Multi-user MIMO

About: Multi-user MIMO is a research topic. Over the lifetime, 10265 publications have been published within this topic receiving 227206 citations. The topic is also known as: multi user mimo & MU-MIMO.

Method for transmitting and receiving signals using collaborative mimo scheme

Abstract: A method for reducing inter-cell interference and a method for transmitting a signal by a collaborative MIMO scheme, in a communication system having a multi-cell environment are disclosed. An example of a method for transmitting, by a mobile station, precoding information in a collaborative MIMO communication system includes determining a precoding matrix set including precoding matrices of one more base stations including a serving base station, based on signal strength of the serving base station, and transmitting information about the precoding matrix set to the serving base station. A mobile station in an edge of a cell performs a collaborative MIMO mode or inter-cell interference mitigation mode using the information about the precoding matrix set collaboratively with neighboring base stations.

Max-Min Fairness Linear Transceiver Design for a Multi-User MIMO Interference Channel

Abstract: Consider the max-min fairness linear transceiver design problem for a multi-user multi-input multi-output (MIMO) interference channel. When the channel knowledge is perfectly known, this problem can be formulated as the maximization of the minimum signal-to-interference-plus-noise ratio (SINR) utility, subject to individual power constraints at each transmitter. We prove in this paper that, if the number of antennas is at least two at each transmitter (receiver) and is at least three at each receiver (transmitter), the max-min fairness linear transceiver design problem is computationally intractable as the number of users becomes large. In fact, even the problem of checking the feasibility of a given set of target SINR levels is strongly NP-hard. We then propose two iterative algorithms to solve the max-min fairness linear transceiver design problem. The transceivers generated by these algorithms monotonically improve the min-rate utility and are guaranteed to converge to a stationary solution. The efficiency and performance of the proposed algorithms compare favorably with solutions obtained from the channel matched beamforming or the leakage interference minimization.

Compressed Sensing-Aided Downlink Channel Training for FDD Massive MIMO Systems

Abstract: There is much discussion in industry and academia about possible technical solutions to address the growth in demand for wireless broadband. Massive multiple-input multiple-output (MIMO) systems are one of the most popular solutions to addressing this broadband demand in fifth generation (5G) cellular systems. Massive MIMO systems employ tens or hundreds of antennas at the base station to enable advanced multiuser MIMO communications. To reap the massive MIMO throughput gain, coherent transmission exploiting accurate channel state information at the transmitter is required. While it is expected that many 5G systems will employ frequency division duplexing (FDD), channel sounding for FDD systems requires a large pilot overhead, which usually scales proportionally to the number of transmit antennas. To resolve this problem, a compressed sensing (CS)-aided channel estimation scheme is proposed, which exploits the observation that the channel statistics change slowly in time. By utilizing a conventional least squares approach and a CS technique simultaneously, the proposed scheme reduces the pilot overhead. Simulation results show that the proposed scheme can estimate the channel with a reduced pilot overhead even when conventional CS cannot be applied.

Capacity enhancement in coherent optical MIMO (COMIMO) multimode fiber links

Abstract: In this paper, we study a coherent optical MIMO (COMIEMO) multi-mode fiber link proposed for enhancing the fiber information capacity. We examine the statistical characterization of the equivalent MIMO channel and the improvement in the fiber capacity due to MIMO transmission. It is shown that the equivalent channel behaves similarly to a complex Gaussian MIMO channel, suggesting that the available results on wireless MIMO communication systems can be applied to optical fiber links for capacity enhancement.

Massive MIMO Wireless Networks: An Overview

Abstract: Massive multiple-input-multiple-output (MIMO) systems use few hundred antennas to simultaneously serve large number of wireless broadband terminals. It has been incorporated into standards like long term evolution (LTE) and IEEE802.11 (Wi-Fi). Basically, the more the antennas, the better shall be the performance. Massive MIMO systems envision accurate beamforming and decoding with simpler and possibly linear algorithms. However, efficient signal processing techniques have to be used at both ends to overcome the signaling overhead complexity. There are few fundamental issues about massive MIMO networks that need to be better understood before their successful deployment. In this paper, we present a detailed review of massive MIMO homogeneous, and heterogeneous systems, highlighting key system components, pros, cons, and research directions. In addition, we emphasize the advantage of employing millimeter wave (mmWave) frequency in the beamforming, and precoding operations in single, and multi-tier massive MIMO systems.