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 rate and normalized error of the radar-target channel estimation are mathematically analyzed, and the trade-off between the achievable rate and radar detection performance is demonstrated in terms of the output power of the communication and radar sub-systems and the signal-to-noise ratio.

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 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 considers the optimization of a dual-functional 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.

This paper studies joint device-to-device (D2D) group association and channel assignment in uplink multi-cell non-orthogonal multiple-access (NOMA) networks. Particularly, the goal is to assign D2D groups to cellular user channels at each base-station, while accounting for negative network externality due to the interference caused by pairing a user with a D2D group. To that end, a multi-objective signal-to-interference-plus-noise ratio (SINR)-maximizing power allocation solution procedure is proposed to determine the optimal power allocation for each (D2D group, user) pair, while meeting quality-of-service (QoS) requirements. After that, the joint D2D group association and channel assignment problem is modeled as a student-project allocation with preferences over (student, project) pairs matching problem. More specifically, two polynomial-time complexity stable matching algorithms are proposed to pair D2D groups with users, and associate them with base-stations. Simulation results are presented to evaluate the proposed matching algorithms when combined with the devised solution procedure, and compare them to a joint D2D group association, channel assignment and power allocation (J-GA-CA-PA) scheme. More importantly, the proposed algorithms are shown to efficiently yield comparable SINR—per user and D2D receiver—to the J-GA-CA-PA scheme, while maintaining QoS requirements.

Non-orthogonal multiple-access (NOMA) has recently been proposed to improve throughput and spectrum-efficiency of 5G cellular networks and beyond. It is also a key enabler for ultra-reliable and low-latency (URLL) communications. Moreover, the Internet-of-Things (IoT) paradigm has emerged to practically provide massive connectivity for smart devices and systems, which entails spectrum-and energy-efficient transmission schemes. To this aim, NOMA and energy-harvesting (EH) solutions have been put forth to address such demands, making the combination of such technologies inevitable in NOMA-based URLL-EH-IoT networks. On the other hand, random-access (RA) techniques are the key solution to enable massive URLL-EH-IoT networks, since they reduce signaling overhead, packet latency, and energy consumption when massive numbers of clustered IoT devices with sporadic traffic behavior are considered. In this paper, uplink RA-NOMA in URLL-EH-IoT networks with short packet and diversity transmissions is studied and analyzed. Network metrics—such as average packet latency, reliability, and GoodPut—are derived for the RA-NOMA scenario and compared with its RA-OMA counterpart to explore the advantages of RA-NOMA over RA-OMA. Moreover, the analytical derivations have been validated and shown to coincide with the simulation results. Furthermore, the effect of the transmission diversity and number of data bits per blocklength on the different network metrics are extensively evaluated. Lastly, the analytical derivations are utilized to find the optimum values of the IoT nodes’ transmit power, number of packet replicas, and number of transmitted data bits per blocklength, such that the maximum sum-GoodPut of a RA-NOMA IoT cluster is achieved, subject to URLL constraints.

Cellular network operators are actively expanding network coverage and capacity by deploying additional base-stations to provide mobile services to customers in rural areas. The increasing deployment of cellular base-stations has increased the power consumption, energy cost, and associated adverse environmental impact. This paper addresses the feasibility of using renewable energy sources to power off-grid rural 4G/5G cellular base-stations based on Kuwait’s solar irradiance and wind potentials. More importantly, a hybrid renewable energy system will be designed and modeled to meet realistic energy demands of remote base-stations and determine the optimum size of the hybrid system components. Particularly, the hybrid off-grid system may incorporate wind turbines (WTs), photovoltaic (PV) solar panels, converters, a battery bank (BB), and a back-up diesel generator (DG). Two remote cell-sites are considered, namely: (1) Jal-Alayah and (2) Wafra, where the Jal-Alayah cell-site is characterized with higher average wind speed (and wind potential), while the Wafra cell-site has higher average clearness index and solar irradiance. Various hybrid PV/wind electric system (HPWES) configurations are modeled and simulated via HOMER software, with the aim of determining the optimal configuration—in terms of net present cost (NPC)—in each cell-site. Specifically, the simulations have revealed that the WT-BB configuration is the most economical at the Jal-Alayah cell-site while requiring minimal land area and ensuring 100% renewable energy and zero CO${}_2$ emissions. This configuration is followed by the PV-DG-BB and PV-WT-DG-BB configurations, where the latter configuration incurs a marginal increase in the NPC than the former but with less land area. On the other hand, the PV-BB configuration is the most cost-effective in the Wafra cell-site; however, in the scenario of limited land area, then the PV-DG-BB configuration can be used but at the expense of slight increase in the NPC and CO${}_2$ emissions. This study confirms that utilizing renewable energy sources in two rural areas in Kuwait can be extremely effective in replacing conventional DG-powered base-stations, while minimizing the NPC and CO${}_2$ emissions.