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In downlink multiuser multiple-input–multiple-output (MU-MIMO) systems, users are practically heterogeneous. However, many existing user-scheduling algorithms are designed with an implicit assumption that users are homogeneous. In this paper, we revisit the problem by exploring the characteristics of heterogeneous users from a subspace viewpoint. With an objective of minimizing interference nonorthogonality among users, three new angular-based user-scheduling criteria are proposed. While the first criterion is heuristically determined by identifying the incapability of the largest principal angle to characterize subspace correlation and, hence, interference nonorthogonality between users, the second and third criteria are derived by using the sum rate capacity bounds with block diagonalization and the change in capacity by adding a new user into an existing user subset, respectively. Aiming to capture fairness among heterogeneous users while maintaining multiuser diversity gain, two new hybrid user-scheduling algorithms, whose computational complexities are only linearly proportional to the number of users, are proposed. We show by simulations the effectiveness of our proposed user-scheduling criteria and algorithms with respect to those commonly used in a homogeneous environment. [ABSTRACT FROM PUBLISHER]

In this paper, we first study the design of network coding for the generalized multiple-input–multiple-output (MIMO) Y channels, where K users wish to exchange information with each other within two time slots. Precoding at each user and the relay is carefully constructed to ensure that the signals from the same user pair are grouped together and that cross-pair interference can be canceled. In addition, a simple mapping function is proposed to ensure low-complexity detection at the relay. Exact expressions of symbol error rate (SER) are then developed to establish the explicit relationship between the diversity gain and the number of node antennas. Monte Carlo simulation is also provided to demonstrate the performance of the proposed scheme. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate a novel relaying technique employing scheduling, precoding, beamforming, and power allocation for a multiuser multiple-input–multiple-output (MU-MIMO) relay network. In the proposed scheme, the interference is canceled by using a combination of transmit–receive weights and Tomlinson–Harashima precoding (THP). To achieve data rate fairness among different users and further improve the performance of MU-MIMO relay networks, we propose a low-complexity power allocation (LC-PA) to allocate power to each user. In addition, an algorithm to select a subset of users that has maximum sum rate performance is proposed. The performance of the proposed scheme is investigated by examining the sum rate of the system for different user selection algorithms and different power allocation schemes. [ABSTRACT FROM PUBLISHER]

This paper investigates the performance of multihop virtual multiple-input–multiple-output systems (V-MIMO), based on the concept of virtual antenna array (VAA), in the presence of random location of nodes. Nodes are supposed to be distributed according to a Poisson point process. Random fluctuations are considered, and the channel model takes both slow and fast fading into account. Performance is evaluated in terms of outage probability, which is defined as the probability that the ergodic capacity between the source and the destination is smaller than a given threshold. We investigate the impact of a random distribution of nodes on the overall performance. The role played by the interference, when some reuse of radio resources is considered for inter-VAA communication, is also investigated. [ABSTRACT FROM PUBLISHER]

This paper analyzes the average bit error rate (BER) of multiple-input–multiple-output (MIMO) systems in transmit-correlated Rayleigh flat-fading channels. The receiver scheme is based on the minimum mean square error (MMSE) criterion, and the input may be precoded to optimize the communication. Accurate closed-form formulations for the average BER are derived. [ABSTRACT FROM PUBLISHER]

Multicell cooperative processing (MCP) has been recognized as a promising technique for increasing the spectral efficiency of future wireless systems. Unfortunately, the provided benefits of MCP come at the cost of increased radio feedback and backhaul overhead; for downlink transmission in frequency-division duplexing (FDD) systems, users need to feed back their channel-state information (CSI) to the MCP scheduler, and user data need to be exchanged between all cooperating base stations (BSs) through the backhaul network. In the context of conventional noncooperative networks, it has been suggested that radio feedback load could be reduced by preventing users with low-quality channels from feeding back their CSI (concept of selective feedback), at the cost of a small fraction of the multiuser diversity gain. In this paper, we investigate the translation of this selective feedback concept to MCP systems. According to this technique, users with weak interference links are prevented from feeding back their full CSI to the MCP scheduler. Although efficient, this technique alone cannot mitigate the backhaul overhead related to routing user data possibly to several BSs. To overcome this condition, we propose two schemes: one scheme based on Media Access Control (MAC)-layer scheduling and the other scheme based on physical-layer precoding. These schemes, combined with feedback load reduction, allow for a substantial mitigation of the MCP overheads related to feedback and backhaul load. We analyze the improvements in terms of both user-to-BS feedback reduction and backhaul load reduction, and we show that this framework results in a good tradeoff between performance and overhead for multicell cooperative networks. [ABSTRACT FROM PUBLISHER]

Channel estimation is critical to the performance of a multiple-input multiple-output and orthogonal frequency-division-multiplexing (MIMO-OFDM) communication system. Current MIMO-OFDM channel estimation techniques suffer from either high complexity or poor performance. In fact, this issue has become one of the bottlenecks of a practical MIMO-OFDM system. This paper solves the problem by introducing a new technique that has minimum complexity and yet provides superior channel tracking performance close to a minimum mean square error (MMSE) estimate over a wide range of channel selectivity and noise variance. The performance was evaluated via numerical simulations. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a practical downlink multiuser multiple-input–multiple-output (MU-MIMO) system. The proposed MU-MIMO system focuses on improving two limiting factors for practical implementations of MU-MIMO: 1) feedback rate and 2) computational complexity. First, users efficiently feed their channel-state information back with low feedback rate based on the proposed channel-quantization method. Second, the beamforming matrix at the base station is easily computed using singular value decomposition (SVD). Numerical results show that the proposed MU-MIMO system achieves a higher sum rate than conventional MU-MIMO systems, particularly at low feedback rate, while the computational complexity is kept reasonable. [ABSTRACT FROM PUBLISHER]

We consider the scenario in which multiple transmitters send signals to a receiver in the asynchronous multiple-input-multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) mode. A receiver structure that can perform joint synchronization and space-time equalization for the asynchronous MIMO-OFDM systems is proposed. We first introduce a novel space-time equalization algorithm based on the channel state information. This algorithm aims to null the cochannel interference and combat asynchronism, as well as minimize a lower bound to the symbol error rate in the asynchronous MIMO-OFDM system. In the second part of this paper, we propose a training-based minimizing mean-square-error (MMSE) algorithm to jointly obtain frequency offsets and equalization delays. We compensate for the effects of the frequency offsets and the propagation delays with these estimated parameters and then use the proposed direct training-based equalizer design algorithm to obtain the equalizer coefficients. The simulation section illustrates the desirable bit-error-rate (BER) performance of our proposed algorithms. [ABSTRACT FROM AUTHOR]

In this paper, a two stage hybrid interference cancellation and equalization framework is proposed for interference cancellation in the uplink of multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. The first stage uses time domain equalization to suppress cochannel interference, mitigate asynchronism, and shorten the postequalization channel response to be no longer than the length of the cyclic prefix. The second stage performs low-complexity single tap equalization and detection in the frequency domain. The framework is developed specifically for spatial multiplexing and is applied to multiuser MIMO-OFDM systems with asynchronism between users as well as to single-user MIMO-OFDM systems. Various equalizer design methods are proposed that determine the coefficients directly from the training data and are compared with methods based on channel estimates. The equalizer coefficients and postequalization channel response are found by solving a joint optimization that maximizes the signal to interference-plus-noise ratio (SINR) in the frequency domain. Simulations compare various training-based methods and show the proposed methods provide good bit error rate (BER) and SINR performance in a variety of interference scenarios. [ABSTRACT FROM AUTHOR]