Guangchi Zhang

Relay Beamforming for Amplify-and-Forward Multi-Antenna Relay Networks with Energy Harvesting Constraint

For amplify-and-forward multi-antenna relay networks with energy harvesting (EH) constraint, we study the optimal relay beamforming problem which maximizes the achievable rate from source to information-decoding receiver subject to the transmit power constraint at relay and the EH constraint at EH receiver. Because of the EH constraint, the beamforming problem is not convex. We propose the optimal beamforming scheme by converting the beamforming problem into a convex semidefinite programming with the rank-one relaxation and Charnes-Cooper transformation. We also propose a suboptimal closed-form beamforming scheme. It is shown from simulations that when the maximum allowable relay transmit power to noise power ratio is high, the performance of proposed suboptimal scheme approaches that of the optimal scheme.

Fast antenna subset selection algorithms for multiple-input multiple-output relay systems

The antenna subset selection technique balances the performance and hardware cost in the multiple-input multiple-output (MIMO) systems, and the problems on the antenna selection in MIMO relay systems have not been fully solved. This paper considers antenna selection on amplify-and-forward (AF) and decode-and-forward (DF) MIMO relay systems to maximise capacity. Since the optimal antenna selection algorithm has high complexity, two fast algorithms are proposed. The selection criterion of the algorithm for AF relay is to maximise a lower bound of the capacity, but not the exact capacity. This criterion reduces algorithmic complexity. The algorithm for DF relay is an extension of an existing antenna subset selection algorithm for one-hop MIMO systems. The authors show the derivations of the algorithms in detail, and analyse their complexity in terms of numbers of complex multiplications. Simulation results show that the proposed algorithms for both cases achieve comparable performance to the optimal algorithm under various conditions, and have decreased complexity.

Joint resource allocation with subcarrier pairing in cooperative OFDM DF multi-relay networks

For conventional subcarrier pairing scheme in cooperative orthogonal frequency division multiplexing decode-and-forward multi-relay networks, to avoid interference, each subcarrier pair (SP) is assigned to a single relay. Over a specific subcarrier, the destination receives signals transmitted from the relay. In this study, to better exploit the degrees of spatial freedom, the authors propose to assign each SP to multiple relays. Thus, over a specific subcarrier, the destination receives signals transmitted from multiple relays. Under the total network power constraint, to maximise the sum transmission rate, they propose a joint resource allocation scheme, in which they jointly optimised the four types of resources: assisting relays selection, transmission mode selection, subcarrier pairing and power allocation. They further propose a suboptimal algorithm which can significantly reduce the computational complexity of the aforementioned optimal allocation scheme with sacrificing little on the performance. It is shown from simulation results that the authors proposed schemes have significant performance improvement over the resource allocation schemes in the literature.

Signal and artificial noise beamforming for secure simultaneous wireless information and power transfer multiple-input multiple-output relaying systems

Simultaneous wireless information and power transfer (SWIPT) is a potential technique to solve the energy scarcity problem in wireless communication networks. Information transmission security is one of the key issues to be addressed in SWIPT. In this study, the authors consider guaranteeing the information transmission security of a multiple-input multiple-output non-regenerative relay system with SWIPT in the physical layer by designing source and relay beamforming to maximise the security rate of the system. The problem is to design the source signal and artificial noise (AN) beamforming and the relay forwarding beamforming jointly, which is highly non-convex. They first propose an alternating optimisation-based algorithm, which designs the beamforming matrices at the source and relay separately and alternately. Next, they propose a joint design algorithm which designs the source signal and AN beamforming and the relay beamforming together. Finally, they propose a non-iterative design algorithm with low complexity. The performances of the proposed design algorithms have been verified by computer simulations.

Signal-to-interference-plus-noise ratio-based multi-relay beamforming for multi-user multiple-input multiple-output cognitive relay networks with interference from primary network

Cognitive radio is a potential technique to solve the spectrum shortage problem in wireless communications. Integrating wireless relaying into the cognitive radio networks can further improve the spectrum efficiency. In this study, a multiple-input multiple-output cognitive relay network is considered, where the primary network (PN) consists of one transmitter-receiver pair and the secondary network consists of multiple active source-destination pairs and non-regenerative relays. All nodes in the networks are deployed with multiple antennas. How to avoid interference to the PN is an important task in the secondary network design. The precoders of the secondary sources and the receivers of the secondary destinations are designed in a well-known zero-forcing way. The secondary relays forward signals for the secondary source-destination pairs by beamforming. With interference cancellation constraints and individual transmit power constraints, a relay beamforming scheme is proposed to maximise the total signal-to-interference-plus-noise ratio (SINR) at the secondary destinations. Then a maximising minimum SINR relay beamforming scheme is further proposed to provide max–min fairness among the secondary source-destination pairs. The beamforming problems are formulated into the quadratically constrained quadratic fractional programming problems, and are solved by the semi-definite relaxation technique. The performances of these beamforming schemes have been verified by computer simulations.

Optimal Precoder Design for Non-Regenerative MIMO Cognitive Two-Way Relay Systems with Underlay Spectrum Sharing

We study the optimal precoder design for a MIMO cognitive two-way relay system with underlay spectrum sharing. The system consists of two secondary users (SUs) and one relay station (RS). We jointly optimize the precoders for SUs and RS with perfect and imperfect channel state information (CSI) between SUs/RS and the primary user, where our design approach is based on the alternate optimization method. For the perfect CSI case, we derive the optimal structure of the RS precoding matrix, which generalizes the result for single-antenna SUs and helps to reduce the search complexity. We develop gradient projection (GP) algorithm to calculate the optimal RS precoder numerically. When the RS precoder is given, we propose a fast algorithm based on generalized water-filling theorem to compute the optimal SU precoders. For the imperfect CSI case, we derive equivalent conditions for the interference power constraints and convert the robust SU precoder optimization into the form of semi-definite programming. As for the robust RS precoder optimization, we relax the interference power constraint related with the RS precoder to be convex and then the GP algorithm can be applied. Finally, simulation results demonstrate the effectiveness of the proposed schemes.

QoS-Driven Jointly Optimal Subcarrier Pairing and Power Allocation for Decode-and-Forward OFDM Relay Systems

In this paper, we investigate the quality-of-service (QoS) driven subcarrier pairing and power allocation for two-hop decode-and-forward (DF) OFDM relay systems. By integrating the concept of effective capacity, our goal is to maximize the system throughput subject to a given delay-QoS constraint. Based on whether the destination can receive the signal transmitted by the source, we consider two scenarios, i.e. OFDM DF relay systems without diversity and OFDM DF relay systems with diversity, respectively. For OFDM DF relay systems without diversity, we demonstrate that the jointly optimal subcarrier pairing and power allocation can be implemented with two separate steps. For OFDM DF relay systems with diversity, we propose an iterative algorithm to achieve jointly optimal subcarrier pairing and power allocation. Furthermore, we find that the analytical results show different conclusions for the two types of OFDM relay systems. For OFDM relay systems without diversity, the optimal power allocation depend on not only the channel quality of subcarriers but also the delay QoS constraints, while the optimal subcarrier pairing just depends on the channel quality of subcarriers. For OFDM relay systems with diversity, both the optimal subcarrier pairing and power allocation depend on the channel quality of subcarriers and the delay QoS constraints. Simulation results show that our proposed scheme offers a superior performance over the existing schemes.

Subcarrier-pair Based Power Allocation for Cooperative OFDM AF Multi-Relay Networks

For conventional subcarrier pairing schemes in cooperative orthogonal frequency division multiplexing amplify and forward multi-relay networks, to avoid interference, each subcarrier pair (SP) is assigned to only one relay. Over a specific subcarrier, the destination receives signals transmitted from only one relay. In our subcarrier pairing scheme, we assign each SP to all the relays. Thus, over a specific subcarrier, the destination receives signals transmitted from all the relays. Since it is assumed that there exists the direct link from the source to the destination, we assume that the source also transmits signals during the second time slot for the direct transmission mode. We propose an enhanced joint subcarrier pairing and power allocation optimization scheme which maximizes the transmission rate subject to total network power constraint. The problem is simplified and solved by using dual method. It is shown from simulation results that our proposed scheme outperforms the other schemes.

Resource allocation for MIMO multi-relay systems with zero-forcing relaying

In this paper, we consider a two-hop multiple-input multiple-output (MIMO) multiple relays communication networks, where each relay employs the zero-forcing (ZF) relaying scheme, we assume that the perfect channel state information (CSI) is available at the source, the destination and the relays. We propose a total relays power allocation (PA) scheme with the sum relays transmit power constraint to maximize the average system capacity. Since the original PA optimization problem is not convex, it is difficult to derive an analytical solution, so we propose to simplify the problem by employing the relaxed power constraint which is slightly higher than the actual sum relays power, then we derive the closed-form solution. The Monte Carlo simulation results shown that our proposed joint PA scheme significantly improves the system capacity compared with the conventional ZF relaying scheme.

Proactive Eavesdropping via Pilot Contamination and Jamming

Proactive eavesdropping is a new paradigm shift in wireless physical layer security from preventing conventional eavesdropping attacks to legitimate intercepting suspicious communications, which has attracted a lot of attention recently. Pilot contamination is one effective technique in proactive eavesdropping, which spoofs the suspicious transmitter on channel estimation by sending the same pilot signal as the suspicious receiver, and lets it leak information in the direction of the legitimate eavesdropper during its transmission. However, this technique may fail when an anti-pilot-contamination mechanism called “energy ratio detector (ERD)” is applied at the suspicious receiver. To deal with the case that the suspicious receiver is a smart device using ERD, in this paper, we study using pilot contamination along with jamming to improve the legitimate eavesdropping performance. We first derive a closed-form expression for the probability of pilot contamination being detected by the suspicious receiver, and use it to obtain a closed-form expression for the eavesdropping rate. Using this theoretical analysis result, we propose an algorithm to maximize the eavesdropping rate by jointly optimizing the pilot contamination power and jamming power via two-dimensional search. Simulation results show that the proposed eavesdropping rate maximization algorithm can significantly improve eavesdropping rate, as compared to other benchmark schemes.