Effective Signal-to-interference-plus-noise Ratio Research Articles

An optimal calibration factor for mutual information effective SINR mapping scheme in 5G NR

AbstractIn this letter, an optimal calibration factor for mutual information effective signal‐to‐interference‐plus‐noise ratio (SINR) mapping (MIESM) scheme in fifth‐generation new radio (5G NR) is provided. By applying the optimal calibration factor to the MIESM scheme, the estimation accuracy of the effective SINR can be improved. The optimal calibration factor minimizes the mean squared error (MSE) of the difference between the estimated effective SINR and the required SNR under additive white Gaussian noise (AWGN) at a block error rate (BLER) of 10%. Simulation results show that the optimized MIESM scheme outperforms the non‐optimized MIESM scheme.

PER Prediction in MIMO-OFDM Systems With Approximate Demodulation: A GMI-Based Method

In multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems, the symbols in a packet may undergo different signal-to-interference-plus-noise ratio (SINR) levels, making packet error rate (PER) prediction a challenging task. Effective SINR mapping (ESM) simplifies this problem by mapping the SINRs on different symbols to a single packet-level effective SINR. A novel ESM method, referred to as mean generalized mutual information mapping (MGMIM), is put forward in this paper. The proposed method transforms the SINR of each symbol to the generalized mutual information (GMI) and then derives an effective SINR from the mean GMI measure over different symbols. The derived effective SINR summarizes the effect of all the SINRs on the packet, which would produce the same PER performance under an additive white Gaussian noise (AWGN) channel. Compared to existing techniques, MGMIM does not require MCS-dependent tuning parameters but delivers competitive or even better PER prediction accuracy. More importantly, MGMIM allows reliable PER prediction when the receiver employs approximate demodulation, which boosts its applicability in practice. These features are demonstrated by comparative numerical simulations.

Physical Layer Abstraction for Multi-Connectivity Communications: Modeling and Analysis

The multi-connectivity is a key enabler for ultra-reliable low-latency communications. To evaluate its performance and suitability to various use cases system-level studies are essential, where the physical layer (PHY) plays an important role. Therefore, PHY modeling is required which is time-intensive and requires highly complex computations. For this purpose, the PHY performance is usually abstracted in terms of signal-to-interference-plus-noise ratio (SINR), also known as physical layer abstraction (PLA). However, due to fading, the symbols inside a packet could have different SINRs which require effective SINR mapping to compute an equivalent SINR. In the context of multi-connectivity, the received SINR depends on all connected links where each link experiences independent fading and on the used link combining technique. As a result, the computation of effective SINR also depends on the combining technique and fading experienced by individual links. To model PHY performance by considering all these effects, we develop PLA for multi-connectivity communications. This includes the computation of received symbols SINR for various link combining techniques and mapping them to effective SINR using enhanced exponential effective SINR mapping (eEESM). Furthermore, a new optimization method is introduced for eEESM to reduce its optimization complexity. Simulation results show that the proposed PLA accurately estimate the performance of different order of multi-connectivity communications under various fading conditions.

A Fine-Grained Analysis of Time Reversal MU-MISO Systems Over Correlated Multipath Channels With Imperfect CSI

Time reversal (TR) is regarded as a potential future transmission scheme for multi-user (MU) multiple-input single-output (MISO) ultra-wideband (UWB) communication systems. In spite of TR’s good performance in MU-MISO UWB systems, it suffers from performance degradation due to spatial correlation and imperfect channel-state information. In this paper, a comprehensive performance analysis of MU-MISO UWB systems with a TR pre-filter is provided. Both spatial correlation and channel estimation errors (CEE) are taken into account in the propagation channel model, and the system performance is mainly studied in terms of its effective signal-to-interference-plus-noise ratio (SINR), channel capacity, and bit error rate. The novel closed-form expressions for the average effective SINR are derived in order to characterize the influence of propagation conditions such as channel impulse response duration, spatial correlation, and CEE on TR performance metrics. The expressions reveal more precisely to us that spatial correlation and CEE have different effects on the average power of the desired signal, inter-symbol interference, and inter-user interference. Moreover, the impacts of spatial correlation and CEE on the performance of MU-MISO TR system are thoroughly investigated. In particular, the capacity loss of MU-MISO TR system due to spatial correlation and CEE is quantified and fully discussed at the end of this paper. It is shown that high spatial correlation and CEE cause a remarkable reduction in bandwidth efficiency. Finally, all theoretical results are confirmed by numerical simulations.

Performance Scaling Law for Multicell Multiuser Massive MIMO

This paper provides a comprehensive scaling law-based performance analysis for multicell multiuser massive multiple-input-multiple-output (MIMO) downlink systems. Imperfect channel state information (CSI), pilot contamination, and channel spatial correlation are all considered. First, a sum-rate lower bound is derived by exploiting the asymptotically deterministic property of the received signal power, while keeping the random nature of other components in the signal-to-interference-plus-noise-ratio (SINR) intact. Via a general scaling model on important network parameters, including the number of users, the channel training energy and the data transmission power, with respect to the number of base station antennas, the asymptotic scaling law of the effective SINR is obtained, which reveals quantitatively the tradeoff of the network parameters. More importantly, pilot contamination and pilot contamination elimination (PCE) are considered in the analytical framework. In addition, the applicability of the derived asymptotic scaling law in practical systems with large but finite antenna numbers are discussed. Finally, sufficient conditions on the parameter scalings for the SINR to be asymptotically deterministic in the sense of mean square convergence are provided, which covers existing results on such analysis as special cases and shows the effect of PCE explicitly.

Link abstraction models for multicarrier systems: A logistic regression approach

SummaryEvaluation of complex wireless systems through simulations is commonly tackled with an abstraction of physical link behavior. This procedure is performed in 2 phases: Firstly, training is performed at the link level, resulting in a mapping function from signal‐to‐interference‐plus‐noise ratio (SINR) to block error rate (BLER); and secondly, physical layer signal processing is replaced by the resulting link‐level mapping function. Several methods have been proposed in the literature for link abstraction. The well‐known exponential effective SINR mapping (EESM) is likely to be the most extensively used procedure for multicarrier transmission. In short, EESM estimates an effective SINR from the whole set of SINRs of useful subcarriers by means of a single parameter mapping function, which must be previously optimized through training. Later on, BLER is assumed as that of the effective SINR over an additive white Gaussian noise channel. In this paper, we propose a novel method for BLER prediction named as logistic regression‐based link method (LRLM). Mean and standard deviation of the SINR set can accurately capture BLER behavior for wideband multicarrier systems through a simpler function, thus reducing the amount of information to be stored compared to EESM. Moreover, LRLM is very flexible and may include extra predictors to reduce the number of different models to be stored. Performance results show that LRLM is able to predict accurately the BLER for all modulation and coding schemes and transport block sizes defined for Long‐Term Evolution technology.

Effective SINR for MIMO System with Decorrelation Based Receive Transformation Under Multi-user Interference

We study the effective signal to interference-plus-noise ratio (SINR) of the MIMO detector (or decoder) for the MIMO system with decorrelation based receive transformation (MIMO-DRT), in which the decorrelation based transformation is employed on the received signal of the MIMO receiver. By performing eigendecomposition on the inverse of the covariance matrix for interference plus noise, we express the effective SINR of MIMO-DRT in terms of the eigenvalues of the covariance matrix for interference plus noise and derive the SINR gain (relative to the MIMO system without receive transformation) provided by MIMO-DRT. We prove that the SINR gain provided by MIMO-DRT is larger than or equal to one. Furthermore, we show by both the analytical results and the simulation results that the SINR gain provided by MIMO-DRT increases with the interference to noise ratio and converges to one as the number of cochannel users gets large.

On the dimensioning of LTE and LTE‐advanced networks

AbstractNetwork design consists of evaluating cell coverage and capacity and may involve many parameters related to environment, system configuration and quality of service requirements. The key parameter for cost optimised Long Term Evolution (LTE)‐based network dimensioning is to provide a tight approximation of the effective signal‐to‐interference‐plus‐noise ratio (SINR) distribution. This paper provides a novel framework for LTE and LTE‐advanced network dimensioning, where the classical single‐carrier SINR performance evaluation is extended to multi‐carriers systems operating over frequency selective channels. Extension is achieved by expressing the link outage probability in terms of the statistics of the effective SINR. For effective SINR computation, the exponential effective SINR mapping technique is used. Closed‐form expression for the link outage probability is achieved assuming a log skew normal approximation for single‐carrier case. Then we rely on the log‐normal approximation to express the exponential effective SINR distribution as a function of the mean and standard deviation of the SINR of a generic subcarrier. Effective SINR values are evaluated at click speed in each point on the network. Simulations show that the proposed framework provides results with accuracy within 0.5 dB for any defined outage probability target. Copyright © 2015 John Wiley & Sons, Ltd.

Performance Study and Optimization of Cooperative Diversity Networks with Co-Channel Interference

In this paper, we investigate the effect of co-channel interference on the performance of cooperative diversity networks with amplify-and-forward (AF) relaying. We consider both conventional and opportunistic relaying. First, we obtain a tight upper-bound for the equivalent signal-to-interference-plus-noise ratio (SINR) at the destination. Subsequently, the cumulative distribution function (CDF), probability density function (PDF) and moment generating function (MGF) of the effective SINR are determined based on the upper-bound. Expressions for the error probabilities in both conventional and opportunistic relaying are derived utilizing the statistical characterization of the effective SINR. We also derive an approximate PDF of the equivalent instantaneous SINR at the destination. This leads to a simple and general asymptotic error probability expression which facilitates better insight into the effect of different system parameters on the error probability. Furthermore, we investigate the problem of optimum resource allocation in the network aiming at improving performance in the presence of resource constraints. We present numerical results that illustrate the excellent match between the analytical results and the simulation results, and the performance enhancement resulting from the proposed optimal resource allocation.

An Adaptive PRB, Power and MCS Allocation Using AMC for MIMO-OFDMA Systems

Long Term Evolution (LTE) is a promising technology for a high communication quality thanks to its radio link flexibility using Adaptive Modulation and Coding (AMC), Multiple Input Multiple Output (MIMO) and Orthogonal Frequency Division Multiple Access (OFDMA) technologies. In this paper, we address the adaptive resource allocation problem in down-link transmission of MIMO-OFDMA systems. We aim at maximizing the total system capacity to meet the 4G-technologies promises. In order to reduce the computational complexity, the original optimization problem is divided into sub-optimal ones. Firstly, a recursive Physical Resource Block (PRB) allocation algorithm is developed where the Effective Signal-to-Interference-plus-Noise Ratio (ESINR) metric is investigated to properly characterize the channel condition. Secondly, a power allocation procedure is performed. As all resource blocks allocated to the same user must use the same Modulation and Coding Scheme (MCS) according to the LTE standard requirements, power optimization sub-problem is divided into three steps: power allocation among PRBs, power allocation among antennas and power allocation among users. Finally, a more effective MCS is obtained, which ensures a better system capacity. Simulation results prove the efficiency of the proposed method to maximize the total system capacity with a low complexity even in the case of loaded systems compared to Minimum-MCS (Min-MCS) and Maximum-SINR (Max-SINR) algorithms.

MIMO 프리코딩을 고려한 셀 탐색 기법

CS/CB(Coordinated Scheduling/Beamforming) 방식은 인접 기지국으로부터의 간섭신호를 최소화시키는 MIMO(Multiple Input Multiple Output) 프리코더를 선택함으로써 셀 경계 사용자의 수율을 증가시킨다. 그러나 현재의 LTE(Long Term Evolution) 시스템에서는 안테나 한 개를 사용하여 주위 기지국으로부터 전송된 동기신호와 기준신호를 사용하여 초기화 단계에서 서빙 셀이 선택된다. 이와 같이 선택된 셀은 초기화 단계에서 MIMO 프리코더 이득을 고려하지 않고 선택되었기 때문에 데이터 전송시 최적의 선택이 아닐 수 있다. 본 논문에서는 MIMO 프리코더를 갖는 LTE 시스템을 위하여 초기화 단계에서 프리코더의 영향을 고려하여 셀을 선택하는 기법을 제안한다. 제안된 기법은 후보 기지국들에서 전송한 기준신호를 사용하여 획득한 정보(랭크, 유효 채널 용량, 유효 SINR(Signal to Interference plus Noise Ratio))를 사용하여 셀 경계의 단말이 서빙 기지국을 선택할 수 있도록 한다. 제안한 기법은 기존의 기법과 비교하여 다중 셀 환경하의 LTE 시스템에서 채널 용량을 크게 향상시킬 수 있음을 모의실험을 통하여 확인한다. In the CS/CB(Coordinated Scheduling/Beamforming) scheme, the cell edge user throughput is increased by selecting MIMO (Multiple Input Multiple Output) precoders which can minimize the interferences from adjacent base stations (BSs). However, in current LTE(Long Term Evolution) systems, the serving cell is selected in the initialization stage by using the synchronization signals and cell specific reference signals transmitted by adjacent BSs with a single antenna. The selected BS in the initialization stage may not be the best one since the MIMO precoding gain has not been considered in the cell selection stage. In this paper, a new cell selection technique is proposed for LTE systems with MIMO precoder by taking into account the effect of the precoder in the initialization stage. The proposed technique enables a user equipment (UE) in the cell boundary to select the serving BS by using the information (channel rank, effective channel capacity, and effective SINR(Signal to Interference plus Noise Ratio)) acquired from cell specific reference signals of candidate BSs. It is verified by computer simulation that the proposed technique can increase the channel capacity significantly in the multi-cell environments, compared with the conventional CS/CB scheme.

Performance Evaluation of Adaptive MIMO-OFDM Systems with Limited Feedback Using Measurement Based Channel Models

Performance evaluation of enhanced link adaptation method for MIMO-OFDM systems with limited feedback using measurement based channels and a stochastic channel model is presented in this paper. In particular, impact of practical channel estimation and feedback errors on link performance is analyzed. An adaptive spatial and modulation scheme selection process is based on the effective signal-to-interference-plus-noise ratio (ESINR). Mutual information effective SINR mapping method is applied for calculating ESINR values due to its capability of accurate estimation of the error rate performance of large variety of MIMO channels. Numerical results show that simple adaptive systems that switch between diversity/multiplexing or beamforming/multiplexing schemes obtain relatively good performance in realistic 2 × 2 MIMO channels. It is also shown that the imperfect channel estimation and feedback errors can have significant impact on the link performance. Furthermore, it is noticed that using the stochastic channel model in performance simulations can give rather pessimistic results compared to true measurement data.

Dimensioning of OFDM/OFDMA-Based Cellular Networks Using Exponential Effective SINR

The classical single-carrier cell-planning procedure is extended to multicarrier systems operating over frequency-selective channels. Extension is achieved by expressing the link outage probability in terms of the statistics of the effective signal-to-interference-plus-noise ratio (SINR). This permits evidencing the role of the number of allocated subcarriers per slot on planning. The exponential effective SINR mapping (EESM) method is adopted. A closed-form expression for the link outage probability is achieved assuming a Gaussian approximation for the derivation of the statistics of the EESM-based SINR. This formula is then used to set up a simple planning procedure requiring the evaluation of only two averages of the SINR calculated on a generic subcarrier. The effectiveness of the proposed approximation with the number of allocated subcarriers per slot is investigated. An upper bound of the link outage probability in the presence of interference is provided. For illustrative purposes, the proposed methodology is applied to the calculation of the network parameters for the typical two-cell interference scenario. It is shown that the considered approximation provides results with accuracy within 1 dB for a number of subcarriers greater than ten and for an outage performance target of 5%.

하향 링크 셀룰러 시스템의 Eigen-Beamforming 전송을 위한 적응적 인접 셀 간섭 완화 방법

MIMO(Multiple-Input Multiple-Output) 시스템에서 EB(Eigen-Beamforming)는 MIMO 채 널의 특이 값 분해(Singular Value Decomposition: SVD)를 통하여 수신기의 유효 신호 대 잡음비(Signal-to-Interference Plus Noise Ratio: SI-NR)를 최대화하는 빔을 형성하는 방법으로써 널리 활용되고 있으나, 인접 셀 간섭 신호의 영향으로 셀 경계에 위치한 단말기의 신호 검출 성능은 급격히 열화되고 전송 효율은 감소하게 된다. 본 논문에서는 EB 전송을 활용하는 경우, 적응적 인접 셀 간섭 완화 방안을 제시하고 그 수신 성능을 평가한다. 특히, EB 전송을 이용하여 기지국예서 전송된 신호를 단말기가 수신할 때, 최대의 유효 신호 대 간섭 잡음비를 얻기 위한 OC(Optimum Combining) 및 MMSE-ISD(Minimum Mean-Squared Error for Intercell Spatial Demultiplexing)를 적응적으로 사용하기 위한 기준을 제시하고 유효 신호 대 간섭 잡음비 및 전송 용량 측면의 수신 성능을 분석한다. 제안하는 적응적 수신 방식은 수신 빔포밍 벡터만을 사용하는 기존의 EB 수신 방식 대비 평균 전송 용량 측면에서 향상된 성능을 보이며, 셀 경계 지역에 단말기가 위치할 경우 최대 2 bps/Hz 성능 개선을 가져온다. EB(Eigen-Beamforming) has widely been applied to MIMO(Multiple-Input Multiple-Output) systems to form beams which maximize the effective signal-to-interference plus noise ratio(SINR) of the receiver using the singular value decomposition(SVD) of the MIMO channel. However, the signal detection performance for the mobile station near the cell boundary is severely degraded and the transmission efficiency decreases due to the influence of the interference signal from the adjacent cells. In this paper, we propose an adaptive interference mitigation method for the EB transmission, and evaluate the reception performance. In particular, a reception strategy which adaptively utilizes optimal combining(OC) and minimum mean-squared error for Intercell spatial demultiplexing(MMSE-lSD) is proposed, and the reception performance is investigated in terms of the effective SINR and system capacity. For the average system capacity, the proposed adaptive reception demonstrates the performance enhancement compared to the conventional EB reception using the receiver beamforming vector, and up to 2 bps/Hz performance gain is achieved for mobile station located at the cell edge.