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Meixia Tao

Publications and source records attributed to Meixia Tao.

191 records · Page 11Linked to original sources

Joint Source and Relay Precoding Designs for MIMO Two-Way Relaying Based on MSE Criterion

Properly designed precoders can significantly improve the spectral efficiency of multiple-input multiple-output (MIMO) relay systems. In this paper, we investigate joint source and relay precoding design based on the mean-square-error (MSE) criterion in MIMO two-way relay systems, where two multi-antenna source nodes exchange information via a multi-antenna amplify-and-forward relay node. This problem is non-convex and its optimal solution remains unsolved. Aiming to find an efficient way to solve the problem, we first decouple the primal problem into three tractable sub-problems, and then propose an iterative precoding design algorithm based on alternating optimization. The solution to each sub-problem is optimal and unique, thus the convergence of the iterative algorithm is guaranteed. Secondly, we propose a structured precoding design to lower the computational complexity. The proposed precoding structure is able to parallelize the channels in the multiple access (MAC) phase and broadcast (BC) phase. It thus reduces the precoding design to a simple power allocation problem. Lastly, for the special case where only a single data stream is transmitted from each source node, we present a source-antenna-selection (SAS) based precoding design algorithm. This algorithm selects only one antenna for transmission from each source and thus requires lower signalling overhead. Comprehensive simulation is conducted to evaluate the effectiveness of all the proposed precoding designs.

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Power and Subcarrier Allocation for Physical-Layer Security in OFDMA-based Broadband Wireless Networks

Providing physical-layer security for mobile users in future broadband wireless networks is of both theoretical and practical importance. In this paper, we formulate an analytical framework for resource allocation in a downlink OFDMA-based broadband network with coexistence of secure users (SU) and normal users (NU). The SU's require secure data transmission at the physical layer while the NU's are served with conventional best-effort data traffic. The problem is formulated as joint power and subcarrier allocation with the objective of maximizing average aggregate information rate of all NU's while maintaining an average secrecy rate for each individual SU under a total transmit power constraint for the base station. We solve this problem in an asymptotically optimal manner using dual decomposition. Our analysis shows that an SU becomes a candidate competing for a subcarrier only if its channel gain on this subcarrier is the largest among all and exceeds the second largest by a certain threshold. Furthermore, while the power allocation for NU's follows the conventional water-filling principle, the power allocation for SU's depends on both its own channel gain and the largest channel gain among others. We also develop a suboptimal algorithm to reduce the computational cost. Numerical studies are conducted to evaluate the performance of the proposed algorithms in terms of the achievable pair of information rate for NU and secrecy rate for SU at different power consumptions.

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Optimization Framework and Graph-Based Approach for Relay-Assisted Bidirectional OFDMA Cellular Networks

This paper considers a relay-assisted bidirectional cellular network where the base station (BS) communicates with each mobile station (MS) using OFDMA for both uplink and downlink. The goal is to improve the overall system performance by exploring the full potential of the network in various dimensions including user, subcarrier, relay, and bidirectional traffic. In this work, we first introduce a novel three-time-slot time-division duplexing (TDD) transmission protocol. This protocol unifies direct transmission, one-way relaying and network-coded two-way relaying between the BS and each MS. Using the proposed three-time-slot TDD protocol, we then propose an optimization framework for resource allocation to achieve the following gains: cooperative diversity (via relay selection), network coding gain (via bidirectional transmission mode selection), and multiuser diversity (via subcarrier assignment). We formulate the problem as a combinatorial optimization problem, which is NP-complete. To make it more tractable, we adopt a graph-based approach. We first establish the equivalence between the original problem and a maximum weighted clique problem in graph theory. A metaheuristic algorithm based on any colony optimization (ACO) is then employed to find the solution in polynomial time. Simulation results demonstrate that the proposed protocol together with the ACO algorithm significantly enhances the system total throughput.

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Cooperative Secret Communication with Artificial Noise in Symmetric Interference Channel

We consider the symmetric Gaussian interference channel where two users try to enhance their secrecy rates in a cooperative manner. Artificial noise is introduced along with useful information. We derive the power control and artificial noise parameter for two kinds of optimal points, max-min point and single user point. It is shown that there exists a critical value $P_c$ of the power constraint, below which the max-min point is an optimal point on the secrecy rate region, and above which time-sharing between single user points achieves larger secrecy rate pairs. It is also shown that artificial noise can help to enlarge the secrecy rate region, in particular on the single user point.

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Blind Spectrum Sensing by Information Theoretic Criteria for Cognitive Radios

Spectrum sensing is a fundamental and critical issue for opportunistic spectrum access in cognitive radio networks. Among the many spectrum sensing methods, the information theoretic criteria (ITC) based method is a promising blind method which can reliably detect the primary users while requiring little prior information. In this paper, we provide an intensive treatment on the ITC sensing method. To this end, we first introduce a new over-determined channel model constructed by applying multiple antennas or over sampling at the secondary user in order to make the ITC applicable. Then, a simplified ITC sensing algorithm is introduced, which needs to compute and compare only two decision values. Compared with the original ITC sensing algorithm, the simplified algorithm significantly reduces the computational complexity without losing any performance. Applying the recent advances in random matrix theory, we then derive closed-form expressions to tightly approximate both the probability of false alarm and probability of detection. Based on the insight derived from the analytical study, we further present a generalized ITC sensing algorithm which can provide flexible tradeoff between the probability of detection and probability of false alarm. Finally, comprehensive simulations are carried out to evaluate the performance of the proposed ITC sensing algorithms. Results show that they considerably outperform other blind spectrum sensing methods in certain cases.

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A New SLNR-based Linear Precoding for Downlink Multi-User Multi-Stream MIMO Systems

Signal-to-leakage-and-noise ratio (SLNR) is a promising criterion for linear precoder design in multi-user (MU) multiple-input multiple-output (MIMO) systems. It decouples the precoder design problem and makes closed-form solution available. In this letter, we present a new linear precoding scheme by slightly relaxing the SLNR maximization for MU-MIMO systems with multiple data streams per user. The precoding matrices are obtained by a general form of simultaneous diagonalization of two Hermitian matrices. The new scheme reduces the gap between the per-stream effective channel gains, an inherent limitation in the original SLNR precoding scheme. Simulation results demonstrate that the proposed precoding achieves considerable gains in error performance over the original one for multi-stream transmission while maintaining almost the same achievable sum-rate.

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Superimposed XOR: Approaching Capacity Bounds of the Two-Way Relay Channels

In two-way relay channels, bitwise XOR and symbol-level superposition coding are two popular network-coding based relaying schemes. However, neither of them can approach the capacity bound when the channels in the broadcast phase are asymmetric. In this paper, we present a new physical layer network coding (PLNC) scheme, called \emph{superimposed XOR}. The new scheme advances the existing schemes by specifically taking into account the channel asymmetry as well as information asymmetry in the broadcast phase. We obtain its achievable rate regions over Gaussian channels when integrated with two known time control protocols in two-way relaying. We also demonstrate their average maximum sum-rates and service delay performances over fading channels. Numerical results show that the proposed superimposed XOR achieves a larger rate region than both XOR and superposition and performs much better over fading channels. We further deduce the boundary of its achievable rate region of the broadcast phase in an explicit and analytical expression. Based on these results, we then show that the gap to the capacity bound approaches zero at high signal-to-noise ratio.

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End-to-End Outage Minimization in OFDM Based Linear Relay Networks

Multi-hop relaying is an economically efficient architecture for coverage extension and throughput enhancement in future wireless networks. OFDM, on the other hand, is a spectrally efficient physical layer modulation technique for broadband transmission. As a natural consequence of combining OFDM with multi-hop relaying, the allocation of per-hop subcarrier power and per-hop transmission time is crucial in optimizing the network performance. This paper is concerned with the end-to-end information outage in an OFDM based linear relay network. Our goal is to find an optimal power and time adaptation policy to minimize the outage probability under a long-term total power constraint. We solve the problem in two steps. First, for any given channel realization, we derive the minimum short-term power required to meet a target transmission rate. We show that it can be obtained through two nested bisection loops. To reduce computational complexity and signalling overhead, we also propose a sub-optimal algorithm. In the second step, we determine a power threshold to control the transmission on-off so that the long-term total power constraint is satisfied. Numerical examples are provided to illustrate the performance of the proposed power and time adaptation schemes with respect to other resource adaptation schemes.

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Utility-Based Wireless Resource Allocation for Variable Rate Transmission

For most wireless services with variable rate transmission, both average rate and rate oscillation are important performance metrics. The traditional performance criterion, utility of average transmission rate, boosts the average rate but also results in high rate oscillations. We introduce a utility function of instantaneous transmission rates. It is capable of facilitating the resource allocation with flexible combinations of average rate and rate oscillation. Based on the new utility, we consider the time and power allocation in a time-shared wireless network. Two adaptation policies are developed, namely, time sharing (TS) and joint time sharing and power control (JTPC). An extension to quantized time sharing with limited channel feedback (QTSL) for practical systems is also discussed. Simulation results show that by controlling the concavity of the utility function, a tradeoff between the average rate and rate oscillation can be easily made.

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Resource Allocation for Delay Differentiated Traffic in Multiuser OFDM Systems

Most existing work on adaptive allocation of subcarriers and power in multiuser orthogonal frequency division multiplexing (OFDM) systems has focused on homogeneous traffic consisting solely of either delay-constrained data (guaranteed service) or non-delay-constrained data (best-effort service). In this paper, we investigate the resource allocation problem in a heterogeneous multiuser OFDM system with both delay-constrained (DC) and non-delay-constrained (NDC) traffic. The objective is to maximize the sum-rate of all the users with NDC traffic while maintaining guaranteed rates for the users with DC traffic under a total transmit power constraint. Through our analysis we show that the optimal power allocation over subcarriers follows a multi-level water-filling principle; moreover, the valid candidates competing for each subcarrier include only one NDC user but all DC users. By converting this combinatorial problem with exponential complexity into a convex problem or showing that it can be solved in the dual domain, efficient iterative algorithms are proposed to find the optimal solutions. To further reduce the computational cost, a low-complexity suboptimal algorithm is also developed. Numerical studies are conducted to evaluate the performance the proposed algorithms in terms of service outage probability, achievable transmission rate pairs for DC and NDC traffic, and multiuser diversity.

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