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Register a new userOn the Performance of MIMO FSO Communications over Double Generalized Gamma Fading Channels
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Added by
Mohammadreza Aminikashani
Publication date
2015
fields
Informatics Engineering
and research's language is
English
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A major performance degrading factor in free space optical communication (FSO) systems is atmospheric turbulence. Spatial diversity techniques provide a promising approach to mitigate turbulence-induced fading. In this paper, we study the error rate performance of FSO links with spatial diversity over atmospheric turbulence channels described by the Double Generalized Gamma distribution which is a new generic statistical model covering all turbulence conditions. We assume intensity modulation/direct detection with on-off keying and present the BER performance of single-input multiple-output (SIMO), multiple-input single-output (MISO) and multiple-input multiple-output (MIMO) FSO systems over this new channel model.
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Free space optical (FSO) communication has been receiving increasing attention in recent years with its ability to achieve ultra-high data rates over unlicensed optical spectrum. A major performance limiting factor in FSO systems is atmospheric turbulence which severely degrades the system performance. To address this issue, multiple transmit and/or receive apertures can be employed, and the performance can be improved via diversity gain. In this paper, we investigate the bit error rate (BER) performance of FSO systems with transmit diversity or receive diversity with equal gain combining (EGC) over atmospheric turbulence channels described by the Double Generalized Gamma (Double GG) distribution. The Double GG distribution, recently proposed, generalizes many existing turbulence models in a closed-form expression and covers all turbulence conditions. Since the distribution function of a sum of Double GG random variables (RVs) appears in BER expression, we first derive a closed-form upper bound for the distribution of the sum of Double GG distributed RVs. A novel union upper bound for the average BER as well as corresponding asymptotic expression is then derived and evaluated in terms of Meijers G-functions.
The fading wire-tap channel is investigated, where the source-to-destination channel and the source-to-wire-tapper channel are corrupted by multiplicative fading gain coefficients in addition to additive Gaussian noise terms. The channel state information is assumed to be known at both the transmitter and the receiver. The parallel wire-tap channel with independent subchannels is first studied, which serves as an information-theoretic model for the fading wire-tap channel. The secrecy capacity of the parallel wire-tap channel is established. This result is then specialized to give the secrecy capacity of the fading wire-tap channel, which is achieved with the source node dynamically changing the power allocation according to the channel state realization. An optimal source power allocation is obtained to achieve the secrecy capacity.
Approximate random matrix models for $kappa-mu$ and $eta-mu$ faded multiple input multiple output (MIMO) communication channels are derived in terms of a complex Wishart matrix. The proposed approximation has the least Kullback-Leibler (KL) divergence from the original matrix distribution. The utility of the results are demonstrated in a) computing the average capacity/rate expressions of $kappa-mu$/$eta-mu$ MIMO systems b) computing outage probability (OP) expressions for maximum ratio combining (MRC) for $kappa-mu$/$eta-mu$ faded MIMO channels c) ergodic rate expressions for zero-forcing (ZF) receiver in an uplink single cell massive MIMO scenario with low resolution analog-to-digital converters (ADCs) in the antennas. These approximate expressions are compared with Monte-Carlo simulations and a close match is observed.
Two mobile users communicate with a central decoder via two base stations. Communication between the mobile users and the base stations takes place over a Gaussian interference channel with constant channel gains or quasi-static fading. Instead, the base stations are connected to the central decoder through orthogonal finite-capacity links, whose connectivity is subject to random fluctuations. There is only receive-side channel state information, and hence the mobile users are unaware of the channel state and of the backhaul connectivity state, while the base stations know the fading coefficients but are uncertain about the backhaul links state. The base stations are oblivious to the mobile users codebooks and employ compress-and-forward to relay information to the central decoder. Upper and lower bounds are derived on average achievable throughput with respect to the prior distribution of the fading coefficients and of the backhaul links states. The lower bounds are obtained by proposing strategies that combine the broadcast coding approach and layered distributed compression techniques. The upper bound is obtained by assuming that all the nodes know the channel state. Numerical results confirm the advantages of the proposed approach with respect to conventional non-robust strategies in both scenarios with and without fading.
The present paper is devoted to the evaluation of energy detection based spectrum sensing over different multipath fading and shadowing conditions. This is realized by means of a unified and versatile approach that is based on the particularly flexible mixture gamma distribution. To this end, novel analytic expressions are firstly derived for the probability of detection over MG fading channels for the conventional single-channel communication scenario. These expressions are subsequently employed in deriving closed-form expressions for the case of square-law combining and square-law selection diversity methods. The validity of the offered expressions is verified through comparisons with results from respective computer simulations. Furthermore, they are employed in analyzing the performance of energy detection over multipath fading, shadowing and composite fading conditions, which provides useful insighs on the performance and design of future cognitive radio based communication systems.
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