Joint scheduling and dynamic power spectrum optimization for wireless multicell networks

This paper proposes a joint proportionally fair scheduling and dynamic power spectrum adaptation algorithm for wireless multicell networks. The proposed system allows multiple base-stations in a multicell network to be coordinated by exchanging interference pricing messages among each other. The messages summarize the effect of intercell interference, and they are functions of transmit power spectra, signal-to-noise ratios, direct and interfering channel gains, and the proportional fairness variables for each user. The use of interference pricing allows the transmit power spectra and user schedule within each base-station to be optimized jointly, while taking into consideration both the intercell interference and the fairness among the users in multiple cells. This paper proposes two power spectrum optimization methods, one based on the Karush-Kuhn-Tucker (KKT) condition of the optimization problem, and another based on the Newton's method. The proposed methods can achieve a throughput improvement of 40%-55% for users at the cell edge as compared to a conventional per-cell optimized system, while maintaining proportional fairness.