Autonomous Distributed Power Control Algorithms for Interference Mitigation in Multi-Antenna Cellular Networks

Interference mitigation has a great potential for improving the performance of current usually interference limited wireless networks. Since centralized "full" cooperation between base stations is still prohibitively complex, distributed schemes are of great interest. In this paper we compare three distributed algorithms for autonomous power control in 4G wireless networks and evaluate their applicability for different user mobility assumptions. The algorithms are based on network utility maximization, gradually and autonomously steering the network towards a higher utility. Besides different additional feedback and messaging requirements, the algorithms mainly differ in the granularity of power control, from controlling frequency subband power via controlling the power on a per-beam basis through to only enforcing average power constraints per beam. For comparison we use extensive system-level simulations indicating high gains compared to no power control. Moreover, it turns out that higher gains can be achieved by imposing average power constraints and allowing opportunistic scheduling instantaneously, rather than controlling the power in a strict way. Finally, we investigate the deviation from global optimality of the general framework by comparing to a Branch-And-Bound solution.