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Ad hoc networks are dynamic and scalable entities that autonomously adapt to nodes entering the network (i.e. increasing interference) or exiting the network (i.e. due to energy depletion), poor connectivity among others. In such networks, nodes exhibit individualistic behaviours where nodes selfishly compete for the limited network resources (i.e. energy and bandwidth) to maximize their own utilities. This consequently degrades network performance leading to low data rates, poor power efficiency, loss of connectivity etcetera. This paper considers a network utility maximization (NUM) strategy based on coupled interference minimization to adapt the transmission power and data rates in ad hoc networks. The proposed distributive joint power and rate adaptation (JRPA) algorithm employs costing (and reward) mechanisms to promote users' cooperation such that both users' local and network global optimum is always attained. This is similar to a super-modular game hence the optimality and convergence of JRPA is analysed using super-modular game theory. Simulation results show that the proposed algorithm improves network performance since users' are compels to transmit at optimal data rates and power levels just enough to sustain the transmission.

DISTRIBUTED JOINT POWER AND RATE ADAPTATION IN AD HOC NETWORKS