We investigate the detector design in generalized space shift keying (GSSK) modulation for large MIMO systems. An orthogonal matching pursuit (OMP) based detector design is adopted due to its low complexity compared with the maximum likelihood (ML) detector. To improve the performance of the OMP algorithm, our first design is to propose an equalizer at the receiver in order to orthogonalize the equivalent channel matrix; our second design is to propose an equalizer whose columns pursue orthonormality to the columns of the channel matrix. We obtain closed-form expressions of the equalizers under the two design objectives. Simulation results demonstrate the performance superiority compared with the standard OMP algorithm.

We consider an amplify-and-forward multiple-input multiple-output relay system with a direct source- destination link. We adopt the minimum-mean-square- error (MMSE) criterion at the destination. The problem of interest is to jointly design source and relay precoders so as to minimize mean square error of transmitted symbols under total power constraints at the source and relay nodes. We propose a method which diagonalizes the MSE matrix using singular value decomposition (SVD) and generalized SVD techniques. The proposed approach based on this diagonalized MSE matrix is suboptimal and aims to reduce the design complexity of the precoders. The solution can be obtained via an iterative water- filling technique. Simulations results show the performance advantages of the proposed approach.

The authors consider distributed estimation using sensor network with coherent multiple access channel model and LMMSE fusion rule. The sensors in the network are divided into a number of clusters. Sensors within the same cluster are allowed to collaborate through an amplification matrix to form a message this then transmitted. They formulate the problem of choosing the amplification matrices as an optimal power allocation problem under a total power constraint. The solution gives the optimal amplification matrices as scaled outer products of the observation gain and the channel gain vectors. The authors show that collaboration improves performance and, in simulations, demonstrate that the amount of improvement is closely related to the amount of collaboration.

The authors consider transmitter power control of wireless communication systems. They propose an adaptive second-order distributed power control algorithm in which the relaxation factors are adaptively adjusted to improve the rate of convergence. The algorithm updates power using a weighted combination of the distributed power control algorithm and the second-order power control (SOPC) algorithm. Simulation results show performance improvement over distributed constrained power control and constrained SOPC.

We propose two-pole one-zero second-order approximations for transfer functions in resistance-inductance-capacitance trees. The approximation matches the first three moments of the original transfer function. Formulas for computing step-response parameters such as delay time, rise time, overshoot, etc., are given. Simulation results show that adding the zero improves accuracy of the approximation.