Hard/Soft detection with limited CSI for multi-hop systems
IEEE Transactions on Wireless Communications
Distributed multicell-MISO precoding using the layered virtual SINR framework
IEEE Transactions on Wireless Communications
Utilizing the Spatial Information Provided by Channel Norm Feedback in SDMA Systems
IEEE Transactions on Signal Processing - Part II
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
Exact symbol error probability of a Cooperative network in a Rayleigh-fading environment
IEEE Transactions on Wireless Communications
A performance study of dual-hop transmissions with fixed gain relays
IEEE Transactions on Wireless Communications
Symbol error probabilities for general Cooperative links
IEEE Transactions on Wireless Communications
Distributed Downlink Beamforming With Cooperative Base Stations
IEEE Transactions on Information Theory
Multiple-input-multiple-output measurements and modeling in Manhattan
IEEE Journal on Selected Areas in Communications
Competition Versus Cooperation on the MISO Interference Channel
IEEE Journal on Selected Areas in Communications
IEEE Transactions on Signal Processing
| Hi-index | 0.00 |
This paper considers downlink multiantenna communication with base stations that perform cooperative precoding in a distributed fashion. Most previous work in the area has assumed that transmitters have common knowledge of both data symbols of all users and full or partial channel state information (CSI). Herein, we assume that each base station only has local CSI, either instantaneous or statistical. For the case of instantaneous CSI, a parametrization of the beamforming vectors used to achieve the outer boundary of the achievable rate region is obtained for two multi-antenna transmitters and two single-antenna receivers. Distributed generalizations of classical beamforming approaches that satisfy this parametrization are provided, and it is shown how the distributed precoding design can be improved using the so-called virtual SINR framework [1]. Conceptually analog results for both the parametrization and the beamforming design are derived in the case of local statistical CSI. Heuristics on the distributed power allocation are provided in both cases, and the performance is illustrated numerically.