This paper addresses the problem of performing orthogonal space-division multiplexing (OSDM) for downlink, point-to-multipoint communications when multiple antennas are utilized at the base station (BS) and (optionally) all mobile stations (MS). Based on a closed-form antenna weight solution for single-user multiple-input multiple-output communications in the presence of other receiver points, we devise an iterative algorithm that finds the multiuser antenna weights for OSDM in downlink or broadcast channels. Upon convergence, each mobile user will receive only the desired activated spatial modes with no cochannel interference. Necessary and sufficient conditions for the existence of OSDM among the number of mobile users, the number of transmit antennas at the BS, and the number of receive antennas at the MS, are also derived. The assumption for the proposed method is that the BS knows the channels for all MS's and that the channel dynamics are quasi-stationary.
This paper addresses the joint robust power control and beamforming design of a linear multiuser multiple-input multiple-output (MIMO) antenna system in the downlink where users are subjected to individual signal-to-interference-plus-noise ratio (SINR) requirements, and the channel state information at the transmitter (CSIT) with its uncertainty characterized by an ellipsoidal region. The objective is to minimize the overall transmit power while guaranteeing the users' SINR constraints for every channel instantiation by designing the joint transmitreceive beamforming vectors robust to the channel uncertainty. This paper first investigates a multiuser MISO system (i.e., MIMO with single-antenna receivers) and by imposing the constraints on an SINR lower bound, a robust solution is obtained in a way similar to that with perfect CSI. We then present a reformulation of the robust optimization problem using S-Procedure which enables us to obtain the globally optimal robust power control with fixed transmit beamforming. Further, we propose to find the optimal robust MISO beamforming via convex optimization and rank relaxation. A convergent iterative algorithm is presented to extend the robust solution for multiuser MIMO systems with both perfect and imperfect channel state information at the receiver (CSIR) to guarantee the worst-case SINR. Simulation results illustrate that the proposed joint robust power and beamforming optimization significantly outperforms the optimal robust power allocation with zeroforcing (ZF) beamformers, and more importantly enlarges the feasibility regions of a multiuser MIMO system.
A subspace-based blind method is proposed for estimating the channel responses of a multiuser and multiantenna orthogonal frequency division multiplexing (OFDM) uplink system. It gives estimations to all channel responses subject to a scalar matrix ambiguity and does not need precise channel order information (only an upper bound for the orders is required). Furthermore, the scalar ambiguity matrix can be easily resolved by using only one pilot OFDM block, given that the number of users is smaller than the number of symbols in the pilot symbol block. Equalization methods are discussed based on the estimated channels. By using partial knowledge of the channels, a multipath subspace method is proposed that reduces the computational complexity. Simulations show that the methods are effective and robust.
In cognitive radio, it is crucial to control the interference from secondary users (SUs) to primary users (PUs). This paper studies the use of transmit beamforming in the cognitive secondary network for enhancing the performance of a SU while controlling the interference to the PUs. In particular, we propose to maximize the service probability of the SU with a number of probability constraints on the interference level at the PUs with the aid of imperfect channel state information (CSI). Modeling the CSI uncertainty as an additive Gaussian noise, it is shown that the optimum can be realized by second-order cone-programming (SOCP) in tandem with a one-dimensional search. Results reveal that the proposed approach provides a technique to tradeoff the performance between the PUs and the SU, making an analytical connection between non-robust and worst-case systems.
This letter proposes an analytical approach to evaluate the performance of MIMO-OFCDM systems [1] with multicode transmission. Assuming zero-forcing successive interference cancellation (ZF-SIC) in the space domain and MMSE detection in the frequency domain, it is shown that at each step of SIC, the error events on multiple code channels are correlated to each other, which make the performance evaluation difficult due to the involvement of a complicated multivariate probability. By approximating the multivariate probability by a series of two-variate probabilities, the proposed analytical approach takes the correlation into account and provides accurate performance estimations. The analytical results are verified by simulations and shown to be more accurate than those where no correlation is considered.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.