Signal-to-leakage-and-noise Ratio Research Articles

Sum-Rate Analysis for Massive MIMO Downlink With Joint Statistical Beamforming and User Scheduling

Statistical beamforming is an important technique for multi-user massive MIMO downlink, since it depends on the downlink channel covariance only. In this paper, we first derive an explicit analytical sum-rate expression for generic channel covariance-based beamforming scheme. Then, a low-complexity joint statistical beamforming and user scheduling algorithm via greedy search is proposed, where the beamforming is based on the signal-to-leakage-and-noise-ratio (SLNR) for closed-form design and tractable analysis, while the user scheduling is based on the derived sum-rate expression. Further, with the help of large-scale asymptotic simplifications and the introduction of the interference user number parameter, a simple analytical sum-rate expression of the joint algorithm is derived for channels with flat power beam spectrum. The expression explicitly exhibits the sum-rate behavior with respect to different network parameters and captures the effect of sum-rate-based user scheduling. Finally, simulation results are provided to verify our analytical results and to show the advantage of the proposed joint design compared with existing schemes.

A low-complexity 3D massive MIMO scheme jointly using statistical and instantaneous CSIT

In this paper, we propose a three-dimensional (3D) beamforming scheme for the massive multiple-input multiple-output (MIMO) system where the base station (BS) employs a uniform rectangular array (URA). In order to avoid the high computational complexity involving large-dimensional channel matrices, a two-stage beamforming method is applied where the second-stage beamforming is a Kronecker product of azimuth and elevation discrete Fourier transform (DFT) beamforming. These DFT prebeamformers are used for cell splitting and form effective channels with lower dimension for first-stage precoding. We develop a low-complexity user grouping algorithm based on the statistical channel state information at the transmitter (CSIT) to partition users. Each group of users is served by the signal-to-leakage-and-noise ratio (SLNR) precoding aiming at suppressing the intra-group and adjacent-group interferences, which is a good balance between performance and complexity. We derive the approximate signal-to-interference-plus-noise ratio (SINR) of our proposed scheme. Numerical results validate that the SINR approximations are tight and indicate the significance of the proposed 3D beamforming scheme.

Quadrature Amplitude Modulation Division for Multiuser MISO Broadcast Channels

This paper considers a discrete-time multiuser multiple-input single-output (MISO) Gaussian broadcast channel~(BC), in which channel state information (CSI) is available at both the transmitter and the receivers. The flexible and explicit design of a uniquely decomposable constellation group (UDCG) is provided based on pulse amplitude modulation (PAM) and rectangular quadrature amplitude modulation (QAM) constellations. With this, a modulation division (MD) transmission scheme is developed for the MISO BC. The proposed MD scheme enables each receiver to uniquely and efficiently detect their desired signals from the superposition of mutually interfering cochannel signals in the absence of noise. In our design, the optimal transmitter beamforming problem is solved in a closed-form for two-user MISO BC using max-min fairness as a design criterion. Then, for a general case with more than two receivers, we develop a user-grouping-based beamforming scheme, where the grouping method, beamforming vector design and power allocation problems are addressed by using weighted max-min fairness. It is shown that our proposed approach has a lower probability of error compared with the zero-forcing (ZF) method when the Hermitian angle between the two channel vectors is small in a two-user case. In addition, simulation results also reveal that for the general channel model with more than two users, our user-grouping-based scheme significantly outperforms the ZF, time division (TD), minimum mean-square error (MMSE) and signal-to-leakage-and-noise ratio (SLNR) based techniques in moderate and high SNR regimes when the number of users approaches to the number of base station (BS) antennas and it degrades into the ZF scheme when the number of users is far less than the number of BS antennas in Rayleigh fading channels.

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

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.

대용량 데이터 전송을 위한 다중 셀 MISO 하향 능동 안테나 시스템에서 3D 빔포밍 기법

본 논문은 다중 셀 다중입력 단일 출력 (MISO : multiple-input single-output) 하향링크 능동 안테나 시스템 (AAS : active antenna systems)에서 기지국의 수직 각도를 최적화하는 새로운 기법을 제시한다. 본 연구에서는 기존의 전역 탐색 방식 대신 간단하면서 최적의 값에 근사한 알고리듬들을 제안한다. 먼저, random matrix theory의 특성을 반영하여 평균 전송용량에 large system approximation이 적용된 수직적 빔포밍 알고리듬을 소개한다. 다음으로, signal-to-leakage-and-noise ratio (SLNR)을 기반으로 최적화 문제를 간단하게 만드는 수직적 빔포밍 알고리듬을 제안한다. 실험 결과를 통해 제안된 알고리듬들의 성능이 기존의 전역 탐색 알고리듬에 비해 복잡도가 매우 감소됨에도 불구하고 거의 비슷한 성능을 보임을 증명하였다. In this paper, we provide a new approach which optimizes the vertical tilting angle of the base station for multi-cell multiple-input single-output (MISO) downlink active antenna systems (AAS). Instead of the conventional optimal algorithm which requires an exhaustive search, we propose simple and near optimal algorithms. First, we represent a large system approximation based vertical beamforming algorithm which is applied to the average sum rate by using the random matrix theory. Next, we suggest a signal-to-leakage-and-noise ratio (SLNR) based vertical beamforming algorithm which simplifies the optimization problem considerably. In the simulation results, we demonstrate that the performance of the proposed algorithms is near close to the exhaustive search algorithm with substantially reduced complexity.

Hybrid coordinated strategy of downlink coordinated multi-point transmission

Coordinated multi-point (CoMP) transmission is put forward in the long term evolution-advanced (LTE-A) system to improve both average and cell-edge throughput. CoMP-joint processing (JP) scheme can get a larger cell-edge throughput and a lower bit error rate (BER) than the CoMP-coordinated beamforming (CB) scheme, but it also has higher complexity due to data sharing. A hybrid coordinated strategy with parameter α, which indicates the proportion of users employing the CoMP-JP scheme, is proposed to apply the CoMP-JP scheme to improve the poorer communication quality of cell edge and employ the CoMP-CB scheme for other users to enhance average throughput and spectral efficiency. This paradigm selects users defined by the certain threshold of signal to interference plus noise power ratio (SINR) corresponding to the parameter α to the CoMP-JP scheme. This paper compares the BER performance between the block diagonalization (BD) based precoding and the linear precoders by maximizing signal to leakage and noise ratio (SLNR), and also indicates that the SLNR based precoding algorithm gets lower BER than the BD based precoding algorithm with certain signal-to-noise ratios (SNRs). Finally, this paper discusses that the system performance is partially affected by the percentage of CoMP-JP users and concludes that 50% of users sorted to communicate under the CoMP-JP scheme will reach the best system performance.

Precoding based on Signal-to-leakage and Noise Ratio to Reduce ICI in MIMO-OFDM Systems

Current trends in the development of high-data-rate wireless systems focus on the integration of orthogonal frequencydivision multiplexing (OFDM) and multiple-input?multiple-output (MIMO).The combination of OFDM and the Multiple-InputMultiple-Output (MIMO) technique represents a promising candidate for future broadband wireless systems. This paper addresses the Inter Carrier Interference (ICI) issue in multiuser MIMO-OFDM systems operating in time-varying frequency selective channel environments.In our proposed method precoding based on signal-to-leakage-and-noise ratio (SLNR) is considered.In this paper model using precoding in MIMOOFDM is introduced.Based on the model algorithm for precoding matrix is developed.Simulation results confirms reduction in ICI without increasing complexity of a system.

A Leakage-Based Solution for Interference Alignment in MIMO Interference Channel Networks

Most recent research on iterative solutions for interference alignment (IA) presents solutions assuming channel reciprocity based on the suppression of interference from undesired sources by using an appropriate decoding matrix also known as a receiver combining matrix for multiple input multiple output (MIMO) interference channel networks and reciprocal networks. In this paper, we present an alternative solution for IA by designing precoding and decoding matrices based on the concept of signal leakage (the measure of signal power that leaks to unintended users) on each transmit side. We propose an iterative algorithm for an IA solution based on maximization of the signal-to-leakage-and-noise ratio (SLNR) of the transmitted signal from each transmitter. In order to make an algorithm removing the requirement of channel reciprocity, we deploy maximization of the signal-to-interference-and-noise ratio (SINR) in the design of the decoding matrices. We show through simulation that minimizing the leakage in each transmission can help achieve enhanced performance in terms of aggregate sum capacity in the system.

Inter-cell Interference Mitigation in Multi-cell Cooperating System Based on SLNR Method

Coordinated Multi-Point transmission/reception (CoMP) can increase the performance of the cell edge users, the spectrum efficiency and mitigate the inter-cell interference among cells. In the CoMP scenario, several base stations which usually need satisfy the cooperating condition serve a single or several cell-edge users cooperatively. As we know, the CoMP techniques can be characterized into many classes. For the joint transmission system which is a classical CoMP system, a large number of data sharing and channel information exchange will be needed, where the system inevitably become comparatively complex. However, in this paper, the coordinated beam forming system will be considered, where several base stations cope with the inter-cell interference among cells, and all the base stations will only exchange the channel information. Further, the downlink multi-cell coordinated beam forming system is considered in this paper. In this downlink multi-cell coordinated beam forming system, it is crucial to design appropriate pre-coding schemes that are able to mitigate the inter-cell interference. In obtainable pre-coding schemes, the Signal-to-leakage-and-noise ratio (SLNR) pre-coding scheme is a promising pre-coding scheme in downlink multi-cell coordinated beam forming system, which makes closed-form solution accessible. Moreover, the problem in designing the pre-coding vectors is not a coupled problem since the cooperative base stations need not optimize the pre-coding vectors jointly, which are responsible for their own design of pre-coding vectors, that is, they will just carry out independent optimization. In this paper, we proposed a novel pre-coding scheme based on the SLNR scheme, which will determine the pre-coding vectors via iteration. The simulation results show that, the proposed method outperforms the conventional SLNR pre-coding scheme in bit error rate performance.

Signal to Leakage and Noise Ratio Based Beamforming and User Scheduling for TD-LTE-A Systems

In TD-LTE-A downlink, signal to leakage and noise ratio (SLNR) based beamforming can eliminate the co-channel interference and noise for multi-user MIMO mode effectively and can be realized more easily than the traditional ideal SINR based algorithms. Moreover, user scheduling can be combined with the SLNR based beamforming algorithm to obtain a better performance. Hence, in this paper, SLNR based beamforming is firstly compared with traditional beamforming algorithms, and then, a suboptimal maximum minimum SLNR (MMSLNR) scheduling strategy is proposed to improve the average BER performance and sum capacity of TD-LTE-A system and decrease the scheduling complexity as well.

An Improved Beamforming Method Based on SLNR for Downlink Multi-user Multi-stream MIMO System

We present an improved beamforming method based on the signal-to-leakage-and-noise ratio (SLNR) for downlink multi-user multi-stream MIMO systems in this paper, which further take into account the co-channel interference. The simulation results demonstrate that the proposed method outperforms the original SLNR criterion and achieves considerable gains in BER performance.

A Leakage-Based Beamforming Algorithm for Cognitive MIMO Systems via Game Theory

Cognitive radio has been recently proposed as a promising technology to achieve efficient use of spectrum resources. In this paper, we consider spectrum sharing in a MIMO system where several secondary users (SUs) share spectrum with a primary user (PU). A leakage-based beamforming algorithm is proposed via game theory. The objective is to maximize the sum throughput of SUs subject to the signal-to-leakage-and-noise ratio (SLNR) constraint of SUs and PU interference constraint. The sum-throughput maximization problem is formulated as a non-cooperative game, where the SUs compete with each other over the resources offered by the PU. Nash equilibrium is considered as the solution of this game. Simulation results show that the proposed algorithm can achieve a high sum throughput and converge to a locally optimal beamforming vector.

A Power Allocation Scheme Using Updated SLNR Value Based on Perturbation Theory

The performance of downlink multiple-input multiple-output (MIMO) cellular networks is limited by co-channel interference (CCI). In this paper, we propose a linear precoding scheme based on signal-to-leakage-and-noise ratio (SLNR) criteria which can reduce the CCI significantly. Since each user’s SLNR value is corresponding to the largest eigenvalue of the generalized matrix which indicates the channel quality that we propose a scheme to do a dynamic power allocation as an auxiliary way to improve SLNR precoding scheme. We use the perturbation theory to update each user’s SLNR value each time step in time-varying channels rather than directly decompose the channel matrix so as to reduce the amount of calculation. The simulation results show that the proposed scheme offers about 0.3 bps/Hz additional capacity gain and 0.5 dB BER gain over conventional SLNR precoding method with lower computational complexity. And it also obtains about 0.5 bps/Hz additional capacity gain and 1 dB BER gain compared to the scheme only update the preceding vectors.

Linear precoding design for cognitive multiuser MIMO systems using a leakage-based approach

In this paper, we develop linear precoding schemes for cognitive radio (CR) multiuser multiple-input multiple-output (MU-MIMO) downlink systems. A secondary user base station (SBS) with multiple secondary users (SUs) sharing the primary user (PU) spectrum is considered. In the proposed scheme, the block diagonalisation (BD) algorithm is adopted to remove the co-channel interference from the SBS to the PU completely, and the matching weighted signal-to-leakage-and-noise ratio (SLNR) maximisation algorithm is proposed to mitigate interference between SUs. We also discuss the cases where the SBS has only partial channel information and the channel estimation with errors, respectively. The proposed scheme does not require a strict restriction on the number of transmit and receive antennas. Simulation results show that the proposed scheme can achieve high sum rate throughput with affordable complexity.

Statistical Eigenmode-Based SDMA for Two-User Downlink

This paper proposes a statistical-eigenmode space-division multiple-access (SE-SDMA) transmission approach for a two-user downlink system where two transmit antennas are deployed at the base station and each mobile user has only one receive antenna, assuming that only statistical channel state information (SCSI) is available at the transmitter. By maximizing a lower bound of the ergodic signal-to-leakage-and-noise ratio (SLNR), the proposed SE-SDMA approach selects two users with orthogonal principal statistical eigen-directions and then transmits to each user along the corresponding eigenmode. For this approach, we derive an exact expression of the achievable ergodic rate, and compare it with the zero-forcing beamforming (ZFBF) system exploiting instantaneous CSI. We show that SE-SDMA can achieve the maximum ergodic sum-rate of the two selected users, and provide significant user selection gains. For comparison with ZFBF, we show that the rate gap between SE-SDMA and ZFBF with perfect CSI at the transmitter (CSIT) tends to zero in highly correlated channels. Further, when ZFBF is implemented with inaccurate CSIT, the operating regions of SE-SDMA and ZFBF are investigated for different ranges of signal-to-noise ratio (SNR), instantaneous CSIT accuracy levels, and spatial correlation levels. Numerical results confirm the analytically derived conclusions, and physical insights are provided.

Power Allocation for SLNR Precoding based on MMSE Criterion in Multiuser MIMO System

Abstract In order to fulfill the rapid increasing demands of the broadband multimedia and wireless communication, the Multi-input multi-output (MIMO) technique serving as one of the key technologies of the physical layer, have drawn a lot of attention in the past few years. Multi-user multiple-input multiple-output (MU-MIMO) wireless communication system has rapidly gained in popularity over the past decade due to its promising improvement in terms of system capacity and transmission quality without incurring extra bandwidth or transmission power. Multi-user interference (MUI) is one of the major impairments on the performance of multi-user multiple input multiple-output (MU-MIMO) wireless communication system. Signal-to-leakage-and-noise ratio (SLNR) precoding suppresses MUI and provides a closed form solution to the coupling problem encountered in the conventional designs based on maximizing signal-to-interference-and-noise ratio (SINR). In this paper, to enhance the transmission quality for SLNR precoding in the MU-MIMO downlink communication, an iterative power allocation scheme is proposed. Based on minimum total mean square error criterion (MMSE), subject to a total transmit power constraint, power allocation factors, precoding and decoding matrix are regenerated and updated in turn iteratively. A local optimal solution could be solved in this alternating optimization. Simulation results demonstrate the improved bit error rate (BER) performance and the convergence of MSE of the proposed scheme.

On the Equivalence Between SLNR and MMSE Precoding Schemes with Single-Antenna Receivers

This letter considers transmit precoding schemes based on the maximum signal-to-leakage-and-noise ratio (SLNR) in multiuser MIMO systems with single-antenna receivers. The closed-form solution of SLNR design is generally given in the form of the eigenvector associated to the maximum eigenvalue. In this letter, analytic expressions of SLNR-based solutions and resulting SLNR are derived for a generic power allocation (GPA). The solution is shown to be a function of user-allocated power and an arbitrary phase shift. Under equal power allocation (EPA), the SLNR precoding scheme is shown to be equivalent to the minimum mean square error (MMSE) precoding scheme. Several useful implications in terms of the possible extension of existing algorithms and performance analysis are also discussed.

A Successive Iterative Optimal Pre-Coding Algorithm for Downlink Multi-User MIMO System

Spatial multiplexing in the multi-user MIMO downlink allows each user in the system to receive multiple data subchannels simultaneously using the same time and spectral resources. In this paper, a successive iterative optimal algorithm based on signal-to-leakage-and-noise-ratio (SLNR) maximization algorithm is proposed, which make use of the unused subspace of some known users to improve the space gain of the other users and has no strict constraint on transmit and receive antennas numbers. According to the simulation results, the proposed algorithm outperforms the original SLNR algorithm, and has a considerable improvement in the system performance.

Sensing-Based Opportunistic Spectrum Sharing for Cognitive Radio Downlink MIMO Systems

In this letter we propose a practical sensing-based opportunistic spectrum sharing scheme for cognitive radio (CR) downlink MIMO systems. Multi-antennas are exploited at the secondary transmitter to opportunistically access the primary spectrum and effectively achieve a balance between secondary throughput maximization and mitigation of interference probably caused to primary radio link. We first introduce a brief secondary frame structure, in which a sensing phase is exploited to estimate the effective interference channel. According to the sensing result and taking the interference caused by the primary link into account, we propose an enhanced signal-to-leakage-and-noise ratio (SLNR)-based precoding scheme for the secondary transmitter. Compared to conventional schemes where perfect knowledge of the channels over which the CR transmitter interferes with the primary receiver (PR) is assumed, our proposed scheme shows its superiority and simulation results validate this.

A Successive Iterative Optimal Pre-Coding Algorithm for Downlink Multi-User MIMO System

Spatial multiplexing in the multi-user MIMO downlink allows each user in the system to receive multiple data subchannels simultaneously using the same time and spectral resources. In this paper, a successive iterative optimal algorithm based on signal-to-leakage-and-noise-ratio (SLNR) maximization algorithm is proposed, which make use of the unused subspace of some known users to improve the space gain of the other users and has no strict constraint on transmit and receive antennas numbers. According to the simulation results, the proposed algorithm outperforms the original SLNR algorithm, and has a considerable improvement in the system performance.