Ang Li

Exploiting Constructive Mutual Coupling in P2P MIMO by Analog-Digital Phase Alignment

In this paper, we propose a joint analog-digital (A/D) beamforming scheme for the point-to-point multiple-input-multiple-output system, where we exploit mutual coupling by optimizing the load impedances of the transmit antennas. Contrary to the common conception that mutual coupling strictly harms the system performance, we show that mutual coupling can be beneficial by exploiting the concept of constructive interference. By changing the value of each load impedance for the antenna array based on convex optimization, the mutual coupling effect can be manipulated so that the resulting interference aligns constructively to the useful signal vector. We first prove that the full elimination of mutual coupling effect is not achievable solely by tuning the values of the antenna load impedances. We then introduce the proposed A/D scheme for both PSK and QAM modulations, where performance gains with respect to conventional techniques are obtained. The implementation of the proposed schemes is also discussed, where a lookup table can be built to efficiently apply the calculated load impedances. The numerical results show that the proposed schemes can achieve an improved performance compared to systems with fixed mutual coupling, especially when the antenna spacing is small.

Hybrid Analog-Digital Millimeter-Wave MU-MIMO Transmission With Virtual Path Selection

In this letter, we propose a low-complexity hybrid precoding and combining design for the millimeter-wave MU-MIMO transmission, applicable to both fully connected and sub-connected structures. Analog precoding and combining schemes are first designed, where a joint approach, a decoupled approach, and a sub-optimal approach are proposed to harvest the array gain. Virtual path selection is performed to maximize the channel gain of the analog effective channel. Then, based on the effective channel, a low-dimensional zero-forcing precoding is applied in the baseband to manage the interference. The simulation results show that the proposed techniques offer an enhanced performance-complexity tradeoff compared with both existing hybrid schemes and fully digital schemes.

A Constellation Scaling Approach to Vector Perturbation for Adaptive Modulation in MU-MIMO

It is known that vector perturbation (VP) precoding does not apply to the case where users employ different modulations, while existing solutions for this scenario are suboptimal. In this letter, a joint vector perturbation precoding algorithm is proposed for multiuser MIMO (MU-MIMO) downlink system in the adaptive modulation scenario where different users apply different modulation types. Compared with conventional block diagonalized vector perturbation (BD-VP) and user grouping VP where the search dimension of the perturbation vector is reduced, the proposed algorithm keeps the search dimension unchanged by applying a simple transformation to the VP operation. Our analysis and results show that the proposed algorithm provides an applicable VP solution to the adaptive modulation scenario, with optimal VP performance.

Robust MIMO Beamforming for Cellular and Radar Coexistence

In this letter, we consider the coexistence and spectrum sharing between downlink multi-user multiple-input-multiple-output (MU-MIMO) communication and an MIMO radar. For a given performance requirement of the downlink communication system, we design the transmit beamforming such that the detection probability of the radar is maximized. While the original optimization problem is non-convex, we exploit the monotonically increasing relationship of the detection probability with the non-centrality parameter of the resulting probability distribution to obtain a convex lower-bound optimization. The proposed beamformer is designed to be robust to imperfect channel state information (CSI). Simulation results verify that the proposed approach facilitates the coexistence between radar and communication links, and illustrates a scalable tradeoff between the two systems’ performance.

MIMO Transmission for Single-Fed ESPAR With Quantized Loads

Compact parasitic arrays in the form of electronically steerable parasitic antenna radiators (ESPARs) have emerged as a new antenna structure that achieves multiple-input-multiple-output (MIMO) transmission with a single RF chain. In this paper, we study the application of precoding on practical ESPARs, where the antennas are equipped with load impedances of quantized values. We analytically study the impact of the quantization on the system performance, where it is shown that while ideal ESPARs with ideal loads can achieve a similar performance to conventional MIMO, the performance of ESPARs will be degraded when only loads with quantized values are available. We further extend the performance analysis to imperfect channel state information. In order to alleviate the performance loss, we propose to approximate the ideal current vector by optimization, where a closed-form solution is further obtained. This enables the use of ESPARs in practice with quantized loads. Simulation results validate our analysis and show that a significant performance gain can be achieved with the proposed scheme over ESPARs with quantized loads. Finally, the tradeoff between performance and power consumption is shown to be favorable for the proposed ESPAR approaches compared with conventional MIMO, as evidenced by our energy efficiency results.

Hybrid precoding and combining design for millimeter-wave multi-user MIMO based on SVD

In this paper, we focus on the millimeter-wave multi-user multiple-input-multiple-output (mmWave MU-MIMO) systems and propose a low-complexity hybrid precoding and combining design, which is applicable to both fully-connected structures and sub-connected structures. Based on the channel knowledge of each user, the analog combiner for each user is independently designed based on the singular value decomposition (SVD), while the analog precoder is obtained by the conjugate transposition to maximize the effective channel gain. Then, with the resulting effective analog channel, low-dimensional baseband precoders can be efficiently applied. The proposed scheme requires no optimization techniques or any complicated iterative algorithms, while the numerical results show that it can approach the performance of fully digital schemes and even achieve a better performance in some scenarios. It is also observed that sub-connected structures can achieve a much higher power efficiency compared to fully-connected structures and are therefore promising for the future green communication systems.

A Two-Stage Vector Perturbation Scheme for Adaptive Modulation in Downlink MU-MIMO

Conventional vector perturbation (VP) is not directly applicable to adaptive modulation, whereas other existing algorithms are suboptimal due to the reduced search dimension of perturbation vectors. In this paper, by applying a simple transformation to the conventional VP operation, the search dimension for the proposed joint VP is made equal to that of conventional VP, and therefore, the performance advantages of VP still hold in this scenario. Furthermore, to reduce the computational complexity, a joint constructive VP scheme is introduced by exploiting constructive interference to simplify the VP operation. By doing so, the sophisticated search for perturbation vectors is partially replaced by a quadratic programming problem, therefore saving significant computational complexity. Our analysis and results show that the proposed scheme offers an improved performance-complexity tradeoff compared with conventional VP approaches by means of the measurement in energy efficiency.

MU-MIMO Communications With MIMO Radar: From Co-Existence to Joint Transmission

Beamforming techniques are proposed for a joint multi-input-multi-output (MIMO) radar-communication (RadCom) system, where a single device acts as radar and a communication base station (BS) by simultaneously communicating with downlink users and detecting radar targets. Two operational options are considered, where we first split the antennas into two groups, one for radar and the other for communication. Under this deployment, the radar signal is designed to fall into the null-space of the downlink channel. The communication beamformer is optimized such that the beampattern obtained matches the radar’s beampattern while satisfying the communication performance requirements. To reduce the optimizations’ constraints, we consider a second operational option, where all the antennas transmit a joint waveform that is shared by both radar and communications. In this case, we formulate an appropriate probing beampattern, while guaranteeing the performance of the downlink communications. By incorporating the SINR constraints into objective functions as penalty terms, we further simplify the original beamforming designs to weighted optimizations, and solve them by efficient manifold algorithms. Numerical results show that the shared deployment outperforms the separated case significantly, and the proposed weighted optimizations achieve a similar performance to the original optimizations, despite their significantly lower computational complexity.

Interference exploitation for radar and cellular coexistence - the power-efficient approach

We propose a novel approach to enable the coexistence between Multi-Input-Multi-Output (MIMO) radar and downlink multi-user Multi-Input-Single-Output (MU-MISO) communication system. By exploiting the constructive multi-user interference (MUI), the proposed approach trades-off useful MUI power for reducing the transmit power, to obtain a power efficient transmission. This paper focuses on two optimization problems: a) Transmit power minimization at the base station (BS) while guaranteeing the receive signal-to-interference-plus-noise ratio (SINR) level of downlink users and the interference-to-noise ratio (INR) level to radar; b) Minimization of the interference from BS to radar for a given requirement of downlink SINR and transmit power budget. To reduce the computational overhead of the proposed scheme in practice, an algorithm based on gradient projection is designed to solve the power minimization problem. In addition, we investigate the trade-off between the performance of radar and communication, and analytically derive the key metrics for MIMO radar in the presence of the interference from the BS. Finally, a robust power minimization problem is formulated to ensure the effectiveness of the proposed method in the case of imperfect Channel State Information (CSI). Numerical results show that the proposed method achieves a significant power saving compared to conventional approaches, while obtaining a favorable performance-complexity trade-off.

Performance analysis for single-fed ESPAR in the presence of impedance errors and imperfect CSI

Existing MIMO precoding techniques assume conventional antenna arrays with multiple radio-frequency (RF) chains each connected to a different antenna. Towards small portable devices and base stations, single-fed compact arrays, also known as electronically steerable parasitic antenna radiators (ESPAR) have recently emerged as a new antenna structure that requires only a single RF chain. In this paper, we study the ESPAR based antenna arrays and explore linear precoding schemes for ESPAR antennas. The closed-form expression for the computation of the tunable loads and the feeding voltage is firstly shown and the impact of impedance errors and imperfect CSI on the performance is also investigated analytically. It will be shown that the impedance errors will act as an additional noise source that is independent of the SNR and thus result in an error floor at high SNR. We further study the energy efficiency of both conventional MIMO and ESPAR-based MIMO systems. Simulation results validate our analysis and show that ESPAR without impedance errors can achieve a similar performance to conventional antenna arrays and a higher energy efficiency, while the performance degradation due to impedance errors motivates the design of robust precoding schemes.