Channel Capacity with Suboptimal Adaptation Technique over Generalized-K Fading using Marginal Moment Generating Function Aakanksha Sharma 1* , Vivek K. Dwivedi 2** , and G. Singh 1*** 1 Jaypee University of Information Technology, Waknaghat, India 2 Jaypee Institute of Information Technology, Noida, India *e-mail: sharmaak16@gmail.com **e-mail: drvivekkdwivedi@gmail.com ***ORCID: 0000-0002-5159-3286 , e-mail: drghanshyam.singh@yahoo.com Received in final form October 31, 2015 Abstract—In this paper we have computed the channel capacity for suboptimal adaptation technique over the generalized-K fading environment. The analytical expression for channel capacity in case of the truncated channel inversion with fixed rate (C TCIFR ) has been exploited in terms of marginal moment generating function (MMGF) and its performance is evaluated over the generalized-K faded environment. The MMGF based approach for the computation of channel capacity has been validated with the reported literature for channel capacity in case of the channel inversion with fixed rate using the suboptimal adaptive technique. DOI: 10.3103/S073527271608001X 1. INTRODUCTION The novel scheme based on wireless communication among the distributed nodes has motivated the use of composite fading models, because such distributed nodes experience different multipath/small-scale fading and shadowing statistics that determine the required information for the performance analysis of different transceivers. In general, the composite fading is modeled by the Rayleigh-lognormal (Suzuki) [1] and Nakagami-lognormal distributions [2], where the Rayleigh/Nakagami distributions are used to model the multipath fading and the lognormal distribution for shadowing. However, the lognormal based fading model is unable to provide significant results for higher order analysis due to its complex integral form. The K-distribution [3] and generalized-K distribution [4] have been provided as a potential substitute to the Rayleigh-lognormal and Nakagami-lognormal distributions, respectively, where the lognormal distribution is approximated by the gamma-distribution. Several performance analyses over the generalized-K distribution with different approaches have been reported in [4–6]. Shankar [4] has provided the probability density function (PDF) for the received signal-to-noise ratio (SNR) over the generalized-K fading channel and performed bit error rate (BER) analysis for binary phase shift keying (BPSK). Bithas et al. [5] have evaluated the cumulative distribution function (CDF) and moment generating function (MGF) for the generalized-K fading channel in terms of generalized hypergeometric function and Whittaker function, respectively. In addition, the authors [5] also provided the closed-form expressions for outage probability, channel capacity and the symbol error probability (SEP) for various modulation formats. Efthymoglou [6] has evaluated BER for different modulation formats using the MGF based approach. The MGF based approach has led to closed-form expressions for BER analysis and has provided the simplification in higher order computation as compared to that of the PDF based approach and thus has motivated its use for potential applications. The channel capacity is the most important performance metric of the wireless communication systems and depends on the instantaneous channel state information. However, the significant improvement in channel capacity for fading channel is obtained by the use of channel state information (CSI) at transmitter which can now adapt its transmission strategy such as transmission rate, power and coding techniques in 325 ISSN 0735-2727, Radioelectronics and Communications Systems, 2016, Vol. 59, No. 8, pp. 325–334. © Allerton Press, Inc., 2016. Original Russian Text © A. Sharma, V.K. Dwivedi, G. Singh, 2016, published in Izvestiya Vysshikh Uchebnykh Zavedenii, Radioelektronika, 2016, Vol. 59, No. 8, pp. 3–14.