Xiangchuan Gao

Optimal power efficiency of spatial multiplexing in optical wireless MIMO channels

This paper investigates the problem of power efficiency for spatially multiplexed multiple-input multiple-output (MIMO) visible light communication (VLC) system. In this system, it combines the optical communication with illumination, but the offset power, which is used to satisfy the nonnegative constraint of the transmitter-side signal after precoding, leads to the reduction of power efficiency. In this paper, a negative inverse diagonal(NID) matrix based on optimal maximum likelihood (ML) criterion and suboptimal criterion is designed to minimise the offset power consumption, which has no effect in the conventional power allocation. We theoretically derive the detection signal at receiver with multiplying by the same NID matrix. The focus of this paper is the capacity and average power efficiency performance of the system. Simulation results show that our proposed method improves power efficiency significantly. Furthermore, we show that our scheme provides higher capacity of the system than the method without designing the NID matrix.

Banker's algorithm based resource allocation in next generation broadcasting wireless systems

This paper studies the resource allocation issue of multiple broadcast signals over multiple carrier frequencies in the next generation broadcasting wireless (NGB-W) system, each of which has specific transmission requirements on time resources and number of carrier frequencies. Based on the modified bankers algorithm, we propose a resource allocation approach of all broadcast signals in the NGB-W system, under the limitation of minimum frame length. Safety judgment is introduced to gain an effective allocation result. If the safe condition is not satisfied, an adjustment strategy need be employed to get a more appropriate allocation result. The effectiveness of the proposed scheme is demonstrated in simulation results.

Asymptotic SEP analysis for optimally precoded large MIMO channels with ZF detection

This paper considers the asymptotic analysis of symbol error probability (SEP) for either optimally precoded or uniformly precoded large correlated MIMO fading channels using the zero-forcing (ZF) detector. For such systems, we reveal some very nice structures which naturally lead us to the exploration of two very strong and very useful mathematical tools for the systematic study of asymptotic behaviors on their error performance. The first tool is the Szegös theorem on large Hermitian Toeplitz matrices and the second tool is the well known limit: limx→∞(1 + 1/x)x = e. This new approach enables us to attain a very simple expression for the SEP limit as the number of the transmitter antennas goes to infinity. One of the major advantages for this method is that its convergence rate is very fast. Hence, this expression is very efficient and effective SEP approximation for the large MIMO systems. Due to the constraint on allowable space and limited (sparse) multi-path scattering, fading correlation between neighbouring antenna elements is almost inevitable in a large MIMO architecture. By specifically examining an exponential correlation matrix model, we show that channel fading correlation can lead to significant performance loss. The optimal precoding technique can yield substantial power gain over the uniform power allocation strategy.

Robust beamforming for multiuser MISO interference channel with energy harvesting constraint

In this paper, we study the robust transmit beamforming and receive power splitting design for simultaneous wireless information and power transfer in multiuser multiple-input single-output interference channel with imperfect channel-state information at the transmitter. We consider two types of receivers, namely Type I and Type II receivers according to the ability of eliminating the interference from received signals. Following the worst-case model, we minimize the average total transmit power subject to a set of energy harvesting constraint and SINR constraint for Type I receiver or SNR constraint for Type II receiver, respectively. Based on the Lagrangian multiplier method, we propose a lower and upper bounds algorithm that is able to achieve a global optimum for Type I receiver. For Type II receiver, we transform this problem into a relaxed semidefinite programming problem, which can be solved efficiently. It is shown from simulation results that our proposed method outperform the non-robust scheme.

Linear space codes for indoor MIMO visible light communications with ML detection

In this paper, we consider the optimal design of linear space codes for an indoor multiple input multiple output (MIMO) visible light communication (VLC) system with maximum-likelihood (ML) detection, where we assume that the full knowledge of channel state information (CSI) is available at both the transmitter and the receiver. For such a system with on-off-keying (OOK) modulation, an optimal closed-form linear space code that maximizes the minimum Euclidean distance for ML detection is attained for the scenario with two transmitters and multiple receivers. Our results reveal the fact that when the channel is good, the optimal code has either a diagonal or an anti-diagonal structure, and when the channel is bad, the optimal code is to diagonalize the channel matrix first, then, optimally distribute the total transmission power into each eigen-subchannel, and then, follow a repetition coding (RC) scheme. Computer simulations verify both the accuracy and the validity of our theoretical analysis, and show that our newly proposed linear space code provides significant error performance gains over currently available space modlution (SM) and RC in literature without CSI at the transmitter.

Reduced-complexity sequential particle belief propagation over correlated fading channels

In this paper, we design a factor graph based receiver for Bit-Interleaved Coded Modulation (BICM) over correlated fading channels. With the aim of enhancing the channel estimation accuracy, we propose belief propagation algorithm combined with particle filter as an alternative to typically used Kalman smoothing algorithm. To further reduce complexity, two schedules are proposed. One is employing mode and list of particle sequentially in iterations to update channel message. Another is an adaptive message update schedule in the demodulator and decoder. Simulation results illustrate performance improvement of the proposed algorithm and significant computational complexity reduction.