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 multipleoutput (mMIMO) communication and orthogonal frequencydivision 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 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.
This paper proposes a joint uplink massive multiple-input-multiple-output (MIMO) communication and orthogonal frequency-division multiplexing (OFDM) radar sensing architecture. Specifically, uplink communication and short-range radar sensing are considered, where the user equipments (UEs) transmit data to the base-station (BS), which simultaneously receives radar returns from the targets over the same subcarriers. Hence, the signals received at each BS antenna include radar returns and communication signals to be processed for extracting the sensing and communication data. The separation and detection of such signals are achieved by utilizing the channel diversity between the UEs and the targets. To this end, the UEs' signals are first detected and demodulated, and then subtracted from the received signal to acquire the radar returns. Symbol-based radar processing is then employed, as it provides substantial processing gains, and its detection performance is independent of the transmitted radar waveform. Furthermore, self-interference-due to the simultaneous operation of transmit and receive antennas-is taken into account. The communication capacity and normalized error of the radar-target channel estimation are mathematically analyzed, and the trade-off between the communication capacity and radar detection performance is demonstrated in terms of the power output of the communication and radar sub-systems, as well as the signal-to-noise ratio.
This paper considers the optimization of a dualfunctional radar and communication (RadCom) system with the objective is to maximize its sum-rate (SR) and energy-efficiency (EE) while satisfying certain radar target detection and data rate per user requirements. To this end, novel RadCom precoder schemes that can exploit downlink radar interference are devised for massive multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems. First, the communication capacity and radar detection performance metrics of these schemes are analytically evaluated. Then, using the derived results, optimum beam power allocation schemes are deduced to maximize SR and EE with modest computational complexity. The validity of the analytical results is confirmed via matching computer simulations. It is also shown that, compared to benchmark techniques, the devised precoders can achieve substantial improvements in terms of both SR and EE.
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