A novel uplink MIMO transmission scheme in a multicell environment

Abstract

Uplink multiple-input multiple-output (MIMO) transmission scheme is developed for time division duplex (TDD) systems in a multicell environment. We propose a precoding scheme that maximizes the total achievable rate and works in the decentralized manner with only locally available channel state information (CSI) at each transmitter. We first establish and solve a decentralized optimization problem for the case of multiple-input single-output (MISO) channels, introducing a new precoding design metric called signal to generated interference plus noise ratio (SGINR). By extending the result to general MIMO channels, we propose an SGINR-based precoding scheme where the number of transmit streams is selected adaptively to the surrounding environments. Simulation results confirm that the proposed precoding scheme offers significant throughput enhancement in multicell environments.Index Terms-Multicell, multiple-input multiple-output (MIMO), generated interference, precoding.

One-shot cooperative beamforming for downlink multicell systems

“…Note that the conventional approaches to non-iterative beamforming in [15][16][17][18][19][20] fail to provide analytic beamforming solution for M > 2 cases, without assuming high SINR, which is obviously not valid for cell edge regions. Moreover, the conventional approaches maximize sum of the V-SINR metric instead of sum rate metric and the gap between sum of V-SINR metric and sum rate metric becomes larger in general M > 2 cases.…”

“…For computationally efficient solutions, the approaches in [15][16][17][18][19][20] propose non-iterative beamforming schemes. To this end, instead of directly maximizing the sum rate, they aim to define a new metric that considers both desired signal power and generating interference power, maximizing the new metric.…”

“…To this end, instead of directly maximizing the sum rate, they aim to define a new metric that considers both desired signal power and generating interference power, maximizing the new metric. In [15] and [16], a new metric is defined as the desired signal power and the generated interference power to neighboring cells plus noise power ratio (SGINR). Then, the cooperative beamforming vector in each cell is individually determined to maximize the SGINR.…”

“…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. For general n-cell cases, the optimality of the SGINR-based cooperative beamforming has not been proved, but the main idea can be generalized by assuming high signal-to-interference-plus-noise ratio (SINR) at all links [16]. In [17][18][19], similar beamforming schemes have been proposed, which maximize virtual SINR.…”

“…The closed-form beamforming solution for K-user MISO interference channel has been derived with some assumptions while conventional virtual SINR beamforming solutions have been derived for a twouser scenario. Although the aforementioned non-iterative beamformings in [15][16][17][18][19][20] maximize SGINR or virtual SINR metric, it is not guaranteed that they can maximize the network-wide sum rate in practical cellular networks.…”