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A Decomposition-Based Low-Complexity Scheduling Scheme for Power Minimization under Delay Constraints in Time-Varying Uplink Channels

In this paper, we investigate the problem of minimizing the average transmission power of users while guaranteeing the average delay constraints in time-varying uplink channels. We design a scheduler that selects a user for transmission and determines the transmission rate of the selected user based on the channel and backlog information of the constituent users. Since it requires prohibitively high computation complexity to determine an optimal scheduler for multi-user systems, we propose a low-complexity scheduling scheme that can achieve near-optimal performance. In this scheme, we reduce the complexity by decomposing the multiuser problem into multiple individual user problems. We present the optimal solution to the user problem and then investigate the effects of the user selection algorithm on the performance for different channel models. The proposed user selection algorithm that utilizes both channel and backlog information turns out to be energy-efficient over wide range of delay requirement regardless of the channel model.