부산대학교 도서관

We propose an uplink rate splitting (RS) scheme for real-time health monitoring in the Internet of Medical Things (IoMT). To minimize total time cost, we jointly optimize biosensor grouping (BG), decoding order, power allocation, receiver beamforming, and computation resources allocation under the constraints of the transmit power and computation resources. This process results in a discrete nonconvex problem, which we decouple into three independent subproblems: 1) reduce co-channel interference to ease the transmit time cost. We solve this with a low-complexity BG algorithm; 2) optimize decoding order, power allocation, and receiver beamforming to reduce the forwarding time cost. We thus develop an alternating optimization algorithm. Specifically, we propose a decoding order update algorithm to optimize ordering, which can converge to the global optimum. We construct accurate surrogates via a quadratic transform approach and use surrogate optimization to attack other variables; and 3) allocate computation resources to minimize the processing time cost. Here, we derive the optimal solution with closed-form expressions. Simulation results indicate that the proposed overall scheme and algorithms present significant performance gains over several existing benchmarks.