Linear IC detectors for low to medium SNR ill-conditioned communication systems with unknown noise variance

Abdelouahab Bentrcia,Saleh A Alshebeili

doi:10.1186/1687-6180-2013-180

Abstract

In this paper, we introduce two new linear parallel interference cancellation (LPIC) detectors that are suitable for low to medium signal-to-noise ratio ill-conditioned communication systems and do not require knowledge of the noise variance but perform close to the linear minimum mean square error detector, which needs such information. Particularly, we focus in this work on fast linear parallel interference cancellation detectors that are asymptotically equivalent to the steepest descent and conjugate gradient algorithms, respectively, and show that they exhibit a spectral filtering property and semi-convergence behavior. Consequently, a deterministic stopping rule to stop the LPIC iterations that is independent of the noise level (known as the L-curve method) is investigated and tested. Simulation results are presented to support our theoretical findings.

Highlights

The capacity of the third-generation cellular systems and optical networks using optical CDMA (OCDMA) technology is mainly limited by the multi-access interference (MAI) [1]
Other systems suffer from other types of interference such as the inter-carrier interference (ICI) in orthogonal frequency division multiple access (OFDMA) and inter-antenna interference (IAI) in multiinput multioutput (MIMO) systems, just to name a few [1]
Simulation results In the following, we evaluate the performance of the linear parallel interference cancellation (LPIC) detector equipped with the L-curve stopping rule and based on the residual norm steepest descent and conjugate gradient least squares, respectively

Summary

Introduction

The capacity of the third-generation cellular systems and optical networks using optical CDMA (OCDMA) technology is mainly limited by the multi-access interference (MAI) [1]. We employ fast linear interference cancellation detectors to reduce its computational complexity, and we make use of an early stopping technique (known as the L-curve method) that does not require noise level information to reduce the noise enhancement effect [9]. In order to implement the above stopping rule, we have to evaluate the norm of the residual error for each OFDM symbol a certain number of stages till the Lshaped curve is obtained and calculate the curvature information to determine the optimal stopping stage This is too expensive in practice and another alternative should be sought. The resulting exponentially fitted curve is used instead in computing the maximum curvature and the optimal stage index This method proved to be efficient in combating the erratic behavior of the residual error norm of the LPIC detector based on the CGLS. More insight about this issue is given in the simulation results

Computational complexity

Conclusion