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Journal ArticleDOI

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

24 Feb 2016-EURASIP Journal on Advances in Signal Processing (Springer International Publishing)-Vol. 2016, Iss: 1, pp 26
TL;DR: 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 is proposed.
Abstract: 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.

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Citations
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Book Chapter
01 Jan 2003

32 citations

Journal ArticleDOI
TL;DR: The performance of zero forcing and minimum mean square error (MMSE) ZF detection methods in Impulsive multi-cell MIMO channels is studied and a simple ZF algorithm is proposed that does not necessitate the matrix inversion.
Abstract: 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.

4 citations

Journal ArticleDOI
TL;DR: 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 is examined.
Abstract: 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.

3 citations

Proceedings Article
01 Jan 2006
TL;DR: 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.
Abstract: 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

1 citations

Journal ArticleDOI
TL;DR: The paper presents and discusses advantages and future needs of denser deployment of base stations and cells in a heterogeneous cellular network, and potentials of superimposing small BSs with traditional macro cell BS are discussed.
Abstract: 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.

1 citations


Cites background from "Co-channel interference suppression..."

  • ...In [21], co-channel interferences are analyzed for MIMO based multi-cell heterogeneous network and an algorithm is proposed which not only reduce the number of ICIs but also increase the system capacity....

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References
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Journal ArticleDOI
TL;DR: This paper proposes designing precoders by maximizing the so-called signal-to-leakage-and-noise ratio (SLNR) for all users simultaneously, and it also avoids noise enhancement.
Abstract: In multiuser MIMO downlink communications, it is necessary to design precoding schemes that are able to suppress co-channel interference. This paper proposes designing precoders by maximizing the so-called signal-to-leakage-and-noise ratio (SLNR) for all users simultaneously. The presentation considers communications with both single- and multi-stream cases, as well as MIMO systems that employ Alamouti coding. The effect of channel estimation errors on system performance is also studied. Compared with zero-forcing solutions, the proposed method does not impose a condition on the relation between the number of transmit and receive antennas, and it also avoids noise enhancement. Simulations illustrate the performance of the scheme

871 citations


"Co-channel interference suppression..." refers methods in this paper

  • ...Therefore, the signal to leakage and noise ratio (SLNR) algorithm proposed by Sadek is chosen to be the criterion of pre-coding design [27]....

    [...]

Book
05 Oct 2017
TL;DR: In this article, the authors present the theory, methods and applications of matrix analysis in a new theoretical framework, allowing readers to understand second-order and higher-order matrix analysis.
Abstract: This balanced and comprehensive study presents the theory, methods and applications of matrix analysis in a new theoretical framework, allowing readers to understand second-order and higher-order matrix analysis in a completely new light Alongside the core subjects in matrix analysis, such as singular value analysis, the solution of matrix equations and eigenanalysis, the author introduces new applications and perspectives that are unique to this book The very topical subjects of gradient analysis and optimization play a central role here Also included are subspace analysis, projection analysis and tensor analysis, subjects which are often neglected in other books Having provided a solid foundation to the subject, the author goes on to place particular emphasis on the many applications matrix analysis has in science and engineering, making this book suitable for scientists, engineers and graduate students alike

613 citations


"Co-channel interference suppression..." refers background in this paper

  • ...base stations and native users can be calculated [34]....

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Proceedings ArticleDOI
12 Apr 2010
TL;DR: To enhance the performance of heterogeneous networks, advanced techniques are described which are needed to manage and control interference and deliver the full benefits of such networks.
Abstract: Long-Term Evolution (LTE) allows operators to use new and wider spectrum and complements 3G networks with higher data rates, lower latency and a flat IP-based architecture. To further improve broadband user experience in a ubiquitous and cost effective manner, 3GPP has been working on various aspects in the framework of LTE Advanced. Since radio link performance is approaching theoretical limits with 3G enhancements and LTE, the next performance leap in wireless networks will come from the network topology. LTE Advanced is about improving spectral efficiency per unit area. Using a mix of macro, pico, femto and relay base-stations, heterogeneous networks enable flexible and low-cost deployments and provide a uniform broadband experience to users anywhere in the network. This paper discusses the need for an alternative deployment model or topology using heterogeneous networks. To enhance the performance of these networks, advanced techniques are described which are needed to manage and control interference and deliver the full benefits of such networks. Range extension allows more user terminals to benefit directly from low-power base-stations such as picos, femtos, and relays. Adaptive inter-cell interference coordination provides smart resource allocation amongst interfering cells and improves inter-cell fairness in a heterogeneous network. In addition, the performance gains with heterogeneous networks using an example macro/pico network are shown.

536 citations

Journal ArticleDOI
TL;DR: A survey of the different state-of-the-art approaches for interference and resource management in orthogonal frequency-division multiple access (OFDMA)-based femtocell networks and a qualitative comparison among the different approaches is provided.
Abstract: One of the effective techniques of improving the coverage and enhancing the capacity and data rate in cellular wireless networks is to reduce the cell size (i.e., cell splitting) and transmission distances. Therefore, the concept of deploying femtocells over macrocell has recently attracted growing interests in academia, industry, and standardization forums. Various technical challenges towards mass deployment of femtocells have been addressed in recent literature. Interference mitigation between neighboring femtocells and between the femtocell and macrocell is considered to be one of the major challenges in femtocell networks because femtocells share the same licensed frequency spectrum with macrocell. Further, the conventional radio resource management techniques for hierarchical cellular system is not suitable for femtocell networks since the positions of the femtocells are random depending on the users' service requirement. In this article, we provide a survey of the different state-of-the-art approaches for interference and resource management in orthogonal frequency-division multiple access (OFDMA)-based femtocell networks. A qualitative comparison among the different approaches is provided. To this end, open challenges in designing interference management schemes for OFDMA femtocell networks are discussed.

422 citations

Journal ArticleDOI
TL;DR: A generalized minimum mean-squared error (MMSE) channel inversion algorithm for users with multiple antennas to overcome the drawbacks of the BD for multiuser MIMO systems and shows that the proposed algorithm is robust to channel estimation errors.
Abstract: Block diagonalization (BD) is a well-known precoding method in multiuser multi-input multi-output (MIMO) broadcast channels. This scheme can be considered as a extension of the zero-forcing (ZF) channel inversion to the case where each receiver is equipped with multiple antennas. One of the limitation of the BD is that the sum rate does not grow linearly with the number of users and transmit antennas at low and medium signal-to-noise ratio regime, since the complete suppression of multi-user interference is achieved at the expense of noise enhancement. Also it performs poorly under imperfect channel state information. In this paper, we propose a generalized minimum mean-squared error (MMSE) channel inversion algorithm for users with multiple antennas to overcome the drawbacks of the BD for multiuser MIMO systems. We first introduce a generalized ZF channel inversion algorithm as a new approach of the conventional BD. Applying this idea to the MMSE channel inversion for identifying orthonormal basis vectors of the precoder, and employing the MMSE criterion for finding its combining matrix, the proposed scheme increases the signal-to-interference-plus-noise ratio at each user's receiver. Simulation results confirm that the proposed scheme exhibits a linear growth of the sum rate, as opposed to the BD scheme. For block fading channels with four transmit antennas, the proposed scheme provides a 3 dB gain over the conventional BD scheme at 1% frame error rate. Also, we present a modified precoding method for systems with channel estimation errors and show that the proposed algorithm is robust to channel estimation errors.

259 citations


"Co-channel interference suppression..." refers background in this paper

  • ...At present, some regularized versions of BDtype algorithms can deal with the limitation of the number of transmitting antennas [25, 26], but they are not referred to the application in multi-cell environment....

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