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.

Outage Analysis of Wireless-Powered Relaying MIMO Systems with Non-Linear Energy Harvesters and Imperfect CSI

Abstract: In this paper, we investigate a wireless-powered dual-hop relaying multiple-input multiple-output system, which consists of a multi-antenna source (S) node, a multi-antenna destination (D) node, and $N (N>1)$ single-antenna wireless-powered relaying nodes. At each relay, a power splitting receiver is applied to process the received signal for information decoding and energy harvesting simultaneously, and a decode-and-forward scheme is adopted to forward the processed information. Furthermore, the energy harvester at each relay is assumed to be non-linear with a saturation threshold to limit the power level of the energy. Assuming imperfect channel state information is available both at S and D, outage performance is investigated when S adopts transmit antenna selection in the presence of feedback delay and D performs maximal ratio combining technique to deal with the multiple copies of signals with channel estimation errors. Taking into account a $K$ th best relay selection criterion, which results in the $K$ th best performance in terms of outage probability for the source-relay-destination link, an analytical expression for OP is derived. Monte Carlo simulation results are presented to verify the accuracy of the derived analytical model.

Energy-Efficient Resource Allocation for Wireless Powered Massive MIMO System With Imperfect CSI

Abstract: In this paper, we propose an energy-efficient resource allocation scheme for a wireless power transfer (WPT) enabled multi-user massive multiple-input multiple-output system with imperfect channel estimation. In the considered system, the users who have data to transmit in the uplink only can be empowered by the WPT in the downlink from a base station (BS) with large scale multiple antennas. The problem of optimizing the energy efficiency of the considered system is formulated with consideration of beamforming design, antenna selection, power allocation, and time division protocol based on the practical consideration, i.e., imperfect channel state information at the BS. In particular, the proposed antenna selection scheme is intended to find the optimal number of antennas and then employ the energy beamforming. Moreover, In order to find the optimal power and time allocation, a scheme based on nonlinear fractional programming is utilized. Extensive simulation studies are conducted to demonstrate the effectiveness of the proposed schemes and their superior performance over other existing schemes.

Time–Frequency Joint Sparse Channel Estimation for MIMO-OFDM Systems

Abstract: This letter proposes a time-frequency joint sparse channel estimation for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems under the framework of structured compressive sensing (CS). The proposed scheme first relies on a pseudorandom preamble, which is identical for all transmit antennas, to acquire the partial common support by utilizing the sparse common support property of the MIMO channels. Then, a very small amount of frequency-domain orthogonal pilots are used for the accurate channel recovery. Simulation results show that the proposed scheme demonstrates better performance and higher spectral efficiency than the conventional MIMO-OFDM schemes. Moreover, the obtained partial common support can be further utilized to reduce the complexity of the CS algorithm and improve the signal recovery probability under low signal-to-noise-ratio conditions.

An energy saving base station employing spatial modulation

Abstract: In this paper, we evaluate the energy efficiency of a multi-antenna Base Station (BS) employing Spatial Modulation (SM). Taking advantage of the single Radio Frequency (RF) chain configuration of SM, we show that SM offers a significant total power reduction compared to other multi-RF chain Multiple-Input Multiple-Output (MIMO) architectures. For the same RF transmit power, we demonstrate that the total power saving of SM scales linearly with the number of RF chains required by other MIMO schemes. Furthermore, we clarify that for the same ergodic capacity, SM has a significant advantage in energy efficiency compared to the studied multi-RF chain MIMO configurations. In addition, for a number of transmit antennas larger than two, we establish that SM results in higher ergodic capacity than Space-Time Block-Coding (STBC), combined with significant power saving. For a BS with 8 transmit antenna, the achieved power saving of SM can reach up to almost 90%. Finally, based on simulation results, we demonstrate that the energy efficiency (bits/J) of the studied MIMO schemes exhibits a maximum as function of ergodic capacity, and it is further shown that this maximum is several times higher in SM compared to the studied state-of-the-art MIMO schemes.

Optimality of beamforming in fading MIMO multiple access channels

Abstract: We consider the sum capacity of a multi-input multi-output (MIMO) multiple access channel (MAC) where the receiver has the perfect channel state information (CSI), while the transmitters have either no or partial CSI. When the transmitters have partial CSI, it is in the form of either the covariance matrix of the channel or the mean matrix of the channel. For the covariance feedback case, we mainly consider physical models that result in single-sided correlation structures. For the mean feedback case, we consider physical models that result in in-phase received signals. Under these assumptions, we analyze the MIMO-MAC from three different viewpoints. First, we consider a finite-sized system. We show that the optimum transmit directions of each user are the eigenvectors of its own channel covariance and mean feedback matrices, in the covariance and mean feedback models, respectively. Also, we find the conditions under which beamforming is optimal for all users. Second, in the covariance feedback case, we prove that the region where beamforming is optimal for all users gets larger with the addition of new users into the system. In the mean feedback case, we show through simulations that this is not necessarily true. Third, we consider the asymptotic case where the number of users is large. We show that in both no and partial CSI cases, beamforming is asymptotically optimal. In particular, in the case of no CSI, we show that a simple form of beamforming, which may be characterized as an arbitrary antenna selection scheme, achieves the sum capacity. In the case of partial CSI, we show that beamforming in the direction of the strongest eigenvector of the channel feedback matrix achieves the sum capacity. Finally, we generalize our covariance feedback results to double-sided correlation structures in the Appendix.