Optimal signaling and detector design for power-constrained binary communications systems over non-Gaussian channels

In this letter, joint optimization of signal structures and detectors is studied for binary communications systems under average power constraints in the presence of additive non-Gaussian noise. First, it is observed that the optimal signal for each symbol can be characterized by a discrete random variable with at most two mass points. Then, optimization over all possible two mass point signals and corresponding maximum a posteriori probability (MAP) decision rules are considered. It is shown that the optimization problem can be simplified into an optimization over a number of signal parameters instead of functions, which can be solved via global optimization techniques, such as particle swarm optimization. Finally, the improvements that can be obtained via the joint design of the signaling and the detector are illustrated via an example. © 2010 IEEE

Optimal stochastic signaling for power-constrained binary communications systems

Cataloged from PDF version of article.Optimal stochastic signaling is studied under second and fourth moment constraints for the detection of scalar-valued binary signals in additive noise channels. Sufficient conditions are obtained to specify when the use of stochastic signals instead of deterministic ones can or cannot improve the error performance of a given binary communications system. Also, statistical characterization of optimal signals is presented, and it is shown that an optimal stochastic signal can be represented by a randomization of at most three different signal levels. In addition, the power constraints achieved by optimal stochastic signals are specified under various conditions. Furthermore, two approaches for solving the optimal stochastic signaling problem are proposed; one based on particle swarm optimization (PSO) and the other based on convex relaxation of the original optimization problem. Finally, simulations are performed to investigate the theoretical results, and extensions of the results to -ary communications systems and to other criteria than the average probability of error are discussed

Stochastic signaling in the presence of channel state information uncertainty

Cataloged from PDF version of article.In this paper, stochastic signaling is studied for power-constrained scalar valued binary communications systems in the presence of uncertainties in channel state information (CSI). First, stochastic signaling based on the available imperfect channel coefficient at the transmitter is analyzed, and it is shown that optimal signals can be represented by a randomization between at most two distinct signal levels for each symbol. Then, performance of stochastic signaling and conventional deterministic signaling is compared for this scenario, and sufficient conditions are derived for improvability and nonimprovability of deterministic signaling via stochastic signaling in the presence of CSI uncertainty. Furthermore, under CSI uncertainty, two different stochastic signaling strategies, namely, robust stochastic signaling and stochastic signaling with averaging, are proposed. For the robust stochastic signaling problem, sufficient conditions are derived for reducing the problem to a simpler form. It is shown that the optimal signal for each symbol can be expressed as a randomization between at most two distinct signal values for stochastic signaling with averaging, as well as for robust stochastic signaling under certain conditions. Finally, two numerical examples are presented to explore the theoretical results. (C) 2012 Elsevier Inc. All rights reserve

Detector Randomization and Stochastic Signaling for Minimum Probability of Error Receivers

Cataloged from PDF version of article.Optimal receiver design is studied for a communications system in which both detector randomization and stochastic signaling can be performed. First, it is proven that stochastic signaling without detector randomization cannot achieve a smaller average probability of error than detector randomization with deterministic signaling for the same average power constraint and noise statistics. Then, it is shown that the optimal receiver design results in a randomization between at most two maximum a-posteriori probability (MAP) detectors corresponding to two deterministic signal vectors. Numerical examples are provided to explain the results

Communications over fading channels with partial channel information : performance and design criteria

The effects of system parameters upon the performance are quantified under the assumption that some statistical information of the wireless fading channels is available. These results are useful in determining the optimal design of system parameters. Suboptimal receivers are designed for systems that are constrained in terms of implementation complexity. The achievable rates are investigated for a wireless communication system when neither the transmitter nor the receiver has prior knowledge of the channel state information (CSI). Quantitative results are provided for independent and identically distributed (i.i.d.) Gaussian signals. A simple, low-duty-cycle signaling scheme is proposed to improve the information rates for low signal-to-noise ratio (SNR), and the optimal duty cycle is expressed as a function of the fading rate and SNR. It is demonstrated that the resource allocations and duty cycles developed for Gaussian signals can also be applied to systems using other signaling formats. The average SNR and outage probabilities are examined for amplify-and-forward cooperative relaying schemes in Rayleigh fading channels. Simple power allocation strategies are determined by using knowledge of the mean strengths of the channels. Suboptimal algorithms are proposed for cases that optimal receivers are difficult to implement. For systems with multiple transmit antennas, an iterative method is used to avoid the inversion of a data-dependent matrix in decision-directed channel estimation. When CSI is not available, two noncoherent detection algorithms are formulated based on the generalized likelihood ratio test (GLRT). Numerical results are presented to demonstrate the use of GLRT-based detectors in systems with cooperative diversity

Adaptive multicoding and robust linear-quadratic receivers for uncertain CDMA frequency-selective fading channels

Wideband Code Division Multiple Access (WCDMA) communications in the presence of channel uncertainty poses a challenging problem with many practical applications in the wireless communications filed. In this dissertation, robust linear-quadratic (LQ) receivers for time-varying, frequency-selective CDMA channels in the presence of uncertainty regarding instantaneous channel state information are proposed and studied. In order to enhance the performance of the LQ receivers, a novel modulation technique adaptive multicoding is employed. We proposed a simple, intuitively appealing cost function the modified deflection ratio that can be maximized to find signal constellations and associated LQ receivers that are optimal in a certain sense. We discuss the properties of the proposed LQ cost function and derive a related adaptive algorithm for the simultaneous design of signals and receivers based on a simple multicoding technique. The Chernoff bound for the LQ receivers is also derived to compensate for the analytical intractability of the probability of bit error. Finally, in order to achieve higher data rate transmission in favorable channels, we extend our approach from binary signals to M-ary signal constellations in a multi-dimension subspace