A robust maximin approach for MIMO communications with imperfect channel state information based on convex optimization

This paper considers a wireless communication system with multiple transmit and receive antennas, i.e., a multiple-input-multiple-output (MIMO) channel. The objective is to design the transmitter according to an imperfect channel estimate, where the errors are explicitly taken into account to obtain a robust design under the maximin or worst case philosophy. The robust transmission scheme is composed of an orthogonal space–time block code (OSTBC), whose outputs are transmitted through the eigenmodes of the channel estimate with an appropriate power allocation among them. At the receiver, the signal is detected assuming a perfect channel knowledge. The optimization problem corresponding to the design of the power allocation among the estimated eigenmodes, whose goal is the maximization of the signal-to-noise ratio (SNR), is transformed to a simple convex problem that can be easily solved. Different sources of errors are considered in the channel estimate, such as the Gaussian noise from the estimation process and the errors from the quantization of the channel estimate, among others. For the case of Gaussian noise, the robust power allocation admits a closed-form expression. Finally, the benefits of the proposed design are evaluated and compared with the pure OSTBC and nonrobust approaches.Postprint (published version

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

Application of Permutation Genetic Algorithm for Sequential Model Building–Model Validation Design of Experiments

YesThe work presented in this paper is motivated by a complex multivariate engineering problem associated with engine mapping experiments, which require efficient Design of Experiment (DoE) strategies to minimise expensive testing. The paper describes the development and evaluation of a Permutation Genetic Algorithm (PermGA) to support an exploration-based sequential DoE strategy for complex real-life engineering problems. A known PermGA was implemented to generate uniform OLH DoEs, and substantially extended to support generation of Model Building–Model Validation (MB-MV) sequences, by generating optimal infill sets of test points as OLH DoEs, that preserve good space filling and projection properties for the merged MB + MV test plan. The algorithm was further extended to address issues with non-orthogonal design spaces, which is a common problem in engineering applications. The effectiveness of the PermGA algorithm for the MB-MV OLH DoE sequence was evaluated through a theoretical benchmark problem based on the Six-Hump-Camel-Back (SHCB) function, as well as the Gasoline Direct Injection (GDI) engine steady state engine mapping problem that motivated this research. The case studies show that the algorithm is effective at delivering quasi-orthogonal space-filling DoEs with good properties even after several MB-MV iterations, while the improvement in model adequacy and accuracy can be monitored by the engineering analyst. The practical importance of this work, demonstrated through the engine case study, also is that significant reduction in the effort and cost of testing can be achieved.The research work presented in this paper was funded by the UK Technology Strategy Board (TSB) through the Carbon Reduction through Engine Optimization (CREO) project

Rank-Two Beamforming and Power Allocation in Multicasting Relay Networks

In this paper, we propose a novel single-group multicasting relay beamforming scheme. We assume a source that transmits common messages via multiple amplify-and-forward relays to multiple destinations. To increase the number of degrees of freedom in the beamforming design, the relays process two received signals jointly and transmit the Alamouti space-time block code over two different beams. Furthermore, in contrast to the existing relay multicasting scheme of the literature, we take into account the direct links from the source to the destinations. We aim to maximize the lowest received quality-of-service by choosing the proper relay weights and the ideal distribution of the power resources in the network. To solve the corresponding optimization problem, we propose an iterative algorithm which solves sequences of convex approximations of the original non-convex optimization problem. Simulation results demonstrate significant performance improvements of the proposed methods as compared with the existing relay multicasting scheme of the literature and an algorithm based on the popular semidefinite relaxation technique

Spatial processing for frequency diversity schemes

A novel technique to obtain optimum blind spatial processing for frequency diversity spread spectrum (FDSS) communication systems is introduced. The sufficient statistics for a linear combiner, which prove ineffective due to the interferers frequency characteristics, are modified to yield improved detection under partial jamming in the spectral domain. Robustness to partial time jamming is achieved by extending the notion of replicas over the frequency axis to a repetition over the time variable. Analysis and simulations are provided, showing the advantages of using FDSS with spatial diversity to combat the interference when it is confined to a narrow frequency band or short time interval relative to the desired signal extent in either domain.Peer Reviewe