Joint opportunistic power and rate allocation for wireless ad hoc networks: An adaptive particle swarm optimization approach

In this paper, the joint opportunistic power and rate allocation (JOPRA) algorithm, which aims at maximizing the sum of source utilities while minimizing power allocation for all links in wireless ad hoc networks, is solved by means of an improved adaptive particle swarm optimization (IAPSO), which can overcome some limitations of the traditional dual and subgradient method. Compared with the original APSO, in our IAPSO, the maximum movement velocity of the particles changes dynamically, a modified replacement procedure with no introduced additional parameters is employed in constraint handling, and the state of the optimization run and the diversity in the population are taken into account in stopping criteria. It is shown that the proposed JOPRA algorithm can fast converge to the optimum and reach larger total data rate and utility while less total power is consumed. The efficiency of our approach is further illustrated via numerical comparison with the original APSO. This work is a beneficial attempt to integrate adaptive evolutionary algorithms with the resource allocation in wireless ad hoc networks.