Abstract
We propose a one-shot (non-iterative) cooperative beamforming scheme for downlink multicell systems. Unlike previous non-iterative beamforming schemes, the proposed cooperative beamforming strives to balance maximizing the desired signal power while minimizing the generated interference power to neighbors by maximizing the network-wide average sum rate. Based on the average sum rate analysis, we derive what we term a “global selfishness” that steers the egoistic-altruistic balance of the network to maximize average sum rate. The global selfishness enables an autonomous decision on the cooperative beamforming vector in each cell. The main advantage of our approach is that cooperative beamforming solutions are analytically derived not only for an ideal two-cell network scenario but also for a practical three-sectored cellular network scenario. The simulation results verify that the proposed one-shot cooperative beamforming outperforms other conventional non-iterative schemes especially in interference-limited regions, which implies that it is very effective for performance improvement of edge users.
Highlights
Intercell interference (ICI) has been one of the most dominating factors that limits the performance of cellular systems
The main advantage of our approach is that we can derive the cooperative beamforming vectors for a practical three-sectored cellular network scenario as well as an ideal two-cell network scenario, which can be achieved in proposed one-shot beamforming approaches without high signal-to-interference-plus-noise ratio (SINR) assumption unlike the conventional non-iterative beamforming approaches
5.1 Ideal two-cell network scenario We describe how to determine the optimal value of global selfishness for an ideal two-cell network scenario
Summary
Intercell interference (ICI) has been one of the most dominating factors that limits the performance of cellular systems. In an ideal two-cell network scenario, the SGINR-based cooperative beamforming has been shown to achieve near optimal performance that maximizes the network-wide sum rate. The main advantage of our approach is that we can derive the cooperative beamforming vectors for a practical three-sectored cellular network scenario as well as an ideal two-cell network scenario, which can be achieved in proposed one-shot beamforming approaches without high SINR assumption unlike the conventional non-iterative beamforming approaches. Based on the closed-form expression, we determine the optimal value of global selfishness that maximizes network-wide sum rate. Considering that previous non-iterative beamforming schemes aim to maximize alternate performance metric, e.g., virtual SINR, our approach directly tackles network-wide sum rate. In a scenario where there exists two BSs and two MSs, the virtual SINR maximizing beamforming scheme has been shown to achieve near optimal performance in terms of network-wide sum rate. The proposed scheme requires only a single computation of precoding vector, the conventional iterative beamforming schemes in [7–12, 14] require dozens of computations for precoding vectors, for example, the iterative scheme in [7] requires about 30 repeats of precoding vector computations
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