Signal To Interference And Noise Ratio Research Articles

Transmission scheduling for multi-process multi-sensor remote estimation via approximate dynamic programming

In this paper, we consider a remote estimation problem where multiple dynamical systems are observed by smart sensors, which transmit their local estimates to a remote estimator over channels prone to packet losses. Unlike previous works, we allow multiple sensors to transmit simultaneously even though they can cause interference, thanks to the multi-packet reception capability at the remote estimator. In this setting, the remote estimator can decode multiple sensor transmissions (successful packet arrivals) as long as their signal-to-interference-and-noise ratios (SINR) are above a certain threshold. In this setting, we address the problem of optimal sensor transmission scheduling by minimizing a finite horizon discounted expected estimation error covariance cost across all systems at the remote estimator, subject to an average transmission cost. While this problem can be posed as a stochastic control problem, the optimal solution requires solving a Bellman equation for a dynamic programming (DP) problem, the complexity of which scales exponentially with the number of systems being measured and their state dimensions. In this paper, we resort to a novel Least Squares Temporal Difference (LSTD) Approximate Dynamic Programming (ADP) based approach to approximating the value function. More specifically, an off-policy based LSTD approach, named in short Enhanced-Exploration Greedy LSTD (EG-LSTD), is proposed. We discuss the convergence analysis of the EG-LSTD algorithm and its implementation. A Python based program is developed to implement and analyse the different aspects of the proposed method. Simulation examples are presented to support the results of the proposed approach both for the exact DP and ADP cases.

Joint power allocation and cooperative analog beamforming for ultra‐dense low Earth orbit satellite constellation networks

SummaryIn this paper, downlink multigroup multicast transmission in the ultra‐dense low Earth orbit satellite constellation networks with full frequency reuse is studied. Multicast transmission significantly improves the system performance compared with point‐to‐point transmission. However, multicast capacity is constrained by the signal to interference and noise ratio (SINR) of bottleneck users in each group. To tackle this problem, we propose an alternating optimization‐based joint power allocation and cooperative beamforming algorithm (AO‐JPACB) to enhance the SINR of the bottleneck users and improve the system capacity. Simulation results show that the proposed AO‐JPACB algorithm can improve the system capacity compared to single‐satellite schemes.

Guided MAC to Enhance Quality of Experience of Video Data Transmission over Massive MIMO

Massive MIMO (M-MIMO) system comprises of multiple number of antennas to achieve energy- efficiency and large gains in spectral-efficiency in comparison to existing MIMO technology. High speed and Quality of Experience (QoE) of video data over wireless communication has always been a challenge for the researchers due to scarcity of the bandwidth, fading and interference. The channels with high noise corrupt the transmitted video and results in poor QoE of at the receiver. Therefore, to maintain the quality of transmitted video, it is highly desirable to identify noisy channels and avoid transmission over them. This paper deals with QoE of the transmitted video over Massive MIMO channels. The channels are categorized into two categories: good and bad depending upon the value of Signal to Interference and Noise Ratio (SINR). A channel above the minimum acceptable value (threshold) of SINR is categorized as good channel otherwise bad channel. A Guided MAC layer (GMAC) protocol is designed to transmit the video data over good channels only and to discard the transmission over bad channels.

Performance Analysis of Rate Splitting in Massive MIMO Systems with Low Resolution ADCs/DACs

In this paper, we propose rate-splitting (RS) multiple access to mitigate the effects of quantization noise (QN) inherent in low-resolution analog-to-digital converters (ADCs) and digital-to-analog converters (DACs). We consider the downlink (DL) of a multiuser massive multiple-input multiple-output (MIMO) system where the base station (BS) is equipped with low-resolution ADCs/DACs. The BS employs the RS scheme for data transmission. Under imperfect channel state information (CSI), we characterize the spectral efficiency (SE) and energy efficiency (EE) by deriving the asymptotic signal-to-interference-and-noise ratio (SINR). For 1-bit resolution, the QN is very high, and the RS scheme shows no rate gain over the non-RS scheme. As the ADC/DAC resolution increases (i.e., 2–3 bits), the RS scheme achieves higher SE in the high signal-to-noise ratio (SNR) regime compared to that of the non-RS scheme. For a 3-bit resolution, the number of antennas can be reduced by 27% in the RS scheme to achieve the same SE as the non-RS scheme. Low-resolution DACs degrades the system performance more than low-resolution ADCs. Hence, it is preferable to equip the system with low-resolution ADCs than low-resolution DACs. The system achieves the best SE/EE tradeoff for 4-bit resolution ADCs/DACs.

Multi-element full-duplex FSO transceiver design using optimum tiling

With ever-growing demand of high-speed mobile data and in vision of smart cities, optical wireless, a.k.a. free-space optical (FSO), communication deem to be a critical technology due to its significantly faster data transfer rate, higher security, lower costs, and reduced power usage. These beneficial effects have led to interest in exploring FSO technologies for mobile platforms such as drone-based cell tower to provide Internet services to remote areas, or even for wireless communications on the ground with jammed radio channels as in battlefields. Direct line-of-sight (LOS) is required to establish secure directional FSO communication (FSOC) links which are highly susceptible to random and erratic movements of the mobile nodes as well as the turbulence in the free-space medium. The performance of FSOC links can be improved by designing multi-element tiling of the laser-based transceivers which is capable of in-band full-duplex (IBFD) communication. In this work, we propose a genetic algorithm framework to explore optimized multi-element FSO transceiver tiling patterns to ensure maximal signal-to-interference and noise ratio (SINR) and minimize the effects of vibration of the mobile platform and atmospheric turbulence.

Interference Rejection Combining Approach in Vehicle Communication Systems for Throughput Enhancement

In this paper, we present interference rejection combining scheme for interference suppression in wireless access in vehicular environments (WAVE) system. WAVE system performances depend on interference traffic since various signals and noises are present due to various vehicles on the road. The IRC scheme can minimize the interference presence from the received signal within the massive interference condition, resulting in the substantial gain of signal-to-interference and noise ratios (SINR) and performance. Based on the experiment of our proposed scheme, given the vehicle speed, SINR and different channel condition, our proposed scheme for interference suppression achieved significant improvements by 2 dB SINR performance gain in the low speed condition and above 0.5 dB performance gain at the high speed case. To extend our scheme for the comprehensive analysis, we also produced the vehicle speed and SINR performance map, which showed the performance pattern over vehicle speed and SINR of our scheme.

A REVIEW OF INTER CELL INTERFERENCE MANAGEMENT IN REGULAR AND IRREGULAR GEOMETRY CELLULAR NETWORKS

This paper reviews the inter-cell interference (ICI) mitigation approaches in the OFDMA based multicellular networks with more emphasis on the frequency reused based ICI coordination schemes in the downlink systems. The geometry of the network severely affects the Signal to Interference and Noise Ratio (SINR); therefore, the wireless cellular systems are strongly dependent on the spatial BSs configuration and topology of a network. ICI mitigation techniques for both regular and irregular geometry networks are analyzed and a qualitative comparison along with the future research directions are presented.

Coverage analysis of indoor users from mm‐wave multi‐RAT small cells deployed along roads

AbstractThe initial deployment of millimeter‐wave (mm‐wave) base stations (BSs), for example, by Verizon and AT&T will be on top of lamp‐posts along the roads of an urban scenario. These deployments will mainly target the outdoor pedestrian users and provide on‐demand ultra‐high data rates. However, as the mm‐wave deployments mature, the operator must necessarily dimension the network by taking into consideration the requirements of the indoor cellular users as well. In this paper, we study the extent of indoor coverage with on‐road BS deployments, so as to enable the network operators with necessary system design and network dimensioning insights. We derive the tier and radio access technique (RAT) selection probabilities of the typical indoor user, and consequently, we characterize its signal to interference and noise ratio (SINR) coverage probability. Based on the density of roads in the city, we prescribe the optimal density of the BSs required to maximize the SINR coverage of the indoor users.

SINR-based power schedule of sensors and DoS attackers in wireless network

In this paper, the game theory approaches are used to solve the power schedule problem in the wireless communication network. All sensors can be affected by DoS attackers when transmitting data. The game process between sensors and attackers is established as Bayesian game process. First, a Nash Equilibrium (NE) framework is proposed based on the object function consist of signal-to-interference-and-noise-ratio (SINR). Second, the total power of sensors is considered to have two types, and each type has some power levels. Unlike NE, both sensors and attackers no longer learn the specific total power of each other. However, sensors and attackers can get the type distribution of each other. In this situation, the strategies of sensors and attackers are formulated by introducing the Harsanyi transformation, and the Bayesian Nash Equilibrium (BNE) is solved. Finally, the Bayesian equilibrium strategies used by both offensive and defensive players are compared in the numerical example, which can illustrate the advantage of making full use of incomplete information.

Space-Constrained Arrays for Massive MIMO

We analyse the behavior of a massive multi-user MIMO (MU-MIMO) system comprising a base station (BS) equipped with one of five antenna topologies whose spatial apertures are either unconstrained, or space-constrained. We derive the normalized mean interference (NMI) with a ray-based channel model, as a metric for topology comparison. Using an existing derivation for a horizontal uniform rectangular array (HURA), we provide closed-form NMI equations for a uniform linear array (ULA) and uniform circular array (UCirA). We then derive the same for a vertical URA (VURA) and uniform cylindrical array (UCylA). Results for the often-considered unconstrained case confirm the prior understanding that topologies with wider azimuth footprints aid performance. However, in the constrained case, performance is dictated by the angular resolution of the topology, particularly in elevation. We confirm the behavioral patterns predicted by the NMI by observing the same patterns in the signal-to-interference-and-noise-ratio (SINR) with minimum mean-squared error (MMSE) processing.

Sparse Backbone and Optimal Distributed SINR Algorithms

We develop randomized distributed algorithms for many of the most fundamental communication problems in wireless networks under the Signal to Interference and Noise Ratio (SINR) model of communication, including (multi-message) broadcast, local broadcast, coloring, Maximal Independent Set, and aggregation. The complexity of our algorithms is optimal up to polylogarithmic preprocessing time. It shows—contrary to expectation—that the plain vanilla SINR model is just as powerful and fast (modulo the preprocessing) as various extensions studied, including power control, carrier sense, collision detection, free acknowledgements, and geolocation knowledge. Central to these results is an efficient construction of a constant-density backbone structure over the network, which is of independent interest. This is achieved using an indirect sensing technique, where message non-reception is used to deduce information about relative node-distances.

Analysis of spectral efficiency for OFDM cooperative cognitive networks with non‐linear relay

This paper analyzes the downlink achievable spectral efficiency of an orthogonal frequency-division multiplexing (OFDM) cooperative cognitive network with a non-linear relay. The analysis is carried out subject to the power amplifier's (PA) non-linear effect on the relay node which operates in the amplify-and-forward (AF) mode. Specifically, an analytical expression for the power spectral density (PSD) of relay output in terms of its source power is derived. By using the obtained PSD, the power of relay's PA output is derived for each subcarrier and the 1 dB compression point is determined. Then, the adjacent channel power (ACP) of each subcarrier is analytically derived in terms of secondary user (SU) source input power. Next, the signal to interference and noise ratio (SINR) of each subcarrier at destination (SU receiver) is calculated by considering the non-linear effect of PA at the relay. Having the SINRs of all subcarriers, a constrained optimization problem on the source's input power is formulated in which the achievable spectral efficiency is the objective function and all ACPs being less than the interference temperature limit are its constraints. Finally, we perform some simulations and show that the numerical results are consistent with the analytical findings.

Investigation of Ideal Number User Terminals with Spectrum Efficiency in Next Generation Wireless Communication Systems

Suppose that a multi-user multiple-input multiple-output (MIMO) system is developed from scratch to equally envelop a defined region with optimal spectrum efficiency (SE) in next generation wireless communication systems such as sixth-generation (6G) and beyond networks. What are the ideal number of user terminals U, number of base stations antennas, and used pilot reuse factor? The purpose of this paper is to address this specific issue. Three interference levels are specified for this. Based on these interference levels, signal-to-interference-and-noise ratios (SINRs) are extracted. Closed-form spectrum efficiency equations are thus obtained. As a function of the base station (BS) antenna number, simulations are carried out considering multiple pilot reuse factors and diverse processing schemes such as Maximum Ratio Combining (MRC) and Zero-Forcing (ZF). From the results, it is understood that U varies according to the processing schemes. Therefore, evaluating the results considering the fixed number of users K will not give an accurate result in determining the design parameters for the next generation communication systems. In general, these results are useful statements that spectrum efficiency is maximized when the ideal number of users U is used in multi-cell systems.

Parametric matched filter based on interference iteration

In this paper, an iteration algorithm based on interference iteration is proposed and referred to as I-PMF. Derived from the parametric matched filter (PMF), I-PMF has a low computational cost and reveals not only an iteration relationship between the autoregressive (AR) coefficient matrices and interferences in mathematics, but also a mechanism for PMF in suppressing interferences. Then the iteration of I-PMF is utilized in an adaptive method, namely I-PAMF. The average minimum output signal-to-interference-and-noise ratio (SINR) of I-PAMF is analyzed with separated interferences and verified by numerical results. It is shown that the computational cost of the proposed iterative algorithm, i.e. I-PMF, is low and the detection performance of the proposed adaptive iterative algorithm, i.e. I-PAMF, outperforms most of its counterparts with small training size. Although there might be a small loss of detection performance for I-PAMF compared with a few of its counterparts in some cases, I-PAMF still has a much lower computational cost than these counterparts.

On Constructing t‐Spanner in IoT under SINR

Following the recent advances in the Internet of Things (IoT), it is drawing lots of attention to design distributed algorithms for various network optimization problems under the SINR (Signal‐to‐Interference‐and‐Noise‐Ratio) interference model, such as spanner construction. Since a spanner can maintain a linear number of links while still preserving efficient routes for any pair of nodes in wireless networks, it is important to design distributed algorithms for spanners. Given a constant t > 1 as the required stretch factor, the problem of our concern is to design an efficient distributed algorithm to construct a t‐spanner of the communication graph under SINR such that the delay for the task completion is minimized, where the delay is the time interval between the time slot that the first node commences its operation to the time slot that all the nodes finish their task of constructing the t‐spanner. Our main contributions include four aspects. First, we propose a proximity range and proximity independent set (PISet) to increase the number of nodes transmitting successfully at the same time in order to reduce the delay. Second, we develop a distributed randomized algorithm SINR‐Spanner to construct a required t‐spanner with high probability. Third, the approximation ratio of SINR‐Spanner is proven to be a constant. Finally, extensive simulations are carried out to verify the effectiveness and efficiency of our proposed algorithm.

Multi-Aperture Space-Time Transmit and Receive Design for MIMO Radar

We consider the joint transmit and receive design for multi-input multi-output radar with slow-time processing. The radar employs multiple transmit apertures to improve diversity. The design parameters include the spatial transmit code for each aperture, which varies from pulse to pulse to provide Doppler shaping, and the space-time receive filter, to jointly optimize the radar output signal-to-interference-and-noise ratio (SINR). To relieve the dependence on specific target parameters as required by some prior methods, we use the average SINR, averaged with respect to the target location/Doppler uncertainties, as the design metric. Simulation results show that our proposed multi-aperture solution outperforms a previous single-aperture based space-time transmit and receive design as well as the conventional phased-array radar.

Beam-Domain Anti-Jamming Transmission for Downlink Massive MIMO Systems: A Stackelberg Game Perspective

In this paper, beam-domain (BD) anti-jamming transmission in a downlink massive multiple-input multiple-output (MIMO) system is investigated. A smart jammer with multiple antennas attempts to interfere with the signal reception of users with the desired energy efficiency (EE), whereas a base station (BS) tries to minimize the transmission cost while ensuring uninterrupted communication. A Bayesian Stackelberg game between the BS and jammer, where the jammer is the follower and the BS acts as the leader, is modeled. In the follower subgame, the optimal jamming precoding with a closed-form power solution is introduced. The optimal jamming power is proportional to the transmission power in the downlink, and thus, for the BS, the strategy of suppressing malicious attacks by increasing the transmission power fails. In the leader subgame, generalized zero-forcing (ZF), whose closed-form power solution constitutes the unique Stackelberg equilibrium (SE) with that of the jammer, is found to be the optimal anti-jamming precoding for robust transmission. The results show that there always exists a precoding solution for the BS that ensures reliable transmission when the SE is obtained. A proper increase in the minimum signal-to-interference-and-noise ratio (SINR) threshold or the BD channel approximation error helps the BS save power during the resistance against the jammer. Then, a simplified power solution without the instantaneous channel state information (CSI) of jamming channels is further introduced for practical implementation. Numerical results are provided to verify the proposed solutions.

Radar Waveform Design Under Communication Sum Capacity Constraint

This paper considers a joint radar and wireless communication systems where the radar transmit waveform is adaptively designed. To ensure acceptable performance of both radar and communication systems operating in the same frequency bands, the radar makes use of knowledge provided by the communication systems and vice versa. Specifically, the radar transmit waveform is designed not only to maximize radar performance such as signal-to-interference-and-noise ratio (SINR) but also to guarantee acceptable communication systems performance by ensuring a prescribed total throughput or sum capacity of communication systems. We formulate an optimization problem that maximizes the radar performance subject to the radar power constraint and the communication sum capacity constraint. Since the sum capacity constraint is not a convex constraint, the resulting optimization problem is not convex. We provide a geometric analysis of the sum capacity constraint and the solution of the SINR maximization problem in two steps: 1) obtain the optimal solution with only radar power constraints, i.e., without the sum capacity constraint, and then 2) starting from the optimal solution of the first step, find a solution satisfying the sum capacity constraint. In this process, a closed form solution to find the locally optimal point at each search is derived, which reduces computational complexity of the proposed algorithm. Numerical results are provided to verify performance of the proposed method.

Spectral and Energy Efficiency for Large-Scale Multiple-Input-Multiple-Output Two-Way Hybrid Relaying With Multi-Pair Users Under Imperfect Channel State Information

Herein, we investigate the system spectral efficiency (SSE) and system energy efficiency (SEE) for massive two-way multiple-input-multiple-output (MIMO) relaying networks while considering imperfect channel state information (CSI) with $K$ -pair users in the presence of the hybrid relaying processing. First, we obtain the general expression of the signal-to-interference-and-noise-ratio (SINR) for the considered system when the antenna number of the relay station (RS) $M$ tends to be significantly large. Next, we consider the power scaling scheme (PSS) and achieve asymptotic SSE and SEE. We set the pilot sequence transmit power $P_{P}$ to be fixed $P_{P}$ and variable $P_{P}$ . For a nonvanishing SINR, we achieve different power scaling cases under fixed and variable $P_{P}$ . For a fixed $P_{P}$ value, the optimal PSS of the SSE can be obtained when the transmit power of each user can be scaled by $M$ , whereas that of the SEE can be achieved when the transmit power of both the RS and each user terminal can be reduced by $M$ . Based on the variable value of $P_{P}$ , the optimal PSS’ of both the SSE and the SEE can be used when the transmit power of both RS and each user can be scaled by $M^{1/3}$ . Thus, we conclude that the required SSE and SEE performances can be attained in multi-pair massive MIMO two-way relaying networks with a considerably low transmit power at RS and/or the transmit power of each user. The analytical results for the same are validated via simulation.

Constant Envelope Precoding With Extended Degrees of Freedom Through Per-User Symbol Scaling

In this letter, we propose a novel constant envelope precoding (CEP) design for multi-user multi-input single-output (MU-MISO) downlink, where we exploit the extra degrees of freedom (DoFs) by allowing individual rotation and scaling for each constellation point. By jointly optimizing the transmitting signal matrix and the complex scaling factors, the signal-to-interference-and-noise-ratio (SINR) at the receiver is maximized. The formulated optimization problem is divided into two sub-problems and solved by the alternating optimization approach. We further propose a simplified gradient descent algorithm and extend our algorithm to frame-level precoding design. Simulation results show that the proposed algorithms outperform the existing CEP algorithms in terms of both symbol error rate (SER) and computational complexity.