Downlink Optimization with Interference Pricing and Statistical CSI


In this paper, we propose a downlink transmission strategy based on intercell interference pricing and a distributed algorithm that enables each base station (BS) to design locally its own beamforming vectors without relying on downlink channel state information of links from other BSs to the users. This algorithm is the solution to an optimization problem that minimizes a linear combination of data transmission power and the resulting weighted intercell interference with pricing factors at each BS and maintains the required signal-to-interference-plus-noise ratios (SINR) at user terminals. We provide a convergence analysis for the proposed distributed algorithm and derive conditions for its existence. We characterize the impact of the pricing factors in expanding the operational range of SINR targets at user terminals in a power-efficient manner. Simulation results confirm that the proposed algorithm converges to a network-wide equilibrium point by balancing and stabilizing the intercell interference levels and assigning power optimal beamforming vectors to the BSs. The results also show the effectiveness of the proposed algorithm in closely following the performance limits of its centralized coordinated beamforming counterpart.


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