On the energy efficiency of massive MIMO with space-constrained 2D antenna arrays

We examine the deployment of a large multi-user multiple-input multiple-output (MIMO) system and the resulting Energy Efficiency (EE) considering a 2D rectangular array with increasing antenna elements within a fixed physical space. The resulting increasing mutual coupling and correlation among the base station (BS) antennas are incorporated by deriving a practical mutual coupling matrix which considers coupling among all antenna elements. We also provide a realistic analysis of the energy consumption using a new model, taking into account the circuit power consumption as a function of the number of BS antennas and then present a performance analysis of the system with respect to EE. Our analysis shows that while spectral efficiency increases with increasing number of BS antennas in a massive MIMO system, EE does not increase boundlessly when the increasing number of antennas are to be accommodated within a fixed physical space and the total power consumed is considered to be a function of the BS antennas. Accordingly, analytic expressions for the optimum number of antennas to attain maximum EE are obtained

Transmit-Power Efficient Linear Precoding Utilizing Known Interference for the Multiantenna Downlink

It has been shown that the knowledge of both channel and data information at the base station prior to downlink transmission can help increase the received signal-to-noise ratio (SNR) of each user without the need to increase the transmitted power. Achievability is based on the idea of phase alignment (PA) precoding, where instead of nulling out the destructive interference, it judiciously rotates the phases of the transmitted symbols. In this way, they add up coherently at the intended user and yield higher received SNRs. In addition, it is well known that regularized channel inversion (RCI) precoding improves the performance of channel inversion (CI) in multiantenna downlink communications. In line with this and similar to the RCI precoding, in this paper, we propose the idea of regularized PA (RPA), which is shown to improve the performance of original PA precoding. To do this, we first rectify the original PA precoding, deriving a closed-form expression to evaluate the amount of transmit-power reduction achieved for the same average output SNR compared with CI precoding. We then use this new analysis to select the appropriate regularization factor for our proposed RPA scheme. It is shown by means of theoretical analysis and simulations that the proposed RPA precoding outperforms CI, RCI, and PA precoders from both symbol error rate (SER) and throughput perspectives and provides a more power-efficient alternative. This is particularly pronounced as the number of transmit antennas becomes larger, where up to a 50-times reduction in the transmit power is achieved by RPA (PA) compared with RCI (CI) precoding for a given 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

On Range Sidelobe Reduction for Dual-Functional Radar-Communication Waveforms

In this letter, we propose a novel waveform design for multi-input multi-output (MIMO) dual-functional radar-communication systems by taking the range sidelobe control into consideration. In particular, we focus on optimizing the weighted summation of communication and radar metrics under per-antenna power budget. While the formulated optimization problem is non-convex, we develop a first-order descent algorithm by exploiting the manifold structure of its feasible region, which finds a near-optimal solution within a low computational overhead. Numerical results show that the proposed waveform design outperforms the conventional techniques by improving the communication rate while reducing the range sidelobe level

Secure Dual-functional Radar-Communication Transmission: Hardware-Efficient Design

This paper investigates the constructive interference (CI) based constant evelope (CE) waveform design problem aiming at enhancing the physical layer (PHY) security in dual-functional radar-communication (DFRC) systems. DFRC systems detect the radar target and communicate with downlink cellular users in wireless networks simultaneously, where the radar target is regarded as a potential eavesdropper which might surveil the data from the base station (BS) to communication users (CUs). The CE waveform and receive beamforming are jointly designed to maximize the signal to interference and noise ratio (SINR) of the radar under the security and system power constraints when the target location is imperfectly known. The optimal solution is obtained by the max-min fractional programming (FP) method. Specifically, the problem is designed to maximize the minimum SINR of the radar in the target location angular interval. Simulation results reveal the effectiveness and the hardware efficiency of the proposed algorithm

Radar and Communication Coexistence Enabled by Interference Exploitation

In this paper, we propose a novel approach for the spectrum sharing between Multi-Input-Multi-Output (MIMO) radar and downlink multi-user Multi-Input- Single-Output (MU-MISO) communication system. To obtain a power-efficient beamforming at the base station (BS), we utilize the constructive multi- user interference (MUI) as a source of green signal power. The proposed beamforming design mainly focuses on two optimization problems, i.e., transmit power minimization for BS and interference minimization for radar, subject to given performance requirements of the two systems. We further consider the impact of the proposed methods on radar, where the detection probability for MIMO radar in the presence of the interference from BS is analytically derived, and important trade-offs are revealed. Numerical results show that the proposed approach outperforms the conventional beamforming designs by achieving a significant performance gain under the discussed coexistence scenario

MIMO Radar and Cellular Coexistence: A Power-Efficient Approach Enabled by Interference Exploitation

We propose a novel approach to enable the coexistence between Multi-Input-Multi-Output (MIMO) radar and downlink multiuser multi-input single-output communication system. By exploiting the constructive multiuser interference (MUI), the proposed approach tradeoff 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 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 tradeoff 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. Numerical results show that the proposed method achieves a significant power saving compared to conventional approaches, while obtaining a favorable performance-complexity tradeoff