Matrix analysis
Convex Optimization
EURASIP Journal on Wireless Communications and Networking - Special issue on multiuser MIMO networks
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Coordinated beamforming for the multicell multi-antenna wireless system
IEEE Transactions on Wireless Communications
IEEE Transactions on Information Theory
Cooperative multi-cell block diagonalization with per-base-station power constraints
IEEE Journal on Selected Areas in Communications - Special issue on cooperative communications in MIMO cellular networks
Complete Characterization of the Pareto Boundary for the MISO Interference Channel
IEEE Transactions on Signal Processing - Part II
Network coordination for spectrally efficient communications in cellular systems
IEEE Wireless Communications
Sum Rate Characterization of Joint Multiple Cell-Site Processing
IEEE Transactions on Information Theory
Interference Alignment and Degrees of Freedom of the -User Interference Channel
IEEE Transactions on Information Theory
Gaussian Interference Channel Capacity to Within One Bit
IEEE Transactions on Information Theory
Cognitive radio: brain-empowered wireless communications
IEEE Journal on Selected Areas in Communications
Optimized transmission for fading multiple-access and broadcast channels with multiple antennas
IEEE Journal on Selected Areas in Communications
Multi-cell MIMO cooperative networks: a new look at interference
IEEE Journal on Selected Areas in Communications - Special issue on cooperative communications in MIMO cellular networks
Wireless Personal Communications: An International Journal
Hi-index | 35.68 |
In this correspondence, we study the downlink transmission in a multi-cell system, where multiple base stations (BSs) each with multiple antennas cooperatively design their respective transmit beamforming vectors to optimize the overall system performance. For simplicity, it is assumed that all mobile stations (MSs) are equipped with a single antenna each, and there is one active MS in each cell at one time. Accordingly, the system of interests can be modeled by a multiple-input single-output (MISO) Gaussian interference channel (IC), termed as MISO-IC, with interference treated as noise. We propose a new method to characterize different rate-tuples for active MSs on the Pareto boundary of the achievable rate region for the MISO-IC, by exploring the relationship between the MISO-IC and the cognitive radio (CR) MISO channel. We show that each Pareto-boundary rate-tuple of the MISO-IC can be achieved in a decentralized manner when each of the BSs attains its own channel capacity subject to a certain set of interference-power constraints (also known as interference-temperature constraints in the CR system) at the other MS receivers. Furthermore, we show that this result leads to a new decentralized algorithm for implementing the multi-cell cooperative downlink beamforming.