Joint communications and sensing design for multi-carrier MIMO systems

Abstract

With the emergence of ultra-reliable and low latency communication (URLLC) services, link adaptation (LA) plays a pivotal role in improving the robustness and reliability of communication networks via appropriate modulation and coding schemes (MCS). LA-based resource management schemes in both physical and medium access control layers can significantly enhance the system performance in terms of throughput, latency, reliability, and quality of service. Increasing the number of retransmissions will achieve higher reliability and increase transmission latency. In order to balance this trade-off with improved link performance for URLLC services, we study a joint subcarrier and power allocation problem to maximize the achievable sum-rate under an appropriate MCS. The formulated problem is mixed-integer nonconvex programming which is challenging to solve optimally. In addition, a direct application of standard optimization techniques is no longer applicable due to the complication of the effective signal-to-noise ratio (SNR) function. To overcome this challenge, we first relax the binary variables to continuous ones and introduce additional variables to convert the relaxed problem into a more tractable form. By leveraging the successive convex approximation method, we develop a low-complexity iterative algorithm that guarantees to achieve at least a locally optimal solution. Simulation results are provided to show the fast convergence of the proposed iterative algorithm and demonstrate the significant performance improvement in terms of the achievable sum-rate, compared with the conventional LA approach and existing retransmission policy.