Multiuser Wireless Systems Research Articles

Greedy scheduling performance for a zero-forcing dirty-paper coded system

This letter presents two results for multiuser wireless systems employing dirty-paper coding strategies along with greedy scheduling over the broadcast multiple-input multiple-output channel. Specifically, an efficient and suboptimal downlink scheduler is proposed to approximate the maximum sum rate using equal power allocation, and it is shown to approach the maximum sum rate of optimal power allocation for a large number of users under optimal scheduling. The second result demonstrates that the average maximum sum rate can be tightly upper bounded when spatial multiplexing is maximized.

TPC-based STBC multiuser detection with LSE-RLS algorithm

The Bit Error Rate (BER) performance of a Turbo Product Code (TPC) based Space-Time Block Coding (STBC) multiuser wireless system in the frequency-selective channels has been investigated. Both of the good error correcting capability of TPC and the large diversity gain of STBC can be achieved simultaneously. A Least Square Error-Recursive Least Square (LSE-RLS) algorithm is applied to estimate the channel and cancel the interference. Simulations show that the proposed system can obtain about 2.7dB gain in E s /N 0 at the BER of 10−3.

A Covariance Shaping Framework for Linear Multiuser Detection

A new class of linear multiuser receivers, referred to as the covariance shaping multiuser (CSMU) receiver, is proposed, for suppression of interference in multiuser wireless communication systems. This class of receivers is based on the recently proposed covariance shaping least-squares estimator, and is designed to minimize the total variance of the weighted error between the receiver output and the observed signal, subject to the constraint that the covariance of the noise component in the receiver output is proportional to a given covariance matrix, so that we control the dynamic range and spectral shape of the output noise. Some of the well-known linear multiuser receivers are shown to be special cases of the CSMU receiver. This allows us to interpret these receivers as the receivers that minimize the total error variance in the observations, among all linear receivers with the same output noise covariance, and to analyze their performance in a unified way. We derive exact and approximate expressions for the probability of bit error, as well as the asymptotic signal-to-interference+noise ratio in the large system limit. We also characterize the spectral efficiency versus energy-per-information bit of the CSMU receiver in the wideband regime. Finally, we consider a special case of the CSMU receiver, equivalent to a mismatched minimum mean-squared error (MMSE) receiver, in which the channel signal-to-noise ratio (SNR) is not known precisely. Using our general performance analysis results, we characterize the performance of the mismatched MMSE receiver. We then treat the case in which the SNR is known to lie in a given uncertainty range, and develop a robust mismatched MMSE receiver whose performance is very close to that of the MMSE receiver over the entire uncertainty range.

The optimality of beamforming in uplink multiuser wireless systems

This paper considers the optimal uplink transmission strategy that achieves the sum-capacity in a multiuser multi-antenna wireless system. Assuming an independent identically distributed block-fading model with transmitter channel side information, beamforming for each remote user is shown to be necessary for achieving sum-capacity when there is a large number of users in the system. This result stands even in the case where each user is equipped with a large number of transmit antennas, and it can be readily extended to channels with intersymbol interference if an orthogonal frequency division multiplexing modulation is assumed. This result is obtained by deriving a rank bound on the transmit covariance matrices, and it suggests that all users should cooperate by each user using only a small portion of available dimensions. Based on the result, a suboptimal transmit scheme is proposed for the situation where only partial channel side information is available at each transmitter. Simulations show that the suboptimal scheme is not only able to achieve a sum rate very close to the capacity, but also insensitive to channel estimation error.

Optimum Infinite-Length MMSE Multi-User Decision-Feedback Space-TimeProcessing in Broadband Cellular Radio

We present an investigation of space-time receiver architectures in multi-user wireless systems where optimal idealized (infinite-length) space-time filtering is applied to minimize the mean-square error (MSE). Feedforward, decision-feedback and cross-decision feedback filters are employed; hence, the system eliminates the post-cursor ISI (intersymbol interference) and CCI (co-channel interference). While this is a form of MIMO-DFE (Multi-Input Multi-Output Decision-Feedback Equalization), no joint transmitter-receiver optimization is performed since the transmit sources are assumed to be individual users. Our analysis leads to an entirely novel closed-form expression for the minimum achievable MSE for any single user in both fully- and partially-connected cross-decision feedback systems (XDF). This differs from previous results on MIMO-DFE obtained in a CDMA context which rely on the Gaussian assumption. Numerical results compare the performance of XDF systems with standard space-time DF and linear processing as well as the MIMO matched-filter bound in both a generic Rayleigh-fading system context and a broadband wireless context with fixed, highly directional subscriber antennas and correlated fading based on a 3D channel model parameterized according to measurements at 29.5 GHz. Results indicate that generally, an N-element array with fully-connected XDF processing provides the same performance as an N+1-element array with standard linear space-time processing.

Quantum signal processing

In this article we present a signal processing framework that we refer to as quantum signal processing (QSP) (Eldar 2001) that is aimed at developing new or modifying existing signal processing algorithms by borrowing from the principles of quantum mechanics and some of its interesting axioms and constraints. However, in contrast to such fields as quantum computing and quantum information theory, it does not inherently depend on the physics associated with quantum mechanics. Consequently, in developing the QSP framework we are free to impose quantum mechanical constraints that we find useful and to avoid those that are not. This framework provides a unifying conceptual structure for a variety of traditional processing techniques and a precise mathematical setting for developing generalizations and extensions of algorithms, leading to a potentially useful paradigm for signal processing with applications in areas including frame theory, quantization and sampling methods, detection, parameter estimation, covariance shaping, and multiuser wireless communication systems. We present a general overview of the key elements in quantum physics that provide the basis for the QSP framework and an indication of the key results that have so far been developed within this framework. In the remainder of the article, we elaborate on the various elements in this figure.

Capacity and optimal resource allocation for fading broadcast channels .I. Ergodic capacity

In multiuser wireless systems, dynamic resource allocation between users and over time significantly improves efficiency and performance. In this two-part paper, we study three types of capacity regions for fading broadcast channels and obtain their corresponding optimal resource allocation strategies: the ergodic (Shannon) capacity region, the zero-outage capacity region, and the outage capacity region with nonzero outage. We derive the ergodic capacity region of an M-user fading broadcast channel for code division (CD), time division (TD), and frequency division (FD), assuming that both the transmitter and the receivers have perfect channel side information (CSI). It is shown that by allowing dynamic resource allocation, TD, FD, and CD without successive decoding have the same ergodic capacity region, while optimal CD has a larger region. Optimal resource allocation policies are obtained for these different spectrum-sharing techniques. A simple suboptimal policy is also proposed for TD and CD without successive decoding that results in a rate region quite close to the ergodic capacity region. Numerical results are provided for different fading broadcast channels.

Constrained power control

High system capacities can be achieved by controlling the transmitter power in multiuser radio systems. Power control with no constraint on the maximum power level has been studied extensively in earlier work [1–18]. Transmitter power is at a premium in radio systems such as cellular systems and PCS. There is a limit on the maximum transmitter power especially at the terminals (e.g. mobile units and handsets) since the power comes from a battery. In this paper we study power control that maximizes the minimum carrier to interference ratio (CIR), with a constraint on the maximum power. The optimal power vector solution lies on the boundary of the constrained power vector set and achieves a balance in the CIR's. Results indicate that the constraints do not induce any stability problems. A distributed scheme with favourable convergence properties and close to optimum performance is presented. Simulation results show that the algorithm tries to maximize the number of terminals served with CIR greater than or equal to the target CIR, while conserving power.