Proposed Beamforming Design Research Articles

Transmission design for ISAC‐WPT backscatter RFID systems

AbstractIn this letter, a novel integrated sensing and communication (ISAC) scenario with wireless power transfer (ISAC‐WPT) is investigated. In this new setup, an access point simultaneously employs communication and sensing beams to serve a communication user, detect an RFID tag, and power an energy receiver. The objective is to design the sensing and communication beams to minimize the total transmit power while satisfying the requirements of tag detection, communication, and energy harvesting. To address the corresponding non‐convex problem, the constraints are reformulated into convex second‐order cone constraints, thereby obtaining the globally optimal solution. To further reduce computational complexity, zero‐forcing is employed to design the beamforming vectors, followed by solving a convex optimization problem to determine the optimal power allocation between sensing and communication beams. The simulation results demonstrate the effectiveness of the proposed beamforming designs, highlighting the potential of ISAC‐WPT Backscatter RFID systems.

Beam Designs for Millimeter-Wave Backhaul With Dual-Polarized Uniform Planar Arrays

This paper proposes hybrid beamforming designs for millimeter-wave (mmWave) multiple-input multiple-output (MIMO) backhaul systems equipped with uniform planar arrays (UPAs) of dual-polarization antennas at both the transmit and receive base stations. The proposed beamforming designs are to near-optimally solve optimization problems taking the dual-polarization UPA structure into account. Based on the solutions of optimization problems, this paper shows it is possible to generate the optimal dual-polarization beamformer from the optimal single-polarization beamformer sharing the same optimality. As specific examples, squared error and magnitude of inner product are considered respectively for optimization criteria. To optimize proposed beamformers, partial channel information is needed, and the use of low overhead pilot sequences is also proposed to figure out the required information. Simulation results verify that the resulting beamformers have the most uniform gain (with the squared error criterion) or the highest average gain (with the magnitude of inner product criterion) in the covering region with the UPA of dual-polarization antennas.

A Novel Multiuser Beamforming System With Reduced Complexity and Beam Optimizations

Analog beamforming is widely used in the incoming 5G/B5G communications systems to leverage against power consumption by significantly reducing the number of RF chains. In this paper, we propose a new multiuser beamforming scheme that allows the number of RF chains to be smaller than the number of users. In addition, we propose the beamforming algorithms to minimize the transmit power and weighted symbol error rates for the proposed scheme. For both high- and low-SNR regimes, the proposed beamforming designs provide simple closed-form solutions. The simulation results show that with half the number of RF chains and, thus, lower hardware cost, the proposed scheme outperforms the conventional zero-forcing beamforming systems in several interested parameter settings. Meanwhile, the performance degradation due to the quantization effect of the proposed system is less pronounced than that of the conventional beamforming systems.

SWIPT in MISO full-duplex systems

This paper investigates a multiuser multiple-input singleoutput (MISO) full-duplex (FD) system for simultaneous wireless information and power transfer (SWIPT), in which a multiantenna base station (BS) simultaneously sends wirelessly information and power to a set of single-antenna mobile stations (MSs) using power splitters (PSs) in the downlink and receives information in the uplink in FD mode. In particular, we address the joint design of the receive PS ratio and the transmit power at the MSs, and the beamforming matrix at the BS under signal-to-interferenceplus- noise ratio (SINR) and the harvested power constraints. Using semidefinite relaxation (SDR), we obtain the solution to the problem with imperfect channel state information (CSI) of the selfinterfering channels. Furthermore, we propose another suboptimal zero-forcing (ZF) based solution by separating the optimization of the transmit beamforming vector and the PS ratio. Simulation results are provided to evaluate the performance of the proposed beamforming designs.

Multicast Beamforming Design in Multicell Networks With Successive Group Decoding

We consider a generic problem of multicast beamforming design in multicell networks where each base station (BS) has multiple independent messages to multicast and each user intends to decode an arbitrary subset of messages sent from all BSs using successive group decoding (SGD). We first formulate the total transmit power minimization problem subject to the constraints that a target rate vector is achievable by the SGDs at all receivers. This problem is a non-convex quadratically constrained quadratic program and NP-hard. We propose a new method based on solving a sequence of linearly regularized semi-definite programming (SDP) relaxation of the original problem that yields feasible and near-optimal solutions with high probability. Moreover, we propose a decentralized algorithm based on the alternating direction method of multipliers to solve each linearly regularized SDP, which consists of solving a quadratic program at the central controller, and closed-form analytic computations at each BS. Finally, we propose an iterative procedure for joint beamformer and rate optimization under the SGD framework. Numerical results confirm the superiority of the proposed beamformer design in both performance and complexity. It is also demonstrated that, compared with the traditional linear receivers, the SGD receivers achieve both significant rate improvement and energy savings.

General Rank Multiuser Downlink Beamforming With Shaping Constraints Using Real-Valued OSTBC

In this paper we consider optimal multiuser downlink beamforming in the presence of a massive number of arbitrary quadratic shaping constraints. We combine beamforming with full-rate high dimensional real-valued orthogonal space time block coding (OSTBC) to increase the number of beamforming weight vectors and associated degrees of freedom in the beamformer design. The original multi-constraint beamforming problem is converted into a convex optimization problem using semidefinite relaxation (SDR) which can be solved efficiently. In contrast to conventional (rank-one) beamforming approaches in which an optimal beamforming solution can be obtained only when the SDR solution (after rank reduction) exhibits the rank-one property, in our approach optimality is guaranteed when a rank of eight is not exceeded. We show that our approach can incorporate up to 79 additional shaping constraints for which an optimal beamforming solution is guaranteed as compared to a maximum of two additional constraints that bound the conventional rank-one downlink beamforming designs. Simulation results demonstrate the flexibility of our proposed beamformer design.

Secure Beamforming via Amplify-and-Forward Relays in Machine-to-Machine Communications

We consider the collaborative use of amplify-and-forward relays to form a beamforming system and provide physical layer security for a wireless machine-to-machine (M2M) communication network. We investigate two objectives: (i) the achievable secrecy rate maximization subject to the relay power constraint and (ii) the relay transmit power minimization under a secrecy rate constraint. For the first objective, we propose a secrecy rate maximization (SRM) beamforming scheme. The secrecy rate maximization problem can be formed into a two-level optimization problem and we solve it using semidefinite relaxation (SDR) techniques. To reduce the complexity of the SRM beamforming scheme, a virtual eavesdropper-based SRM (VE-SRM) beamforming scheme is proposed, in which we hypothesize a virtual eavesdropper instead of all eavesdroppers and maximize the secrecy rate according to the virtual eavesdropper. In addition, for the second objective, we design a relay power minimization (RPM) beamforming scheme, in which an iterative algorithm combining the SDR technology and the gradient-based method is devised by studying the convexity of the RPM problem. By relaxing the constraints of the RPM beamforming scheme, we propose a virtual eavesdropper-based RPM (VERPM) beamforming scheme, which reduces the multivariate RPM problem to a problem of a single variable, and thus an analytical solution is obtained. Our proposed beamforming designs can work well even if the number of eavesdroppers is larger than that of relays, while the existing schemes, for example, the null-space beamforming schemes, cannot work under this condition. Simulation results are presented to demonstrate the significance of performance improvements with the SRM and RPM beamforming schemes. It is also shown that the virtual eavesdropper approaches significantly reduce the complexity with acceptable performance degradation.

Efficient Relay Beamforming Design With SIC Detection for Dual-Hop MIMO Relay Networks

In this paper, we consider a dual-hop multiple-input-multiple-output (MIMO) relay wireless network, in which a source-destination pair, which are both equipped with multiple antennas, communicates through a large number of half-duplex amplify-and-forward (AF) relay terminals. Two novel linear beamforming schemes based on the matched filter and regularized zero-forcing precoding techniques are proposed for the MIMO relay system. We focus on the linear process at the relay nodes and design the new relay beamformers by utilizing the channel-state information (CSI) of both backward and forward channels. The proposed beamforming designs are based on the QR decomposition filter at the destination node, which performs successive interference cancellation to achieve the maximum spatial-multiplexing gain. Simulation results demonstrate that the proposed beamformers that fulfil both the intranode array gain and distributed array gain outperform other relaying schemes under different system parameters in terms of the ergodic capacity.

SINR Balancing Technique for Downlink Beamforming in Cognitive Radio Networks

We propose a novel signal to interference and noise (SINR) balancing technique for a downlink cognitive radio network (CRN) wherein multiple cognitive users (also referred to as secondary users (SUs)) coexist and share the licensed spectrum with the primary users (PUs) using the underlay approach. The proposed beamforming technique maximizes the worst SU SINR while ensuring that the interference leakage to PUs is below specific thresholds. Due to the additional interference constraints imposed by PUs, the principle of uplink-downlink duality used in the conventional downlink beamformer design cannot be directly applied anymore. To circumvent this problem, using an algebraic manipulation on the interference constraints, we propose a novel SINR balancing technique for CRNs based on uplink-downlink iterative design techniques. Simulation results illustrate the convergence and the optimality of the proposed beamformer design.