Multi-objective scheduling for MUD based ad-hoc networks

Common channel multi-hop Ad Hoc networks have some inherent constraints related to throughput and Quality of Service (QoS). Multiuser detection (MUD) based Medium Access Control (MAC) can relax some of these constraints and provide significant gains in throughput and Quality of Service (QoS). These gains can be realized by implementing a distributed neighborhood scheduling algorithm that needs to choose one from several possible transmission configurations in each frame. This feature allows formulating different scheduling performance objectives such as delay minimization or throughput maximization. In this paper we focus on analysis and comparison of the system performance under different objectives including multi-objective formulations. First we implement a scheduling scheme that minimize delay using Start Time Fair Queuing (STFQ) algorithm and compare its performance with scheduling that maximises the throughput. Then we formulate multi-objective functions that are used to achieve a trade-off between delay and throughput performance. One of these formulations is based on the Nash arbitration scheme from cooperative game theory. The numerical results demonstrate the flexibility and efficiency of the proposed approach.