Issues and Approaches

In wireless channels, Non-Gaussian noise is one of the most common noise models that is observed. This type of noise has a severe impact on wireless systems with linear and multiuser detection devices. In this paper, We study the performance of zero forcing (ZF) and minimum mean square error (MMSE) ZF detection methods in Impulsive multi-cell MIMO channels. We start by showing the Bit Error Rate performance in non-Gaussian channels for ZF Detection, then we extend the derivations for MMSE ZF system. We clearly show the lower and upper bound derivations and verify it through simulations. The sum rate analysis for this case is also examined. Finally, we address the ZF matrix inversion complexity problem, and propose a simple ZF algorithm that does not necessitate the matrix inversion. We then investigate the convergence of such a detector and look at the Symbol Error rate SER performance through simulation again.

Error Rate Analysis of ZF and MMSE Decoders for Massive Multi Cell MIMO Systems in Impulsive Noise Channels

In this paper, we examine the performance of zero forcing (ZF) and minimum mean square error (MMSE) ZF linear detection methods in non-Gaussian impulsive and Laplacian multi-cell MIMO channels. We start by showing the symbol error rate performance in non-Gaussian channels for ZF detection, and then we build over it and extend to the derivations for MMSE ZF system. The lower and upper bound derivations are clearly shown and verified through computer software Montecarlo simulations.

Performance of ZF and MMSE decoders for massive multi-cell MIMO systems in impulsive and Laplacian noise channels

This paper introduces three basic structures about digital radio frequency memory(DRFM) and analyses noise encoded which is one of important index of the DRFM,comparing these structures according to the spectral impurities of the output spectrum

Architectures and performance analysis of DRFM

Cellular operators are moving towards deployment of heterogeneous cellular networks (HetCNs) not just to deliver services to remote locations but also to spread out data capacity in crowded urban areas. HetCNs, along with traditional macro towers may also include relays, smaller base station and distributed antennas. These new infra with small base stations and cells (e.g., metrocells, microcells, picocells, and femtocells) have advantages such as smartness, cheap, less obstructive, and easier installation compared to traditional homogeneous macrocell networks. Traditional single towers along with these small cells can provide services not only to outside busy intersections but also to residential homes and offices. This paper addresses some of the major concerns of today’s cellular system such as coverage, capacity, interference and spectrum reuse. The paper also presents and discusses advantages and future needs of denser deployment of base stations and cells in a heterogeneous cellular network. Literature survey on some of the recent research works associated with spectrum allocation and interference management are presented. Major issues such as user association, off-loading of users from a macro to small cells etc, and potentials of superimposing small BSs with traditional macro cell BS are discussed.

/pdf/traditional-macro-tower-to-heterogeneous-cellular-networks-a-16kyh9bs3l.pdf

Traditional Macro-tower to Heterogeneous Cellular Networks: A Survey

The heterogeneous network, contains a macro cell and a grid of low power nodes with the same frequencies, can improve the system capacity and spectrum efficiency. Configuring low-power nodes that share the same spectrum with macro cell to form heterogeneous networks makes it more likely to improve the system capacity and spectrum efficiency, but inevitably, strong co-channel interference is the main barrier to further improvement for heterogeneous networks. This paper proposes an algorithm which combines the triangular decomposition and signal to leakage and noise ratio (SLNR) (TD-SLNR) to suppress strong co-channel interference in multi-cell multiple input and multiple output (MIMO) heterogeneous networks. Firstly, the proposed algorithm can reduce the number of inter-cell interferences in half. As a result of triangular decomposition, an equivalent interference channel model is extracted to eliminate the rest of interferences using SLNR and interference suppression matrix. Theoretical analysis shows that the proposed algorithm provides a potential solution to suppress the co-channel interference with low complexity and reduce the computation complexity without adding extra interference suppression matrices and computation complexity at receivers. Furthermore, the simulation results show that TD-SLNR algorithm can improve system capacity and energy efficiency comparing with the traditional SLNR algorithm.

/pdf/co-channel-interference-suppression-for-multi-cell-mimo-3w5xzdmbal.pdf

Zufan Zhang

Papers

Co-channel interference suppression for multi-cell MIMO heterogeneous network