A Dual-Functional Massive MIMO OFDM Communication and Radar Transmitter Architecture

In this study, a dual-functional radar and communication (RadCom) system architecture is proposed for application at base-stations (BSs), or access points (APs), for simultaneously communicating with multiple user equipments (UEs) and sensing the environment. Specifically, massive multiple-input multiple-output (mMIMO) communication and orthogonal frequency-division multiplexing (OFDM)-based MIMO radar are considered with the objective to jointly utilize channel diversity and interference. The BS consists of a mMIMO antenna array, and radar transmit and receive antennas. Employing OFDM waveforms for the radar allows the BS to perform channel state information (CSI) estimation for the mMIMO and radar antennas simultaneously. The acquired CSI is then exploited to predict the radar signals received by the UEs. While the radar transmits an OFDM waveform for detecting possible targets in range, the communication system beamforms to the UEs by taking into account the predicted radar interference. To further enhance the capacity of the communication system, an optimum radar waveform is designed. Moreover, the network capacity is mathematically analyzed and verified by simulations. The results show that the proposed RadCom can achieve higher capacity than conventional mMIMO systems by utilizing the radar interference while simultaneously detecting targets.

I. Introduction

The relative success of current wireless networks has raised the expectations from next-generation networks (5G and beyond) such as supporting a massive number of devices, reducing latency or being able to detect targets present in the propagation environment. Meanwhile, radar systems and communication networks have been gradually converging in the frequency spectrum due to the increasing demands on bandwidth by various data hungry communication applications [1]. For example, autonomous driving applications require the vehicles to communicate with each other (vehicle-to-vehicle - V2V) and their surroundings (vehicle-to-everything - V2X), while sensing the road conditions to provide safer and better driving. Such applications require a substantial amount of bandwidth of an increasingly congested spectrum [2]. Therefore, this study presents a joint massive MIMO radar-communication (RadCom) platform, where the radar operates simultaneously with the communication downlink using the same time-frequency resources.