020). Statistical CSI based design for intelligent reflecting surface assisted MISO systems. Science China Information Sciences, 63(222303), 2020. https://doi.org/10.1007/s11432-020-3033-3

    Article  MathSciNet  Google Scholar 

  237. Liu, Y., Qin, Z., Elkashlan, M., Ding, Z., Nallanathan, A., & Hanzo, L. (2017). Nonorthogonal multiple access for 5G and beyond. Proceedings of the IEEE, 105(12), 2347–2381. https://doi.org/10.1109/JPROC.2017.2768666

    Article  Google Scholar 

  238. Anwar, A., Seet, B.-C., Hassan, M. A., & Li, X. (2019). A survey on application of non-orthogonal multiple access to different wireless networks. Electronics, 8, 1355. https://doi.org/10.3390/electronics8111355

    Article  Google Scholar 

  239. Men, J., Ge, J., & Zhang, C. (2017). Performance analysis of nonorthogonal multiple access for relaying networks over Nakagami-m fading channels. IEEE Transactions on Vehicular Technology, 66(2), 1200–1208. https://doi.org/10.1109/TVT.2016.2555399

    Article  Google Scholar 

  240. Kim, J., & Lee, I. (2015). Capacity analysis of cooperative relaying systems using non-orthogonal multiple access. IEEE Communications Letters, 19(11), 1949–1952.

    Article  Google Scholar 

  241. Yan, X., Xiao, H., An, K., Zheng, G., & Chatzinotas, S. (2020). Ergodic capacity of NOMA-based uplink satellite networks with randomly deployed users. IEEE Systems Journal, 14(3), 3343–3350. https://doi.org/10.1109/JSYST.2019.2934358

    Article  Google Scholar 

  242. Yan, X., Xiao, H., Wang, C., & An, K. (2018). Outage performance of NOMA-based hybrid satellite-terrestrial relay networks. IEEE Wireless Communications Letters, 7(4), 538–541. https://doi.org/10.1109/LWC.2018.2793916

    Article  Google Scholar 

  243. Yan, X., Xiao, H., Wang, C., & An, K. (2017). On the ergodic capacity of NOMA-based cognitive hybrid satellite terrestrial networks. In 2017 IEEE/CIC International Conference on Communications in China (ICCC) (2017). Qingdao. https://doi.org/10.1109/ICCChina.2017.8330454.

  244. Yang, Z., Ding, Z., Fan, P., & Karagiannidis, G. K. (2016). On the performance of non-orthogonal multiple access systems with partial channel information. IEEE Transactions on Communications, 64(2), 654–667. https://doi.org/10.1109/TCOMM.2015.2511078

    Article  Google Scholar 

  245. Xu, P., Yuan, Y., Ding, Z., Dai, X., & Schober, R. (2016). On the outage performance of non-orthogonal multiple access with 1-bit feedback. IEEE Transactions on Wireless Communications, 15(10), 6716–6730. https://doi.org/10.1109/TWC.2016.2587880

    Article  Google Scholar 

  246. Aswathi, V., & Babu, A. (2019). Performance analysis of nonorthogonal multiple access-based underlay cognitive relay network. International Journal of Communication System, 32(13), 3976.

    Article  Google Scholar 

  247. Trinh, Q., Truong, P. Q., & Phan, V. (20190. Performance analysis of NOMA for Wireless Downlink in Multi-tiers Heterogeneous Network. In 2019 International Conference on System Science and Engineering (ICSSE) (pp. 329–334). Dong Hoi, Vietnam. https://doi.org/10.1109/ICSSE.2019.8823273.

  248. Yan, X., Xiao, H., Wang, C., An, K., Chronopoulos, A. T., & Zheng, G. (2018). Performance analysis of NOMA-based land mobile satellite networks. IEEE Access, 6, 31327–31339. https://doi.org/10.1109/ACCESS.2018.2844783

    Article  Google Scholar 

  249. Taruna, S., & Kaur, I. (2013). Performance analysis of MIMO for various antenna configurations. In 2013 International Conference on Green Computing, Communication and Conservation of Energy (ICGCE) (pp. 90–93). Chennai. https://doi.org/10.1109/ICGCE.2013.6823406.

  250. Tickoo, S., Pandit, S., & Kumar, P. (2017). Performance analysis of MIMO–OFDM system with relaying techniques in Rayleigh fading channel. International Journal of Engineering and Technology, 9(4), 3066–3074.

    Article  Google Scholar 

  251. Loskot, P., & Beaulieu, N. C. (2006). Performance Analysis of Coded MIMO-OFDM Systems Over Generalized Ricean Fading Channels. In 2006 Canadian Conference on Electrical and Computer Engineering (pp. 1634–1639). Ottawa, Ont. https://doi.org/10.1109/CCECE.2006.277783.

  252. Kumbjani, B., & Kshetrimayum, R. S. (2016). Performance analysis of MIMO systems with antenna selection over generalized κ − μ fading channels. IETE Journal of Research, 62(1), 45–54.

    Article  Google Scholar 

  253. Sachan, V., Shankar, R., Kumar, I., & Mishra, R. K. (2019). Performance analysis of SM-MIMO system employing binary PSK and M’ary PSK techniques over different fading channels. Procedia Computer Science, 152, 323–332.

    Article  Google Scholar 

  254. Di Renzo, M., & Haas, H. (2012). Bit error probability of SM-MIMO over generalized fading channels. IEEE Transactions on Vehicular Technology, 61(3), 1124–1144. https://doi.org/10.1109/TVT.2012.2186158

    Article  Google Scholar 

  255. Guidotti, A., Evans, B., & Renzo, M. (2019). Integrated satellite-terrestrial networks in future wireless systems. International Journal of Satellite Communication and Networking, 37(2), 73–75.

    Article  Google Scholar 

  256. Zhao, Y., Xie, L., Chen, H., & Wang, K. (2015). Ergodic channel capacity analysis of the hybrid satellite-terrestrial single frequency network. In 2015 IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC) (pp. 1803-1807). Hong Kong. https://doi.org/10.1109/PIMRC.2015.7343591

  257. Sakarellos, V. K., Kourogiorgas, C., & Panagopolous, A. D. (2014). Cooperative hybrid land mobile satellite-terrestrial broadcasting systems: outage probability evaluation and accurate simulation. Wireless Personal Communication, 79(2), 1471–1481.

    Article  Google Scholar 

  258. Sreng, S., Escrig, B., & Boucheret, M. (2012). Outage analysis of hybrid satellite-terrestrial cooperative network with best relay selection. Wireless Telecommunications Symposium 2012 (pp. 1-5). London. https://doi.org/10.1109/WTS.2012.6266136

  259. IqbaI, A., & Ahmed, K. (2013). Integrated satellite-terrestrial system capacity over mix shadowed rician and nakagami channels. International Journal of Communication Networks and Information Security, 5(2), 104–109.

    Google Scholar 

  260. Arti, M. K., & Bhatnagar, M. R. (2013). Performance analysis of AF based hybrid satellite-terrestrial cooperative network over generalized fading channels. IEEE Communications Letters, 17(10), 1912–1915.

    Article  Google Scholar 

  261. Gaber, A. H., Halim, J. V. M., & El Hennawy, H. (2018). Outage probability of AF CDMA hybrid satellite-terrestrial cooperative networks using multiple relays over shadowed-rician fading channels. In 35th National Radio Science Conference (NRSC). Cairo.

  262. Cheng, G., Lin, Z., Lin, M., Huang, Q., & Ouyang, J. (2019). Outage probability analysis for hybrid satellite and terrestrial network with different combining schemes. WiSATS, LNICST, 281, 488–496.

    Google Scholar 

  263. An, K., Ouyang, J., Lin, M., & Liang, T. (2015). Outage analysis of multi-antenna cognitive hybrid satellite-terrestrial relay networks with beamforming. IEEE Communications Letters, 19(7), 1157–1160. https://doi.org/10.1109/LCOMM.2015.2428256

    Article  Google Scholar 

  264. Miridakis, N. I., Vergados, D. D., & Michalas, A. (2015). Dual-hop communication over a satellite relay and shadowed rician channels. IEEE Transactions on Vehicular Technology, 64(9), 4031–4040. https://doi.org/10.1109/TVT.2014.2361832

    Article  Google Scholar 

  265. Zhao, L., Liang, T., & An, K. (2020). Performance optimization of hybrid satellite-terrestrial relay network based on CR-NOMA. Sensors (Basel), 20(18), 1–14.

    Article  Google Scholar 

  266. Khalid, H., Muhmmad, S. S., Nistazakis, H. E., & Tombras, G. S. (2019). Performance analysis of hard-switching based hybrid FSO/RF system over turbulence channels. Computation, 7(28), 1–10.

    Google Scholar 

  267. Shakir, W. (2018). Performance evaluation of a selective combining scheme for the hybrid FSO/RF system. IEEE Photonics, 10, 1–10.

    Article  Google Scholar 

  268. Rakia, T., Yang, H., Alouini, M., & Gebali, F. (2015). Outage analysisof practical FSO/RF hybrid system with adaptive combining. IEEE Communications Letters, 19, 1366–1369.

    Article  Google Scholar 

  269. Amirabadi, M. (2020). Performance Analysis of a Novel Hybrid FSO/RF Communication System. https://arxiv.org/ftp/arxiv/papers/1802/1802.07160.pdf . Accessed: oct 2020.

  270. Shakir, W. M. R. (2019). On performance analysis of hybrid FSO/RF systems. IET Communications, 13(11), 1677–1684. https://doi.org/10.1049/iet-com.2018.5147

    Article  Google Scholar 

  271. Anushree, U., & Jagdeesh, V.K. (2020). Outage Performance Analysis of Hybrid FSO/RF System Using Rayleigh and K-Distribution. In Advances in Communication, Signal Processing, VLSI, and Embedded Systems. Singapore.

  272. Zhang, J., Dai, L., Zhang, Y., & Wang, Z. (2015). Unified performance analysis of mixed radio frequency/free-space optical dual-hop transmission systems. Journal of Lightwave Technology, 33(11), 2286–2293. https://doi.org/10.1109/JLT.2015.2409570

    Article  Google Scholar 

  273. Yang, L., Hasna, M. O., & Ansari, I. S. (2017). unified performance analysis for multiuser mixed $\eta $ - $\mu $ and $\mathcal {M}$ - distribution dual-hop RF/FSO systems. IEEE Transactions on Communications, 65(8), 3601–3613. https://doi.org/10.1109/TCOMM.2017.2700462

    Article  Google Scholar 

  274. Bag, B., Das, A., & Chandra, A. (2017). Capacity analysis for Rayleigh/gamma-gamma mixed RF/FSO relayed transmission. In 2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET) (pp. 1828–1832). Chennai. https://doi.org/10.1109/WiSPNET.2017.8300077.

  275. Jinga, Z., Hong, Z. S., Hu, Z. W., & Fen, C. K. (2017). Performance analysis for mixed FSO/RF Nakagami-m and Exponentiated Weibull dual-hop airborne systems. Optics Communications, 392, 294–299.

    Article  Google Scholar 

  276. Joshy, S., & Babu, A. (2010). Capacity of underwater wireless communication channel with different acoustic propagation. International Journal of Computer Networks & Communications (IJCNC), 2(5), 192–204.

    Article  Google Scholar 

  277. Stefanov, A., & Stojanovic, M. (2011). Design and performance analysis of underwater acoustic networks. IEEE Journal on Selected Areas in Communications, 29(10), 2012–2021.

    Article  Google Scholar 

  278. Stojanovic, M. (2008). Underwater acoustic communications: Design considerations on the physical layer. In Fifth Annual Conference on Wireless on Demand Network Systems and Services. Garmisch-Partenkirchen, Germany.

  279. Fu, Y., & Du, Y. (2018). Performance of heterodyne differential phase-shift-keying underwater wireless optical communication systems in gamma-gamma-distributed turbulence. Applied Optics, 57(9), 2057–2063.

    Article  Google Scholar 

  280. Zou, Z., et al. (2019). Average capacity of a UWOC system with partially coherent Gaussian beams propagating in weak oceanic turbulence. J. Opt. Soc., 36(9), 1463–1474.

    Article  Google Scholar 

  281. Xu, G., & Lai, J. (2020). Average capacity analysis of the underwater optical plane wave over anisotropic moderate-to-strong oceanic turbulence channels with the Málaga fading model. Optics Express, 28(16), 24056–24068.

    Article  Google Scholar 

  282. Farr, N., Bowen, A., Ware, J., Pontbriand, C., & Tivey, M. (2010). An integrated, underwater optical/acoustic communications system. In OCEANS'10. Sydney.

  283. Wang, J., et al. (2017). Design of optical-acoustic hybrid underwater wireless sensor network. Journal of Network and Computer Applications, 92, 59–67.

    Article  Google Scholar 

  284. Lodovisi, C., Loreti, P., Brassiale, L., & Betti, C. (2018). Performance analysis of hybrid optical-acoustic AUV swarms for marine monitoring. Future Internet, 10(65), 1–13.

    Google Scholar 

  285. Johnson, L. J., Green, R., & Leeson, M. (2014). Hybrid underwater optical/acoustic link design. In Transparent Optical Networks (ICTON). Graz, Austria.

  286. Zheng, L., & Tse, D. N. C. (2002). Communication on the Grassmann manifold: A geometric approach to the noncoherent multiple-antenna channel. IEEE Transactions on Information Theory, 48(2), 359–383.

    Article  MathSciNet  MATH  Google Scholar 

  287. Singh, D., Shukla, A. (2021). Performance Analysis of Channel Capacity of MIMO System Without CSI. In Information and Communication Technology for Intelligent Systems. ICTIS 2020. Smart Innovation, Systems (pp. 529-535). Singapore, Springer.

  288. Gong, X., Yue, X., & Liu, F. (2020). Performance analysis of cooperative NOMA networks with imperfect CSI over Nakagami-m fading channels. Sensors, 20, 424. https://doi.org/10.3390/s20020424

    Article  Google Scholar 

  289. Ananth, A., Maheswaran, P., & Selvaraj, M. D. (2019). Generalized Selection Combining for Dynamic SSK-BPSK Systems. In National Conference on Communications (NCC). Banglore.

  290. Mallik, R. K., & Win, M. Z. (2002). Analysis of hybrid selection/maximal-ratio combining in correlated Nakagami fading. IEEE Transactions on Communications, 50(8), 1372–1383.

    Article  Google Scholar 

  291. Kandpal, D. C., Kumar, V., Gangopadhyay, R., & Debnath, S. (2016). Performance of an energy detector with generalized selection combining for spectrum sensing. Cognitive Radio Oriented Wireless Networks. Springer International Publishing (pp. 375–384).

  292. Moualeu, J. M., Hamouda, W., & Takawira, F. (2018). Secrecy Performance of Generalized Selection Diversity Combining Scheme with Gaussian Errors. In 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall). Chicago, IL, USA.

  293. Thakur, S., & Singh, A. (2018). Secrecy analysis of cognitive radio network with MS-GSC/MRC scheme. Journal on Wireless Communications and Networking. https://doi.org/10.1186/s13638-018-1100-y

    Article  Google Scholar 

  294. Kumar, V., Cardiff, B., & Flanagan, M. F. (2019). Performance analysis of NOMA with generalized selection combining receivers. Electronics Letters, 55(25), 1–10.

    Article  Google Scholar 

  295. Eisen, M., Zhang, C., Chamon, L. F. O., Lee, D. D., & Reibeiro, A. (2019). Learning optimal resource allocations in wireless systems. IEEE Transactions on Signal Processing, 67(10), 2775–2790.

    Article  MathSciNet  MATH  Google Scholar 

  296. Ye, H., & Li, G. Y. (2018). Deep Reinforcement Learning for Resource Allocation in V2V Communications. In IEEE International Conference on Communications (ICC). Kansas City.

  297. Yi Huang, X., Ma, Y. L., & Yang, Z. (2021). Effective capacity maximization in beyond 5G vehicular networks: A hybrid deep transfer learning method. Wireless Communications and Mobile Computing, 2021, 12. Article ID 8899094.

    Google Scholar 

  298. Chen, J., Liang, Y. C., Kang, X., & Zhang, R. (2018). Effective-Throughput Maximization for Wireless-Powered IoT Networks with Short Packets. In 2018 IEEE Globecom Workshops (GC Wkshps). Abu Dhabi, United Arab Emirates.

  299. Gómez-Vilardebó, J. (2017). Competitive design of energy harvesting communications in wireless fading channels. IEEE/ACM Transactions on Networking, 25(6), 3863–3872.

    Article  Google Scholar 

  300. Rabie, K. M., Salem, A., Alsusa, E., & Alouini, M. (2016). Energy-harvesting in cooperative AF relaying networks over log-normal fading channels. In IEEE International Conference on Communications (ICC). Kuala Lumpur.

  301. Castro, I. T., Landesa, L., & Serna, A. (2019). Modeling the energy harvested by an RF energy harvesting system using gamma processes. Mathematical Problems in Engineering, 2019, 12. https://doi.org/10.1155/2019/8763580 Article ID 8763580.

    Article  MathSciNet  MATH  Google Scholar 

  302. Nguyen, B C, Manh Hoang, T., Nghia Pham, X., Tran, P. T. (2019). Performance Analysis of Energy Harvesting-Based Full-Duplex Decode-and-Forward Vehicle-to-Vehicle Relay Networks with Nonorthogonal Multiple Access vol. 19, 11. https://doi.org/10.1155/2019/6097686.

  303. Chihaoui, I., & Ammari, M. L. (2019). Save and transmit scheme for energy harvesting MIMO systems with TAS/MRC. Journal of Communications Software and Systems, 15(1), 52–58.

    Article  Google Scholar 

Download references

Funding

No funding was received for this work.

Author information

Authors and Affiliations

Authors

Contributions

All the authors have equally contributed in this manuscript.

Corresponding author

Correspondence to Sandeep Kumar.

Ethics declarations

Conflicts of Interest

Authors declare that there is no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yadav, P., Kumar, S. & Kumar, R. A Review of Transmission Rate over Wireless Fading Channels: Classifications, Applications, and Challenges. Wireless Pers Commun 122, 1709–1765 (2022). https://doi.org/10.1007/s11277-021-08968-1

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-021-08968-1

Keywords

Navigation