Behavior Of Channel Capacity Research Articles

Data Rate Limit in Low and High SNR Regime for Nakagami-q Fading Wireless Channel

Adequate data rate is always desired in wireless communication channels. Previously, few fading models were used to model wireless communication channels and to perform analysis on them. In this paper, analyses of data rate limit of single-input single-output (SISO) wireless communication system over Nakagami-q fading channels are presented. The calculation of capacity has been carried out using small and large limit argument approximations. The analytical solution for channel capacity is presented using small and large limit argument approximations. Where small and large limit argument approx-imations correspond low and high signal-to-noise ratio (SNR) regime. Behavior of channel capacity with respect to SNR and fading parameter respectively has been investigated deeply. The comparison of the channel capacity behavior for both low SNR and high SNR regime and have also been done and analyzed. It has found that the channel capacity increased with increasing SNR in low SNR regime. The channel capacity also behave in the same manner in high SNR regime as well.

Fundamental Capacity Analysis for Identically Independently Distributed Nakagami-q Fading Wireless Communication

With the advancement in technology, decent trans-fer rate of data for fast communication is an exigency. Different distributions on different wireless communication channels have been used previously to model them and to do performance analysis on the systems. In this work, capacity analysis of iden-tically independently distributed Nakagami-q fading single-input multiple-output (SIMO) wireless communication is presented. The derivation of channel capacity with the analytical solution have been conducted using small limit argument approximation. Where the small limit argument approximation corresponds to the low signal-to-noise ratio (SNR) regime. SIMO channel capacity behavior with respect to number of receiver antennas and with respect to SNR have been explored in depth. The improvement of capacity is depicted rigorously. It has been found that using Nakagami-q distribution, capacity of the system increases as number of receiver antenna increases. It is also found that the capacity of this SIMO wireless system can be further improved through changing of certain parameters.

Interference Alignment: From Degrees of Freedom to Constant-Gap Capacity Approximations

Interference alignment is a key technique for communication scenarios with multiple interfering links. In several such scenarios, interference alignment was used to characterize the degrees of freedom of the channel. However, these degree-of-freedom capacity approximations are often too weak to make accurate predictions about the behavior of channel capacity at finite signal-to-noise ratios (SNRs). The aim of this paper is to significantly strengthen these results by showing that interference alignment can be used to characterize capacity to within a constant gap. We focus on real, time-invariant, frequency-flat X-channels. The only known solutions achieving the degrees of freedom of this channel are either based on real interference alignment or on layer-selection schemes. Neither of these solutions seems sufficient for a constant-gap capacity approximation. In this paper, we propose a new communication scheme and show that it achieves the capacity of the Gaussian X-channel to within a constant gap. To aid in this process, we develop a novel deterministic channel model. This deterministic model depends on the 1/2 log (SNR) most-significant bits of the channel coefficients rather than only the single most-significant bit used in conventional deterministic models. The proposed deterministic model admits a wider range of achievable schemes that can be translated to the Gaussian channel. For this deterministic model, we find an approximately optimal communication scheme. We then translate this scheme for the deterministic channel to the original Gaussian X-channel and show that it achieves capacity to within a constant gap. This is the first constant-gap result for a general, fully-connected network requiring interference alignment.

Capacity Bounds and Concatenated Codes over Segmented Deletion Channels

We develop an information theoretic characterization and a practical coding approach for segmented deletion channels. Compared to channels with independent and identically distributed (i.i.d.) deletions, where each bit is independently deleted with an equal probability, the segmentation assumption imposes certain constraints, i.e., in a block of bits of a certain length, only a limited number of deletions are allowed to occur. This channel model has recently been proposed and motivated by the fact that for practical systems, when a deletion error occurs, it is more likely that the next one will not appear very soon. We first argue that such channels are information stable, hence their channel capacity exists. Then, we introduce several upper and lower bounds with two different methods in an attempt to understand the channel capacity behavior. The first scheme utilizes certain information provided to the transmitter and/or receiver while the second one explores the asymptotic behavior of the bounds when the average bit deletion rate is small. In the second part of the paper, we consider a practical channel coding approach over a segmented deletion channel. Specifically, we utilize outer LDPC codes concatenated with inner marker codes, and develop suitable channel detection algorithms for this scenario. Different maximum-a-posteriori (MAP) based channel synchronization algorithms operating at the bit and symbol levels are introduced, and specific LDPC code designs are explored. Simulation results clearly indicate the advantages of the proposed approach. In particular, for the entire range of deletion probabilities less than unity, our scheme offers a significantly larger transmission rate compared to the other existing solutions in the literature.

Capacity Results for Block-Stationary Gaussian Fading Channels With a Peak Power Constraint

We consider a peak-power-limited single-antenna block-stationary Gaussian fading channel where neither the transmitter nor the receiver knows the channel state information, but both know the channel statistics. This model subsumes most previously studied Gaussian fading models. We first compute the asymptotic channel capacity in the high SNR regime and show that the behavior of channel capacity depends critically on the channel model. For the special case where the fading process is symbol-by-symbol stationary, we also reveal a fundamental interplay between the codeword length, communication rate, and decoding error probability. Specifically, we show that the codeword length must scale with SNR in order to guarantee that the communication rate can grow logarithmically with SNR with bounded decoding error probability, and we find a necessary condition for the growth rate of the codeword length. We also derive an expression for the capacity per unit energy. Furthermore, we show that the capacity per unit energy is achievable using temporal ON-OFF signaling with optimally allocated ON symbols, where the optimal ON-symbol allocation scheme may depend on the peak power constraint.

The Poisson Fading Channel

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> In this first paper of a two-part series, a single-user single-input single-output (SISO) shot-noise-limited Poisson channel is considered over which an information signal is transmitted by modulating the intensity of an optical beam, and individual photon arrivals are counted at the photodetector receiver. The transmitted signal, which is chosen to satisfy peak and average constraints, undergoes multiplicative fading, which occurs over coherence time intervals of fixed duration. The fade coefficient (channel state) remains constant in each coherence interval, and varies across successive such intervals in an independent and identically distributed (i.i.d.) fashion. A single-letter characterization of the capacity of this channel is obtained when the receiver is provided with perfect channel state information (CSI) while the transmitter CSI can be imperfect. The asymptotic behavior of channel capacity in the low and high peak-signal-to-shot-noise ratio (SNR) regimes is studied. </para>

PARAMETER-INDUCED STOCHASTIC RESONANCE AND BASEBAND BINARY PAM SIGNALS TRANSMISSION OVER AN AWGN CHANNEL

From the point of information theory, the baseband binary pulse amplitude modulated (PAM) signals transmission, via tuning the nonlinear receiver's parameters, is studied over an additive white Gaussian noise (AWGN) channel. It is demonstrated that the channel capacity of baseband binary communication systems, for a given signal added noise, can be maximized by optimal designed receivers. This new form of stochastic resonance (SR) is referred to as parameter-induced stochastic resonance (PSR) in a broad sense. PSR effect does not require that the input signals are subthreshold. The characteristic behavior of channel capacity versus transmission bit rate is also studied. For reproducing the original binary signals more correctly, time scale transformation method and the approach of ensemble average probability of error bits are introduced. We observe a marked enhancement of the channel capacity for binary PAM signals transmission by PSR in numerical simulations. With this theory and method, the practical applications are considered.

Outdoor MIMO wireless channels: models and performance prediction

We present a new model for multiple-input-multiple-output (MIMO) outdoor wireless fading channels and their capacity performance. The proposed model is more general and realistic than the usual independent and identically distributed (i.i.d.) model, and allows us to investigate the behavior of channel capacity as a function of the scattering radii at transmitter and receiver, distance between the transmit and receive arrays, and antenna beamwidths and spacing. We show how the MIMO capacity is governed by spatial fading correlation and the condition number of the channel matrix through specific sets of propagation parameters. The proposed model explains the existence of channels which exhibit low spatial fading correlation at both ends of the link but still have poor rank properties, and hence, low ergodic capacity. In fact, the model suggests the existence of a more general family of channels spanning continuously from full rank i.i.d. to low-rank pinhole cases. We suggest guidelines for predicting high rank (and hence, high ergodic capacity) in MIMO channels, and show that even at long ranges, high channel rank can easily be sustained under mild scattering conditions. Finally, we validate our results by simulations using ray tracing techniques. Connections with basic antenna theory are made.