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.

Media-based modulation: A new approach to wireless transmission

Abstract: It is shown that embedding part or all of the information in the (intentional) variations of the transmission media (end-to-end channel) can offer significant performance gains vs. traditional SISO, SIMO and MIMO systems, at the same time with a lower complexity. This is in contrast with the traditional wireless systems where the information is entirely embedded in the variations of an RF source prior to the antenna to propagate via the channel to the destination. In particular, it is shown that using a single transmit antenna and D receive antennas; significant savings in energy with respect to a D×D traditional MIMO are achieved. Similar energy savings are possible in SISO, and SIMO setups.

PAR-Aware Large-Scale Multi-User MIMO-OFDM Downlink

Abstract: We investigate an orthogonal frequency-division multiplexing (OFDM)-based downlink transmission scheme for large-scale multi-user (MU) multiple-input multiple-output (MIMO) wireless systems. The use of OFDM causes a high peak-to-average (power) ratio (PAR), which necessitates expensive and power-inefficient radio-frequency (RF) components at the base station. In this paper, we present a novel downlink transmission scheme, which exploits the massive degrees-of-freedom available in large-scale MU-MIMO-OFDM systems to achieve low PAR. Specifically, we propose to jointly perform MU precoding, OFDM modulation, and PAR reduction by solving a convex optimization problem. We develop a corresponding fast iterative truncation algorithm (FITRA) and show numerical results to demonstrate tremendous PAR-reduction capabilities. The significantly reduced linearity requirements eventually enable the use of low-cost RF components for the large-scale MU-MIMO-OFDM downlink.

Coherent optical MIMO (COMIMO)

Abstract: We present a multiple-input multiple-output (MIMO) optical link based on coherent optics and its ability to exploit the inherent information capacity of multimode fiber. A coherent implementation differs from previous work in optical MIMO by allowing the system to tolerate smaller modal delay spreads, because of a much larger carrier frequency, and yet maintain the necessary diversity needed for MIMO operation. Furthermore, we demonstrate the use of MIMO adaptive equalization to mitigate intersymbol interference when exceeding the bandwidth-length product of the link. The impact of phase noise is studied with numerical simulation.

Energy-Efficient Uplink Multi-User MIMO

Abstract: This paper addresses optimal energy-efficient design for uplink (UL) MU-MIMO in a single cell environment. The energy efficiency is measured by throughput per Joule, while both RF transmission power and device electronic circuit power are considered. We define the energy efficiency (EE) capacity for UL MU-MIMO and study the power allocation that achieves this capacity. First we assume all users consume a fixed amount of circuit power and show that user antennas should be used only when the corresponding spatial channels are sufficiently good and using them improves the overall network EE. Mobile devices may have improved circuit management capability and turn off circuit operations when some antennas are not used to reduce circuit power consumption. Therefore we further study energy-efficient UL MU-MIMO with improved circuit management and show that some antennas should not be used even when their channel states are good because turning them on consumes too much circuit power. Based on theoretical analysis, we further develop low-complexity yet globally optimal energy-efficient power allocation algorithms that converge to the optimum exponentially. Simulation results are provided to demonstrate the significant gain in network energy efficiency.

Efficient Coordinated Recovery of Sparse Channels in Massive MIMO

Abstract: This paper addresses the problem of estimating sparse channels in massive MIMO-OFDM systems. Most wireless channels are sparse in nature with large delay spread. In addition, these channels as observed by multiple antennas in a neighborhood have approximately common support. The sparsity and common support properties are attractive when it comes to the efficient estimation of large number of channels in massive MIMO systems. Moreover, to avoid pilot contamination and to achieve better spectral efficiency, it is important to use a small number of pilots. We present a novel channel estimation approach which utilizes the sparsity and common support properties to estimate sparse channels and requires a small number of pilots. Two algorithms based on this approach have been developed that perform Bayesian estimates of sparse channels even when the prior is non-Gaussian or unknown. Neighboring antennas share among each other their beliefs about the locations of active channel taps to perform estimation. The coordinated approach improves channel estimates and also reduces the required number of pilots. Further improvement is achieved by the data-aided version of the algorithm. Extensive simulation results are provided to demonstrate the performance of the proposed algorithms.