Browsing by Author "Ding, M"

Now showing 1 - 16 of 16

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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, S
This 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.
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Energy–Efficiency Fairness of Interference Multi-Relay Networks for Multi-User Communications
(IEEE, 2021-03) Ding, M; Atapattu, S; Weeraddana, C; Evans, J
We 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.
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.1
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, C
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 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.
Embargo
Interference analysis and outage performance of finite multi-antenna ad hoc networks
(IEEE, 2011-07-04) Chen, J; Zhang, Q. T; Ding, M
In 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.
Embargo
Interference statistics and performance analysis of MIMO ad hoc networks in binomial fields
(IEEE, 2012-02-28) Chen, J; Zhang, Q. T; Ding, M
This paper investigates the interference statistics and system performance of a finite multiple-input-multiple-output (MIMO) ad hoc network. A finite network contains a finite number of nodes in a finite region. For such a network, the binomial point process, rather than the ubiquitously employed Poisson point process, is adopted to characterize the spatial node distribution. Reception techniques such as the maximal ratio combining (MRC) and zero forcing (ZF) are employed at the receiver, around which a guard zone is deployed. Either spatial multiplexing or antenna selection is employed at the transmitter side, depending on the availability of feedback. The moment generating functions of the aggregate interference power are first derived, based on which the moments of interference and the outage probability of a test link are obtained. It is shown that the full diversity provided by the channel can be achieved by single-stream transmission, including transmit antenna selection. A network performance measure, i.e., the average network throughput, is also analyzed. Simulations are provided to complement the analysis.
Embargo
Joint optimization for multiuser MIMO uplink systems with imperfect CSI
(IEEE, 2008-05-24) Ding, M; Blostein, S. D
In 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.
Embargo
Maximum mutual information design for MIMO systems with imperfect channel knowledge
(IEEE, 2010-09-13) Ding, M; Blostein, S. D
New results on maximum mutual information design for multiple-input multiple-output (MIMO) systems are presented, assuming that both transmitter and receiver know only an estimate of the channel state as well as the transmit and receive correlation. Since an exact capacity expression is difficult to obtain for this case, a tight lower-bound on the mutual information between the input and the output of a MIMO channel has been previously formulated as a design criterion. However, in the previous literature, there has been no analytical expression of the optimum transmit covariance matrix for this lower-bound. Here it is shown that for the general case with channel correlation at both ends, there exists a unique and globally optimum transmit covariance matrix whose explicit expression can be conveniently determined. For the special case with transmit correlation only, the closed-form optimum transmit covariance matrix is presented. Interestingly, the optimal transmitters for the maximum mutual information design and the minimum total mean-square error design share the same structure, as they do in the case with perfect channel state information. Simulation results are provided to demonstrate the effects of channel estimation errors and channel correlation on the mutual information.
Embargo
MIMO LMMSE transceiver design with imperfect CSI at both ends
(IEEE, 2007-06-24) Blostein, S. D; Ding, M
This 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.
Embargo
MIMO minimum total MSE transceiver design with imperfect CSI at both ends
(IEEE, 2008-10-31) Ding, M; Blostein, S. D
This paper presents new results on joint linear transceiver design under the minimum total mean-square error (MSE) criterion, with channel mean as well as both transmit and receive correlation information at both ends of a multiple-input multiple-output (MIMO) link. The joint design is formulated into an optimization problem. The optimum closed-form precoder and decoder are derived. Compared to the case with perfect channel state information (CSI), linear filters are added at both ends to balance the suppression of channel noise and the noise from imperfect channel estimation. The impact of channel estimation error as well as channel correlation on system performance is assessed, based on analytical and simulation results.
Open Access
Multiple-input multiple-output wireless system designs with imperfect channel knowledge
(Queen's University, 2008-07) Ding, M
Employing multiple transmit and receive antennas for wireless transmissions opens up the opportunity to meet the demand of high-quality high-rate services envisioned for future wireless systems with minimum possible resources, e.g., spectrum, power and hardware. Empowered by linear precoding and decoding, a spatially multiplexed multiple-input multiple-output (MIMO) system becomes a convenient framework to offer high data rate, diversity and interference management. While most of the current precoding/decoding designs have assumed perfect channel state information (CSI) at the receiver, and sometimes even at the transmitter, in this thesis we will design the precoder and decoder with imperfect CSI at both the transmit and the receive sides, and investigate the joint impact of channel estimation errors and channel correlation on system structure and performance. The meansquare error (MSE) related performance metrics will be used as the design criteria. We begin with the minimum total MSE precoding/decoding design for a single-user MIMO system assuming imperfect CSI at both ends of the link. Here the CSI includes the channel estimate and channel correlation information. The closed-form optimum precoder and decoder are determined for the special case with no receive correlation. For the general case with correlation at both ends, the structures of the precoder and decoder are also determined. It is found that compared to the perfect CSI case, linear filters are added to the transceiver structure to balance the channel noise and the additional noise caused by imperfect channel estimation, which improve system robustness against imperfect CSI. i Furthermore, the effects of channel estimation error and channel correlation are coupled together, and are quantified by simulations. With imperfect CSI at both ends, the exact capacity expression for a single-user MIMO channel is difficult to obtain. Instead, upper- and lower-bounds on capacity have been derived, and the lower-bound has been used for system design. The closed-form transmit covariance matrix for the lower-bound has not been found in literature, which is referred to as the maximum mutual information design problem with imperfect CSI. Here we transform the transmitter design into a joint precoding/decoding design problem. The closed-form optimum transmit covariance matrix is then derived for the special case with no receive correlation, whereas for the general case with non-trivial correlation at both ends, the optimum structure of the transmit covariance matrix is determined. The close relationship between the maximum mutual information design and the minimum total MSE design is discovered assuming imperfect CSI. The tightness and accuracy of the capacity lower-bound is evaluated by simulation. The impact of imperfect CSI on single-user MIMO ergodic channel capacity is also assessed. For robust multiuser MIMO communications, minimum average sum MSE transceiver (precoder-decoder pairs) design problems are formulated for both the uplink and the downlink, assuming imperfect channel estimation and channel correlation at the base station (BS). We propose improved iterative algorithms based on the associated Karush-KuhnTucker (KKT) conditions. Under the assumption of imperfect CSI, an uplink–downlink duality in average sum MSE is proved, which is often used to simplify the more involved downlink design. As an alternative for solving the uplink problem, a sequential semidefinite programming (SDP) method is proposed. Simulations are provided to corroborate the analysis and assess the impacts of channel estimation errors and channel correlation at the base station on both the uplink and the downlink system performances.
Embargo
Relation between joint optimizations for multiuser MIMO uplink and downlink with imperfect CSI
(IEEE, 2008-03-31) Ding, M; Blostein, S. D
Joint linear minimum sum mean-squared error (referred to as MSMSE) transmitter and receiver (transceiver) optimization problems are formulated for multiuser MIMO systems under a sum power constraint assuming imperfect channel state information (CSI). Both the uplink and the dual downlink are considered. Based on the Karush-Kuhn-Tucker (KKT) conditions associated with both problems, a relation between the two problems is discovered, which is termed the uplinkdownlink duality in sum MSE under imperfect CSI. As a result, the MSMSEs in both links are the same and any admissible uplink design satisfying the KKT conditions can be translated for application to the downlink, and vice versa. Simulation results are provided to demonstrate the duality and show the impact of imperfect CSI.
Embargo
Source optimization in MISO Relaying with channel mean feedback: A stochastic ordering approach
(IEEE, 2011-06-05) Ding, M; Zhang, Q. T
This 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.
Embargo
Stochastic precoding for MISO interference channels with channel mean feedback
(IEEE, 2012-03-05) Ding, M; Zhang, Q. T
This 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.
Embargo
Transmit precoding in a noncoherent relay channel with channel mean feedback
(IEEE, 2012-01-05) Ding, M; Zhang, Q. T
This 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.
Embargo
Uplink-downlink duality in normalized MSE or SINR under imperfect channel knowledge
(IEEE, 2007-11-26) Ding, M; Blostein, S. D
Duality between the multi-antenna multi-user uplink and the downlink has been discovered in terms of sum rate, capacity region, signal-to-interference-plus-noise-ratio (SINR) region or normalized mean-squared error (MSE) region. Previous work on duality has assumed perfect channel knowledge. However, channel estimation is never perfect in practice. In this paper, channel estimation error as well as antenna correlation at the base station (BS) is taken into account. A multi-user system with multiple antennas at the BS and with single-antenna users is studied. Joint detection and transmission are used in the uplink and the downlink, respectively. It is analytically shown that with imperfect channel state information (CSI), under the same sum power constraint, the achievable SINR regions or the normalized MSE regions in both links are the same, as in the case with perfect CSI. Monte Carlo simulation results and discussions are also provided to complement the analysis.