Age aware power allocation for energy-efficient wireless networks using RSMA

Abstract

With the commercial deployments of 5G, research in Beyond 5G (B5G) and 6G networks has started. Within the context of meeting all needs and demands of future generation networks, the predicted usage is envisaged in three cases: massive Machine-Type Communications (MTC), ultra-reliable low-latency communications, and enhanced mobile broadband. This thesis focuses on massive Machine-Type Communications (mMTC). Energy efficiency, under the banner of green communications and networking is one of the branches complementary to the research conducted on MTC. mMTC, industrial and medical Internet of Things (IoT) type technologies will demand not only networking capabilities for massive access, enhanced communications, but also sustainability and power efficiency. Rate Splitting Multiple Access (RSMA) presents a candidate massive access scheme with spectral efficiency, energy efficiency, reliability, Degree-of-Freedom (DoF) and Quality of Service (QoS) enhancements in most of user deployments and network loads over traditional access schemes used in 5G. Within the scope of the thesis, we propose an age-aware power allocation policy for minimizing the network’s Weighted-Sum Average AoI (WSAoI). To our knowledge, this is the first work in the literature which combines the Age of Information (AoI) concept and RSMA framework. For downlink communication, we formulate the network’s WSAoI minimization as a Markov Decision Process (MDP) and investigate an optimal as well as suboptimal policies for the Base Station (BS) to select a scheme among RSMA, Orthogonal Multiple Access (OMA), and Nonorthogonal Multiple Access (NOMA). We prove existence of an optimal policy. Complexity of computation is reduced by using an action elimination technique, and by using a sub-optimal policy with performance close to the optimal. We also investigate the tradeoff between energy and the WSAoI of the network. The adaptive RSMA only scheme outperforms adaptive RSMA/NOMA/OMA and OMA/NOMA on the basis of network’s WSAoI. For example, when RSMA is selected, the performance metric, WSAoI, at 14, 15, and 16 dB SNR values, is on average, respectively 35.8%, 15.7%, and 12.7% less than the NOMA/OMA cases. Overall, it is seen that, the optimum policy becomes more likely to operate in the RSMA mode with an increase in Signal to Noise Ratio (SNR). By using RSMA scheme instead of NOMA/OMA scheme, power consumption can be saved in average 65.8%, 62.3%, and 59.6% for the selected WSAoI values of 4, 3, and 2, respectively.