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.

Asymmetrical mimo wireless communications

Abstract: A method for asymmetrical MIMO wireless communication begins by determining a number of transmission antennas for the asymmetrical MIMO wireless communication. The method continues by determining a number of reception antennas for the asymmetrical MIMO wireless communication. The method continues by, when the number of transmission antennas exceeds the number of reception antennas, using spatial time block coding for the asymmetrical MIMO wireless communication. The method continues by, when the number of transmission antennas does not exceed the number of reception antennas, using spatial multiplexing for the asymmetrical MIMO wireless communication.

Finite-Alphabet Precoding for Massive MU-MIMO With Low-Resolution DACs

Abstract: Massive multiuser multiple-input multiple-output (MU-MIMO) systems are expected to be the core technology in fifth-generation wireless systems because they significantly improve spectral efficiency. However, the requirement for a large number of radio frequency (RF) chains results in high hardware costs and power consumption, which obstruct the commercial deployment of massive MIMO systems. A potential solution is to use low-resolution digital-to-analog converters (DAC)/analog-to-digital converters for each antenna and RF chain. However, using low-resolution DACs at the transmit side directly limits the degree of freedom of output signals and thus poses a challenge to the precoding design. In this paper, we develop efficient and universal algorithms for a downlink massive MU-MIMO system with finite-alphabet precodings. Our algorithms are developed based on the alternating direction method of multipliers (ADMM) framework. The original ADMM does not converge in a nonlinear discrete optimization problem. The primary cause of this problem is that the alternating (update) directions in ADMM on one side are biased, and those on the other side are unbiased. By making the two updates consistent in an unbiased manner, we develop two algorithms called iterative discrete estimation (IDE) and IDE2. IDE demonstrates excellent performance and IDE2 possesses a significantly low computational complexity. Compared with state-of-the-art techniques, the proposed precoding algorithms present significant advantages in performance and computational complexity.

Method and network device for enabling mimo station and siso station to coexist in wireless network without data collision

Abstract: Provided are a method of enabling a multi-input multi-output (MIMO) station and a single input single output (SISO) station to coexist in a wireless network and a wireless network device. The method includes receiving information on a station when the station accesses a wireless network, setting coexistence information by comparing a number of antennas of the station accessing the wireless network with a number of antennas of a plurality of stations constituting the wireless network, and transmitting a frame containing the coexistence information to the plurality of stations constituting the wireless network.

Mode and user selection for multi-user MIMO WLANs without CSI

Abstract: A Multi-User MIMO (MU-MIMO) Access Point (AP) can obtain a capacity gain by simultaneously transmitting to multiple clients. This technique requires Channel State Information (CSI) at the transmitting AP to set antenna gains and phases to enable simultaneous reception through beamforming. The AP must also select both the mode (number of transmit and collective receive antennas) and the user set prior to transmission. While the ideal mode and user selection is a function of CSI, CSI must be estimated with an overhead intensive channel sounding process. We design, implement, and evaluate Pre-sounding User and Mode selection Algorithm (PUMA), a method for mode and user selection prior to channel sounding. We show that even without CSI, PUMA (i) exploits theoretical properties of MU-MIMO system scaling with respect to mode, (ii) characterizes the relative cost of each potential mode, and (iii) estimates per-stream transmission rate and aggregate throughput in each mode for a potential user set, all without CSI. Once PUMA has selected the appropriate mode and user group, the chosen protocol's channel sounding method is used on the intended user subset to carry out the transmission. We show that, on average, PUMA selects the mode and group that achieves an aggregate rate within 3% of the saturation throughput of what would have been achieved by sounding all users (which would require significant additional overhead). Moreover, we show that PUMA obtains 30% higher aggregate throughput compared to the best fixed-mode policy that uses the maximum number of available transmit and receive antennas.

Energy efficient virtual MIMO communication for wireless sensor networks

Abstract: Virtual multiple input multiple output (MIMO) techniques are used for energy efficient communication in wireless sensor networks. In this paper, we propose energy efficient routing based on virtual MIMO. We investigate virtual MIMO for both fixed and variable rates. We use a cluster based virtual MIMO cognitive model with the aim of changing operational parameters (constellation size) to provide energy efficient communication. We determine the routing path based on the virtual MIMO communication cost to delay the first node death. For larger distances, the simulation results show that virtual MIMO (2×2) based routing is more energy efficient than SISO (single input single output) and other MIMO variations.