Multiple-input Multiple-output Singular Value Decomposition Research Articles

On the Achievable Performance of Nonlinear MIMO Systems

Pre-processing techniques employed at the transmitter side of multiple-input, multiple-output (MIMO) systems, such as the ones used by MIMO singular value decomposition (SVD) (MIMO-SVD) techniques, can lead to signals with large envelope fluctuations and high peak-to-average power ratio (PAPR). For this reason, we can have amplification difficulties and increased sensitivity to nonlinear distortion effects. In this letter, we consider MIMO-SVD schemes with strong nonlinear distortion effects. It is shown that contrarily to what one could expect, the asymptotic optimum performance of the MIMO system with strong nonlinear distortion effects can be much better than the optimum performance with an ideal, linear transmitter.

Robust energy-efficient power loading for MIMO system under imperfect CSI

In this paper, we will investigate the energy efficient power loading problem in multiple-input multiple-output singular value decomposition MIMO-SVD architecture. Most existing power loading schemes are developed on the assumption that a scheduler possesses perfect channel state information CSI. However, in practice, perfect CSI is not always available. In this paper, we propose an energy-efficient power loading scheme for MIMO system under imperfect CSI, taking into account the effects of channel estimation error CEE. Specifically, we propose two algorithms to maximise the system energy efficiency. One is a global method which can achieve the global optimal solution with high computational complexity; the other is a suboptimal method which can obtain the approximate optimal solution with lower computational complexity. Simulation results validate the effectiveness and robustness of our proposed power loading scheme.

Nakagami‐ m approximations for multiple‐input multiple‐output singular value decomposition transmissions

The multiple-input multiple-output singular value decomposition (MIMO SVD) modulation is an efficient way of sending data through a multi-antenna communications link in which the transmitter has knowledge of the channel state. Despite its importance, no simple formula for its symbol error rate (SER) has been found, and hence no intuitive characterisation of the quality of this technique for data transmission is available at the present. In this study, the authors present a method for approximating the statistics of each eigenchannel of MIMO SVD using the Nakagami- m fading model. Using the proposed method, it is seen that the SER of the entire MIMO SVD link can be approximated by the average of the SER of Nakagami- m channels. The expression found is simple and yet accurate. This leads to characterise the eigenchannels of N × N MIMO channels with N larger than 14, showing that the smallest eigenchannel distributes as a Rayleigh channel, the next four eigenchannels closely distributes as Nakagami- m channels with m = 4, 9, 25 and 36, and the N - 5 remaining eigenchannels have statistics similar to an additive white Gaussian noise (AWGN) channel within 1 dB signal-to-noise ratio. It is also shown that 75% of the total mean power gain of the MIMO SVD channel goes to the top third of all the eigenchannels.

Generalized Framework for the Analysis of Linear MIMO Transmission Schemes in Decentralized Wireless Ad Hoc Networks

We develop a general framework for the analysis of a broad class of point-to-point linear multiple-input multiple-output (MIMO) transmission schemes in decentralized wireless ad hoc networks. New general closed-form expressions are derived for the outage probability, throughput and transmission capacity. For the throughput, we investigate the optimal number of data streams in various asymptotic regimes, which is shown to be dependent on different network parameters. For the transmission capacity, we prove that it scales linearly with the number of antennas, provided that the number of data streams also scales linearly with the number of antennas, in addition to meeting some mild technical conditions. We also characterize the optimal number of data streams for maximizing the transmission capacity. To make our discussion concrete, we apply our general framework to investigate three popular MIMO schemes, each requiring different levels of feedback. In particular, we consider eigenmode selection with MIMO singular value decomposition, multiple transmit antenna selection, and open-loop spatial multiplexing. Our analysis of these schemes reveals that significant performance gains are achieved by utilizing feedback under a range of network conditions.

On Marginal Distributions of the Ordered Eigenvalues of Certain Random Matrices

This paper presents a general expression for the marginal distributions of the ordered eigenvalues of certain important random matrices. The expression, given in terms of matrix determinants, is compacter in representation and more efficient in computational complexity than existing results in the literature. As an illustrative application of the new result, we then analyze the performance of the multiple-input multiple-output singular value decomposition system. Analytical expressions for the average symbol error rate and the outage probability are derived, assuming the general double-scattering fading condition.

On the marginal distribution of the eigenvalues of wishart matrices

Random matrices play a crucial role in the design and analysis of multiple-input multiple-output (MIMO) systems. In particular, performance of MIMO systems depends on the statistical properties of a subclass of random matrices known as Wishart when the propagation environment is characterized by Rayleigh or Rician fading. This paper focuses on the stochastic analysis of this class of matrices and proposes a general methodology to evaluate some multiple nested integrals of interest. With this methodology we obtain a closed-form expression for the joint probability density function of k consecutive ordered eigenvalues and, as a special case, the PDF of the lscrth ordered eigenvalue of Wishart matrices. The distribution of the largest eigenvalue can be used to analyze the performance of MIMO maximal ratio combining systems. The PDF of the smallest eigenvalue can be used for MIMO antenna selection techniques. Finally, the PDF the kth largest eigenvalue finds applications in the performance analysis of MIMO singular value decomposition systems.

Performance analysis of multiple-input multiple-output singular value decomposition transceivers during fading and other cell interference

A generalised method is derived to compute the error probabilities of singular value decomposition (SVD)-based receivers for a multiple-input multiple-output (MIMO) system with uncoded transmission. The method can be used for a wide class of flat fading environments, including independent and identically distributed (i.i.d.) and semi-correlated Rayleigh and i.i.d. Ricean channels. Although the method is applied to equal-power binary phase shift keying, it can easily be extended to higher-order M-ary phase shift keying (M-PSK) and M-ary quadrature amplitude modulation (M-QAM) signal constellations and adaptive ‘water-filling’ schemes. The error probability curves derived from closed-form formulas and simulations demonstrate very close agreement. The error performances of channel inversion, minimum mean square error and zero forcing receivers are compared with the SVD receiver for a single-user system. The impact of multiple users is considered by studying the performance of an adaptive MIMO SVD transmission scheme operating in a cellular environment. In particular, the effect of inter-cell interference on the performance of the scheme is quantified, modelling the interference as increased Gaussian noise. A number of cellular layouts are examined and the impact of the resulting singal-to-interference and noise ratio on the constellation sizes that can be supported, the BER and so on is considered. The primary metric used for our performance analysis is the error-free transmission rate, which is derived for our adaptive system. For the cellular scenarios considered, it can be found that the effect of interference is considerable and the performance of the adaptive MIMO SVD scheme is only marginally better than that provided by conventional diversity methods.