Statistical Delay QoS Driven Energy Efficiency and Effective Capacity Tradeoff for Uplink Multi-User Multi-Carrier Systems

In this paper, the total system effective capacity (EC) maximization problem for the uplink transmission, in a multi-user multi-carrier OFDMA system, is formulated as a combinatorial integer programming problem, subject to each user?s link-layer energy efficiency (EE) requirement as well as the individual?s average transmission power limit. To solve this challenging problem, we first decouple it into a frequency provisioning problem and an independent multi-carrier linklayer EE-EC tradeoff problem for each user. In order to obtain the subcarrier assignment solution, a low-complexity heuristic algorithm is proposed, which not only offers close-to-optimal solutions, while serving as many users as possible, but also has a complexity linearly relating to the size of the problem. After obtaining the subcarrier assignment matrix, the multi-carrier link-layer EE-EC tradeoff problem for each user is formulated and solved by using Karush-Kuhn-Tucker (KKT) conditions. The per-user optimal power allocation strategy, which is across both frequency and time domains, is then derived. Further, we theoretically investigate the impact of the circuit power and the EE requirement factor on each user?s EE level and optimal average power value. The low-complexity heuristic algorithm is then simulated to compare with the traditional exhaustive algorithm and a fair-exhaustive algorithm. Simulation results confirm our proofs and design intentions, and further show the effects of delay quality-of-service (QoS) exponent, the total number of users and the number of subcarriers on the system tradeoff performance.