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

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... 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. some alternative approaches have been proposed in the literature [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] . The approaches in [6] [7] [8] [9] [10] [11] [12] [13] [14] are based on a well-known game theory. The characterizations of achievable rate region and existence of a unique Nash equilibrium have been provided in [6] . Cooperative beamforming vectors are determined by utilizing the two extreme solutions as the basis, i.e., egoistic beamforming and altruistic beamforming. A simple linear-type combination of egoistic beamforming and altruistic beamforming has been shown to achieve Pareto optimality in multiple-input single-output (MISO) systems [7] . The extension to a general K-user case has been derived in [8, 9] . For the case when the partial CSI is available at the transmitter, Pareto optimality of MISO system has been shown in [10] . The analysis based on competitive market, called Walrasian market, has been studied in [11] . The ICI links and beamforming vectors are considered consumers and goods, respectively. Then, the arbitrator coordinates the transmission strategies for achieving the Pareto optimal Walrasian equilibrium. In [12], a beamforming scheme that uses the generated interference level as a bargaining value has been proposed, where both of instantaneous and statistical CSI are considered. The non-strict Pareto boundary of two-user MIMO scenario has been