Yunxiang Jiang

Distributed Power Splitting for SWIPT in Relay Interference Channels Using Game Theory

In this paper, we consider simultaneous wireless information and power transfer (SWIPT) in relay interference channels, where multiple source-destination pairs communicate through their dedicated energy harvesting relays. Each relay needs to split its received signal from sources into two streams: one for information forwarding and the other for energy harvesting. We develop a distributed power splitting framework using game theory to derive a profile of power splitting ratios for all relays that can achieve a good network-wide performance. Specifically, non-cooperative games are respectively formulated for pure amplify-and-forward (AF) and decode-and-forward (DF) networks, in which each link is modeled as a strategic player who aims to maximize its own achievable rate. The existence and uniqueness for the Nash equilibriums (NEs) of the formulated games are analyzed and a distributed algorithm with provable convergence to achieve the NEs is also developed. Subsequently, the developed framework is extended to the more general network setting with mixed AF and DF relays. All the theoretical analyses are validated by extensive numerical results. Simulation results show that the proposed game-theoretical approach can achieve a near-optimal network-wide performance on average, especially for the scenarios with relatively low and moderate interference.

A game-theoretical model for wireless information and power transfer in relay interference channels.

In this paper, we consider simultaneous wireless information and power transfer (SWIPT) in relay interference channels, where multiple source-destination pairs communicate through their dedicated energy harvesting relays. Game theory is applied to design a distributed power splitting scheme for the considered system. Particularly, a non-cooperative game is formulated, in which each link is modeled as a strategic player who aims to maximize its own achievable rate. The existence and uniqueness of the Nash equilibrium (NE) for the formulated game is analyzed. A distributed algorithm is proposed based on the best response functions to achieve the NE. Numerical results show that the proposed game-theoretical approach can achieve a near-optimal network-wide performance.

Resource Allocation for Multiuser OFDMA Hybrid Full/Half-Duplex Relaying Systems With Direct Links

Resource allocation is an important strategy to optimize system performance in multiuser cooperative orthogonal frequency-division multiple-access (OFDMA) systems. In this paper, we jointly consider three different transmission modes in cooperative OFDMA systems, i.e., direct transmission (DT) mode, half-duplex (HD) relay cooperative transmission (HDRCT) mode, and full-duplex (FD) relay transmission (FDRT) mode. The joint optimization problem of transmission mode selection, subcarrier assignment, relay selection, subcarrier pairing, and power allocation (PA) is investigated. In this paper, we transform the binary assignment problem into a maximum-weighted bipartite matching problem, which can be solved by the classical Hungarian method. Based on the dual method, we solve the joint PA and binary assignment problem iteratively. Specifically, since the direct link is considered interference in the FD relay transmission mode, the PA problem in FD relay transmission mode is nontrivial. Thus, we provide a novel hierarchical dual method to solve the PA problem in FD relay transmission mode. In addition, in HDRCT mode, the joint transmission of both the source and relay is taken into account, and we provide a simple and insightful PA scheme. Simulation results show that the proposed algorithms can significantly enhance the overall system throughput, compared with previous works.

Max–Min Weighted Downlink SINR With Uplink SINR Constraints for Full-Duplex MIMO Systems

In this paper, we investigate a max–min weighted signal-to-interference-plus-noise-ratio (SINR) problem in a full-duplex multiuser multiple-input-multiple-output system, where a full-duplex-capable base station (BS) equipped with multiple antennas communicates with multiple half-duplex downlink and uplink users under the same system resources. Specifically, we consider a practical scenario where the downlink minimum weighted SINR is maximized under specific SINR constraints for uplink users. Moreover, the optimization is conducted by jointly considering the BS transmit power, the transmit power of uplink users, and BS transmit and receive beamforming. This optimization problem is, therefore, subject to multiple uplink SINR constraints and multiple transmit power constraints. Due to the SINR constraints, negative matrix components arise and hence the optimization problem cannot be directly solved by the standard approach, i.e., Perron–Frobenius theory. We have provided an explicit iterative scheme to solve this joint optimization problem with a strict proof. The proposed algorithm is proved to converge to Karush–Kuhn–Tucker points. Simulation results show that our proposed algorithm has a fast convergence rate and leads to a better performance compared with other optimization techniques that do not jointly consider all parameters.

Parameter Identification of Chaotic Systems by a Novel Dual Particle Swarm Optimization

In this paper, we propose a dual particle swarm optimization (PSO) algorithm for parameter identification of chaotic systems. We also consider altering the search range of individual particles adaptively according to their objective function value. We consider both noiseless and noisy channels between the original system and the estimation system. Finally, we verify the effectiveness of the proposed dual PSO method by estimating the parameters of the Lorenz system using two different data acquisition schemes. Simulation results show that the proposed method always outperforms the traditional PSO algorithm.

Paired-relay-selection schemes for two-way relaying with network coding

To exchange information between two sources in a two-way relaying network with multiple potential relays, most researches focus on two-hop relay system with single-relay-selection (SRS) scheme. Comparing with SRS scheme, the authors first design a paired-relay-selection (PRS) scheme in which a pair of ‘best’ relays broadcast network-coded information to other nodes (source or relay). They propose an optimal selection algorithm and a suboptimal algorithm that selects the pair of ‘best’ relays in the PRS scheme and they describe how the nodes exchange information in a frame consisting of four timeslots. Both the analytical and simulation results show that when the pathloss exponent is large and/or there is a sufficient number of relays to choose from, using two relay nodes can provide a lower outage compared with using only one relay node even under the same total transmit power in uniformly distributed relay networks. In addition, to reduce the overhead of the PRS scheme, they propose an iterative-PRS (I-PRS) scheme in which the paired relay is selected in an iterative and opportunistic way. Simulation results show that the I-PRS scheme has nearly the same outage performance as the PRS scheme under time-invariant channels and significantly outperforms the PRS scheme under time-varying channels.

Full‐duplex OFDMA multi‐user cellular systems: resource allocation and user pairing

In this paper, we consider an orthogonal frequency division multiple access multi-user cellular system with one full-duplex base station communicating with multiple half-duplex users in a bidirectional way. The uplink and downlink transmissions are coupled together because of the existence of the self-interference at the base station and the inter-user interference (IUI) from the uplink users to the downlink users. We aim to maximize the system sum-rate of uplink and downlink transmissions by optimally pairing the uplink and downlink users and allocating the subcarriers and powers to these users. We formulate the problem as a mixed integer nonlinear programming problem. A two-layer iterative solution based on the dual method and the sequential parametric convex approximation (SPCA) method is proposed. It is referred to as the dual–SPCA algorithm. The dual–SPCA algorithm requires the IUI channel state information to be available at the base station, and hence, a significant overhead is generated. To reduce the amount of overhead required, we assume that the IUI channel model is known at the base station, and we design a location-aware resource allocation algorithm with limited channel state information that maximizes the system sum-rate. Simulation results show that when self-interference is low, uplink and downlink user-pairing can provide significant improvement on the system sum-rate compared with the conventional unidirectional half-duplex transmission. In addition, by considering two different network deployments, such as urban macro cell scenario and small cell scenario, we show that the improvement of full-duplex transmission over half-duplex transmission highly depends on the channel parameters. Copyright

Energy efficiency optimisation in full-duplex relay systems

Energy efficiency of relay communications has attracted much interest recently. Most research efforts have focused on half-duplex systems. As there has been significant progress in practical implementation of self-interference cancellation, full-duplex systems will have a promising potential in the near future. In this letter, energy efficiency of a full-duplex relay system under the total power constraint and fixed circuitry power consumption is studied. An optimisation problem is formulated towards maximising the system energy efficiency. Unfortunately, this problem is non-trivial and cannot be solved by conventional fractional programming methods, such as the Dinkelbachs method. To resolve this issue, an algorithm called sequential parametric convex approximation-Dinkelbach is proposed in this letter. Simulation results show that the proposed algorithm can converge to the global optimum very quickly. Copyright

Relay cooperation schemes for the multiple access relay channel: Compute-and-forward and successive interference cancellation

In this paper, we propose two relay cooperation schemes for a Multiple Access Relay Channel (MARC). The proposed schemes make use of a lattice-based approach to block Markov encoding. The first scheme applies Compute-And-Forward (CAF) at the relay and Successive Interference Cancellation (SIC) at the destination; whereas the second one applies SIC at both the relay and the destination. A detailed analysis of the rates achieved by these two schemes is also provided. The schemes are further studied under two specific channel settings.

Improved Min-Sum Decoding for 2-D Intersymbol Interference Channels

In this paper, 2-D normalized min-sum (NMS) algorithm and offset min-sum (OMS) algorithm are proposed for efficient decoding of low-density parity-check (LDPC) codes in 2-D intersymbol interference (ISI) ultra-high density magnetic recording channels, such as bit-patterned magnetic recording and 2-D magnetic recording, where a reduced-complexity 2-D detector based on the iterative row-column soft detection feedback with Gaussian approximation detector is employed instead of the full 2-D Bahl-Cocke-Jelinek-Raviv (BCJR) detector. The normalization and offset factors of the 2-D NMS and 2-D-OMS, are optimized based on the extended density evolution for LDPC coded 2-D ISI channel, respectively. Simulation results show the performance loss caused by the reduced-complexity LDPC decoder can be almost fully recovered by the proposed approaches, while retaining the benefit of low complexity in decoder compared with the belief propagation (BP) decoding. Furthermore, both the NMS and OMS exhibit a lower error floor than that of BP decoding in high signal-to-noise ratio region.