Research Papers - Department of Electrical and Electronic Engineering
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Publication Embargo Energy–Efficiency Fairness of Interference Multi-Relay Networks for Multi-User Communications(IEEE, 2021-03) Ding, M; Atapattu, S; Weeraddana, C; Evans, JWe investigate a single-antenna multi-user multi-relay interference network, where multiple source nodes simultaneously communicate with their respective destination nodes via half-duplex decode-and-forward relays. To ensure fairness among users, we consider a power allocation strategy to maximize the worst-case energy efficiency (EE) of all users for a fixed relay assignment. The resulting optimization problem turns out to be non-convex. Different from those in the literature, our method here is an iterative algorithm where two geometric programs (GPs) are solved in each iteration, one producing an upper-bound to the solution of the original problem and the other providing a feasible lower-bound. Moreover, the upper-bound GP approaches the original problem asymptotically. Our algorithm also works for the problem arising in the non-interfering (orthogonal) transmission, which was previously solved as a fractional program. Numerical results reveal that non-orthogonal transmission outperforms orthogonal transmission in terms of the worst-case EE at low and medium signal-to-noise ratios.Publication Open Access A general framework for MIMO transceiver design with imperfect CSI and transmit correlation(IEEE, 2009) Blostein, S. D; Ding, M— Assuming perfect channel state information (CSI), linear precoding/decoding for multiple-input multiple-output (MIMO) systems has been considered in the literature under various performance criteria, such as minimum total meansquare error (MSE), maximum mutual information, and minimum average bit error rate (BER). It has been shown that these criteria belong to a set of reasonable Schur-concave or Schur-convex objective functions of the diagonal entries of the system mean-square error (MSE) matrix. In this paper, assuming only the knowledge of channel mean and transmit correlation at both ends, a general theoretical framework is presented to derive the optimum precoder and decoder for MIMO systems using these objective functions. It is shown that for all these objective functions the optimum transceivers share a similar structure. Compared to the case with perfect CSI, a linear filter is added to both ends to balance the suppression of channel noise and the additional noise induced from channel estimation error. Simulation results are provided.1Publication Embargo Source optimization in MISO Relaying with channel mean feedback: A stochastic ordering approach(IEEE, 2011-06-05) Ding, M; Zhang, Q. TThis paper investigates the optimum source transmission strategy to maximize the capacity of a multiple-input single-output (MISO) amplify-and-forward relay channel, assuming source-relay channel mean feedback at the source. The challenge here is that relaying introduces a nonconvex structure in the objective function, thereby excluding the possible use of previous methods dealing with mean feedback that generally rely on the concavity of the objective function. A novel method is employed, which divides the feasible set into two subsets and establishes the optimum from one of them by comparison. As such, the optimization is transformed into the comparison of two nonnegative random variables in the Laplace Transform order, which is one of the stochastic orders. It turns out that the optimum transmission strategy is to transmit along the known channel mean and its orthogonal eigenchannels. The condition for rank-one precoding (beamforming) to achieve capacity is also determined. Our results subsume those for traditional MISO precoding with mean feedback.Publication Embargo Interference analysis and outage performance of finite multi-antenna ad hoc networks(IEEE, 2011-07-04) Chen, J; Zhang, Q. T; Ding, MIn this paper, the aggregate interference in a finite-area multi-antenna wireless ad hoc network is statistically characterized. While most of the existing studies model the spatial distribution of transmit nodes as a Poisson point process in an infinite plane, a binomial point process is adopted here to better characterize the node distribution in a finite area. In the test link, maximum-ratio combining (MRC) is employed at the receiver, whereas spatial multiplexing or transmit antenna selection is employed at the transmitter depending on the availability of limited feedback. Moments of aggregate interference as well as outage probability formulas are obtained. Interestingly, for a finite network, our analysis establishes the optimality of single-stream transmissions in spatial multiplexing with a MRC test receiver, and justifies the use of transmit antenna selection for further enhancing the outage performance with limited feedback. Simulations are provided to corroborate the analysis.Publication Embargo Transmit precoding in a noncoherent relay channel with channel mean feedback(IEEE, 2012-01-05) Ding, M; Zhang, Q. TThis paper investigates the optimal source transmit precoding to maximize the ergodic mutual information between the input and the output of a noncoherent amplify-and-forward relay channel, with multiple antennas at the source and with a single antenna at both the relay and the destination. It is assumed that only the source-relay channel mean information is available at the source. The challenge here is that relaying introduces a nonconvex structure in the objective function. Therefore, previous methods dealing with channel mean feedback, which generally require the concavity of the objective function, cannot be applied. To circumvent the difficulty at hand, a different approach based on stochastic ordering is employed. The stochastic optimization problem here is ultimately transformed into the comparison of two nonnegative random variables in the Laplace transform order. It is shown that the optimal source transmit strategy is to transmit along the known channel mean and its orthogonal eigen-channels. Our result subsumes as an asymptotic case the optimal precoding for multiple-input single-output (MISO) channels without relaying under mean feedback. Furthermore, the analysis can be partially extended to the case with multiple antennas at the relay. Numerical examples are provided to complement and corroborate the analysis.Publication Embargo Distributed precoding for MISO interference channels with channel mean feedback: Algorithms and analysis(IEEE, 2013-06-09) Ding, M; Tirkkonen, O; Berry, R. A; Ulukus, SThis work focuses on the design and analysis of distributed stochastic precoding algorithms for multiple-input single-output (MISO) interference channels, where each transmitter is provided with mean information of its intended channel and that of interfering channels. Unlike in cases where exact channel gains are known as in most existing works, here generalrank precoding is required for optimality instead of the rank-one beamforming. An efficient algorithm for the distributed implementation of the Nash equilibrium precoding is first proposed. A sufficient condition for this algorithm to converge to the unique equilibrium is derived for the two-user case based on stochastic ordering, and is valid for a wide range of system parameters. To improve the sum-rate performance under medium to strong interference, a pricing-based algorithm is also provided and its convergence analyzed. The two algorithms are compared in terms of sum-rate and system overhead.Publication Embargo A general framework for MIMO transceiver design with imperfect CSI and transmit correlation(IEEE, 2009-09-13) Ding, M; Blostein, S. D; Mow, W. H; Siriteanu, CAssuming perfect channel state information (CSI), linear precoding/decoding for multiple-input multiple-output (MIMO) systems has been considered in the literature under various performance criteria, such as minimum total mean-square error (MSE), maximum mutual information, and minimum average bit error rate (BER). It has been shown that these criteria belong to a set of reasonable Schur-concave or Schur-convex objective functions of the diagonal entries of the system mean-square error (MSE) matrix. In this paper, assuming only the knowledge of channel mean and transmit correlation at both ends, a general theoretical framework is presented to derive the optimum precoder and decoder for MIMO systems using these objective functions. It is shown that for all these objective functions the optimum transceivers share a similar structure. Compared to the case with perfect CSI, a linear filter is added to both ends to balance the suppression of channel noise and the additional noise induced from channel estimation error. Simulation results are provided.Publication Embargo Stochastic precoding for MISO interference channels with channel mean feedback(IEEE, 2012-03-05) Ding, M; Zhang, Q. TThis work considers linear precoding strategies for multiple-input single-out (MISO) interference channels with channel mean feedback at transmitters, where the interference at each receiver is treated as additive noise. The challenge here is that previous precoder designs with perfect channel state information (CSI) at transmitters do not apply and new approaches are required. Based on the Laplace transform order, an altruistic non-equilibrium strategy, i.e., the stochastic zero forcing, is first proposed under practical assumptions, generalizing the traditional zero forcing which requires perfect CSI. Interestingly, the precoding matrices here are all rank-one beamformers as in the traditional zero forcing. The competitive use of the common physical media in MISO interference channels is also formulated as a strategic noncooperative game. In contrast to the perfect CSI case with a unique rank-one Nash equilibrium, with channel mean feedback, the Nash equilibria here are not necessarily rank-one in general. Nevertheless, when achieved by the rank-one beamforming, the equilibrium is unique and convenient for implementation. Accordingly, the condition for beamforming to achieve the equilibrium is derived. Comparisons of the above two strategies reveal no overall dominance of one over the other, thereby establishing stochastic zero forcing as an alternative to the Nash equilibrium designs.Publication Embargo MIMO LMMSE transceiver design with imperfect CSI at both ends(IEEE, 2007-06-24) Blostein, S. D; Ding, MThis paper presents a new result on minimum total mean squared error (MSE) joint transceiver design for multiple-input multiple-output (MIMO) systems, with imperfect channel state information (CSI) at both ends and subject to a total power constraint. The channel knowledge here is the channel mean and transmit correlation information. The joint design is formulated into an optimization problem, to which the closed-form optimum solution is found. The optimum precoder consists of a linear filter, a matrix which collects effective channel eigenmodes, and a diagonal power allocation matrix. The linear filter balances the suppression of channel noise and the additional noise induced by channel estimation error. Given the precoder, the optimum decoder is simply a linear minimum MSE (LMMSE) data estimator. The performance degradations due to imperfect channel estimation and/or transmit correlation are demonstrated by simulation results. The relation between the minimum total MSE design and the maximum mutual information design is determined as well, under the above mentioned imperfect CSI.Publication Embargo Joint optimization for multiuser MIMO uplink systems with imperfect CSI(IEEE, 2008-05-24) Ding, M; Blostein, S. DIn this paper, a joint linear minimum sum meansquared error transceiver optimization problem is formulated for multiuser MIMO uplink systems under a sum power constraint assuming imperfect channel state information (CSI). Two methods are proposed to solve this problem. One is based on the associated Karush-Kuhn-Tucker conditions. The other is to solve an equivalent problem, approaching the solution by solving a sequence of semi-definite programming problems. After obtaining the solution to the optimization problem, we investigate the effects of channel estimation errors and antenna correlation at the base station on system performance. Simulation results are provided.