Capacity maximizing power allocation for interfering wireless links: A distributed approach

Recent results show that sum-rate maximizing multicell power allocation promises significant gains in interference-limited data networks. Finding practical, Le. distributed, versions of this global optimization problem however remains a challenging task. In this work, we establish a general framework for the distributed power allocation problem for 1 mutually interfering links enabling us to derive a fully distributed power allocation algorithm. Although a gain for N = 2 is observed, a performance gap is still observed compared to a centralized algorithm. As a way to fill that gap, we propose minimal information (in this case 1 bit) message passing between interfering links to improve performance. Numerical results show these algorithms to exploit a substantial amount of the capacity gain offered by centralized optimization.