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

Impact of different receiver geometries on a reconfigurable intelligent surface assisted multi-cell VLC system in the presence of light path blockage.

We report the effect of integrating metasurface-aided reconfigurable intelligent surfaces (RISs) on the signal-to-interference-plus-noise ratio (SINR) and data rate of a multi-cell visible light communication (VLC) system. RIS has been deployed in the channel between transmitter and receiver to redirect the reflected light in the desired directions, even in the absence of line-of-sight (LoS) links. Results show that the introduction of RIS has improved average SINR but reduced average illumination level compared to a no-RIS system. As the quantity of RIS increases, a discernible improvement in the maximum SINR value is observed. Here, three different receiver geometries, namely, a photodiode (PD), freeform diversity receiver (FDR), and modified FDR (MFDR), have been adopted. The impact of individual receivers has been reported in the presence of light path blockage. MFDR geometry is found to be most suitable with more coverage probability compared to the other two receivers. With (40c m×24c m) RIS area, during blockage, MFDR maintains an average SINR of 21.95dB, which is 97.29% and 14.24% greater than PD and FDR, respectively.

Interference Management Using Distance-based Clustering Method for D2D Communication Underlaying Multicell Cellular Network

Device-to-Device (D2D) communication is a technology candidate to support the next generation of cellular communication networks. D2D has the potential to boost the efficiency of frequency resources and system capacity. Generally, D2D performs in-band underlaying or shares frequency channels with traditional cellular users, which can cause co-channel interference problems between these two types of users. This paper offers a solution through a clustering technique for D2D users (DUEs) to reduce interference among DUEs. Clustering technique is performed on DUEs by allocating different frequency channels in a group, in order to reduce the interference effects experienced. Thus, it is expected that through this proposed method, both D2D and cellular users can experience better signal quality with minimal interference effects. Two systems have been considered i.e., the conventional/baseline system and the system with the proposed clustering method. The simulation results show that the SINR (Signal to Interference plus Noise Ratio) values and throughput for the proposed system compared to the baseline system has increased. The SINR result obtained is 16.8 dB for the baseline system and 17.68 dB for the proposed system, and resulting an improvement of 5.4%. Therefore, applying the proposed clustering method is able to increase acceptability of the desired signals for the observed DUEs. Then, the throughput value also increases by 5%, i.e., from 56.17 to 59 Mbps, which the system with the proposed clustering method provides a better increase in data transmission speed compared to the baseline system.

Dynamic Coverage Optimization for 5G Ultra-dense Cellular Networks Based on Their User Densities

This paper has proposed a user-density-based coverage optimization technique for ultra-dense cellular networks. Antenna tilting is a promising coverage optimization technique to be used in 5G networks, that significantly improve the signal to interference plus noise ratio (SINR) by choosing the appropriate angle of tilt. In this paper, the cellular coverage has been optimized for scattered user densities/user hotspots using an adaptive antenna tilting mechanism that steers the beams towards the temporal hot spot in the coverage area. The proposed method has the competence to improve the desired SINR level and coverage area for a group of users rather than a single user. In this work, a reinforcement learning (RL) algorithm has been implemented to optimize the tilt angle. The performance of the proposed technique has been evaluated in the simulation platform considering a three-sectored multicellular mobile network where the groups of user clusters are distributed randomly. The result confirms the improvement in RSS and SINR values in the group of users having high density with maximum user satisfaction.

MIMO Radar Design for Extended Target Detection in a Spectrally Crowded Environment

Multiple-input multiple-output (MIMO) radar design for extended targets in a spectrally crowded environment is a challenge owing to the high sensitivity of the target impulse response (TIR) and the increasing requests for spectrum. Assuming unknown TIR, this paper proposes a joint design method to optimize the transmit waveforms and receive filter bank in MIMO structure ensuring spectral compatibility with the overlayed radiators. A priori information is used to impose a spectral constraint on the waveforms, which is the result of a non-convex optimization problem aimed at enhancing the average signal-to-interference-plus-noise-ratio (SINR) over a finite uncertainty set for the TIR. The new method realizes an improved spectral cohabitation with the surrounding radiators through an appropriate modulation of the transmitted energy. In addition, we develop an iterative optimization algorithm which successively enhances the average SINR. Each iteration of the algorithm involves a hidden convex problem, which can be solved resorting to the rank-one decomposition procedure. Finally, the performance is assessed by studying the trade-off among the achieved SINR and spectral shape. The reported results are presented to analyze the performance of the devised method against several counterparts in terms of the SINR value and robustness.

A Fair SINR Performance Comparison of FBMC/OQAM and FBMC/QAM Multicarrier Communication Systems in the Discrete-Time Framework

In the last couple of decades, multicarrier modulations have witnessed a considerable interest in wireless communication networks due to their ability to fight against multipath fading and offer multiple access with flexible resource sharing. One of the well known multicarrier modulation systems is filter-bank multi-carrier with an offset quadrature amplitude modulation (FBMC/OQAM), which was proposed as a powerful solution during the standardization of 5G. In this paper, we derive a closed-form expression of the signal to interference plus noise ratio (SINR) for FBMC/OQAM systems in the discrete-time context, for arbitrary wide sense stationary uncorrelated scattering (WSSUS) channels as well as transmitter (Tx) and receiver (Rx) waveforms. We quantify the potential gains in SINR brought by FBMC/OQAM, which exclusively operates on critical lattice density, with respect to FBMC/QAM, which have the flexibility to operate on critical or non-critical lattice densities. For completeness, we compare the performance of FBMC/OQAM in the discrete-time context, sweeping the discrete space of waveforms supports, with that of FBMC/OQAM in the continuous-time context, using the Hermite functions, and show how they perform similarly. Simulation results prove that FBMC/OQAM optimization algorithm, performing with the ping-pong optimized pulse shaping (POPS) paradigm, converges rapidly to excellent SINR values, even with small supports durations, in discrete-time context, which is equivalent to a reduced number of Hermite functions, in the continuous-time context.

Relay-Based Clustering Method for Interference Management in Heterogeneous Wireless Cellular Network

Femtocell is one of solutions to improve quality of services and network capacity for users in indoor areas. Radio resources used by femtocells are shared from macrocell network, thus it saves the use of frequency spectrum. However, one of problems in deploying femtocells within coverage area of macrocells is interference due to radio resources sharing between femtocells and macrocells. It creates interferences called as cross-tier (macrocell-femtocell/femtocell-macrocell) and co-tier (macrocell-macrocell/femtocell-femtocell) interferences. This paper proposes a relay-based clustering method to mitigate interference in femtocells located in the whole edge area of macrocell and the cell edge area of sectorized macrocells. Relay nodes are deployed statically (fixed location) in the neighboring macrocell area. Relay node will recruit their members based on the shortest distance. Certain relay node’s members do not need to transmit large amounts of power to enhanced Node B (eNB), such that interference from Macrocell User Equipment (MUE) to Home enhanced Node B (HeNB) can be minimized. Simulation experiments has been carried out and optimistic results for the sectorized macrocells scenario show that Signal-to-Interference-plus-Noise-Ratio (SINR) of femtocells for the conventional system that does not reach the targeted SINR of 20 dB is 87%. Meanwhile, after applying the relay-based clustering method, SINR value of femtocells below or equal to 20 dB reaches 72%. Optimistic results for throughput and Bit Error Rate (BER) show improvement of 15% and 14%, respectively. It has been shown that the relay-based clustering method can provide better performance compared to the conventional system even for femtocells densely deployed.

Seamless connectivity with 5G enabled unmanned aerial vehicles base stations using machine programming approach

AbstractDeployment of a small unmanned aerial vehicle (UAV) mounted 5G base station is a promising solution for providing seamless network connectivity to users in a modern, data‐centric thrust areas. The key challenge is to find the location, the height and the optimum number of mounts. A machine programming based approach is proposed here for optimal placement of UAV‐mounted base station. The location of the deployment is determined using three clustering algorithms such as K‐means, K‐medoids, and fuzzy cluster means. Different sets of UAV‐mounted base stations have been deployed with variable user density at different heights. The impact on the network performance has been quantified through measurements of received power, signal to interference plus noise ratio (SINR), and path loss per active user equipment (UEs). To gain further insights, a scenario where UEs are connected only to the terrestrial base station, that is, the network is devoid of any sort of UAV mounted base station is evaluated. Numerical computations reaffirm that the proposed technique reduces the average path loss of the active UEs. Moreover, the use of height‐mounted base station also alleviates the issues arising due to low SINR values. The said technique shows immense potential in terms of seamless connectivity to end users in events of emergency and remote deployment scenarios, where ground‐based base station is not possible. The big transition of on‐ demand connectivity for 5G networks shall be benefitted from purpose‐built UAV infrastructure with specific locations or areas in mind.

An efficient adaptive modulation technique over realistic wireless communication channels based on distance and SINR

Abstract A growing trend has been observed in recent research in wireless communication systems. However, several limitations still exist, such as packet loss, limited bandwidth and inefficient use of available bandwidth that needs further investigation and research. In light of the above limitations, this paper uses adaptive modulation under various parameters, such as signal to interference plus noise ratio (SINR), and communication channel’s distances. The primary goal is to minimize bit error rate (BER), improve throughput and utilize the available bandwidth efficiently. Additionally, the impact of Additive White Gaussian Noise (AWGN), Rayleigh and Rician fading channels on the performance of various modulation schemes are also studied. The simulation results demonstrate that our proposed technique optimally improves the BER and spectral efficiency in the long-range communication as compared to the fixed modulation schemes under the co-channel interference of surrounding base stations. The results indicate that the performance of fixed modulation schemes is suitable only either at high SINR and low distance or at low SINR and high distance values. Moreover, on the other hand, its performance was suboptimal in the entire wireless communication channel due to high distortion and attenuation. Lastly, we also noted that BER performance in the AWGN channel is better than Rayleigh and Rician channels with Rayleigh channel exhibiting poor performance than the Rician channel.

An Asynchronous Anycast Cross-layer Protocol for WSN Suited to Noisy Environments

This paper presents AGA-MAC+: an asynchronous anycast protocol for wireless sensor networks. Latency is a problem for asynchronous MAC due to sleep-delay, since each relay must wait for the receiver to wake-up. Our protocol employs anycast communication to mitigate the one-hop-delay, selecting a group of neighboring nodes (Forwarding Candidate Set—FCS) as possible next hop. The first FCS member to wake up becomes the next relay, reducing latency. This new protocol is an improvement over AGA-MAC, our previous work, which considers data size to determine the number of FCS members. For large packets, small FCS leads to lower latency, whereas the reverse is true for small packets. This work expands this model, considering the quality of communication channels in FCS selection. In order to receive an error-free data packet with a given probability, nodes with a minimum signal-to-interference-plus-noise ratio (SINR) can take part in FCS. The performance of our protocol was evaluated using GrubiX Simulator, considering an environment with noise and interference. AGA-MAC+ was compared with two other well-known protocols, for different packet sizes and SINR values. Comparing energy spent in the communication process, AGA-MAC+ presented a performance gain of at least 5%, in 88% of the cases. When latency is assessed, AGA-MAC+ outperforms both protocols for all scenarios, presenting an improvement of at least 18% in 83% of the tests.

Orthogonal Chirp-Division Multiplexing for Power Line Sensing via Time-Domain Reflectometry

In this study, a time-domain reflectometry (TDR) system based on a baseband version of the orthogonal chirp-division multiplexing (OCDM) scheme, which is relies on a modified discrete Fresnel transform (DFnT), is proposed for power line sensing. After a detailed description of the system model, a multiple access scheme that exploits the contolution theorem of the modified DFnT for enabling distributed reflectometric and transferometric sensing of the monitored power line. Considering typical European underground low-voltage and US overhead medium-voltage (MV) power distribution networks, range resolution and maximum unambiguous range for the measurements are assessed for the proposed scheme. Next, a comparison with multiple access schemes based on the Hermitian symmetric orthogonal frequency-division multiplexing (HS-OFDM) discussed in a previous work is performed considering a Brazilian MV overhead scenario, being the number of measurements obtained over time, as well as signal-to-interference-plus-noise ratio (SINR) used as performance metrics. The attained results show that the proposed multiple access scheme results in the same range resolution as the others. Also, the highest number of measurements over time is obtained by the proposed scheme, which produces orthogonality among signals transmitted by different power line modems (PLMs) neither and time nor frequency domains, but rather in the Fresnel domain. Meanwhile, although its yielded SINR values are fair among the PLMs consisting the distributed sensing system, the proposed scheme is slightly outperformed by the HS-OFDM based on code-division multiple access and by the HS-OFDM based on frequency-division multiple access at some PLMs.

Phase-Only Space-Time Adaptive Processing

Space-time adaptive processing (STAP) is a well-known and effective method to detect targets, obscured by interference, from airborne radars that works by coherently combining signals from a phased antenna array (spatial domain) with multiple radar pulses (temporal domain). As widely demonstrated, optimum STAP, in the sense of maximizing the output signal to interference plus noise ratio (SINR), is a coherent, linear, transversal filter (i.e., tapped delay line), that can be synthesized by a complex-valued weight vector. This paper extends previous work that focused on adaptive spatial-only nulling; it derives the optimum phase-only STAP, namely, the optimal weight vector that maximizes the SINR subject to the constraint it belongs to the $N$ -torus of phase-only complex vectors, where $N$ is the number of spatio-temporal degrees of freedom. Because this problem does not admit a closed-form solution, it is solved numerically using the phase-only conjugate gradient method (CGM). The effectiveness of phase-only STAP is demonstrated using both SINR values and receiving beampattern shape, comparing it with the optimum fully-adapted STAP and the nonadapted beam former responses as well as other possible counterparts. Additionally, several analyses of practical utility also demonstrate the benefits provided by phase-only STAP.

Information-Theoretic Radar Waveform Design under the SINR Constraint.

This study investigates the information–theoretic waveform design problem to improve radar performance in the presence of signal-dependent clutter environments. The goal was to study the waveform energy allocation strategies and provide guidance for radar waveform design through the trade-off relationship between the information theory criterion and the signal-to-interference-plus-noise ratio (SINR) criterion. To this end, a model of the constraint relationship among the mutual information (MI), the Kullback–Leibler divergence (KLD), and the SINR is established in the frequency domain. The effects of the SINR value range on maximizing the MI and KLD under the energy constraint are derived. Under the constraints of energy and the SINR, the optimal radar waveform method based on maximizing the MI is proposed for radar estimation, with another method based on maximizing the KLD proposed for radar detection. The maximum MI value range is bounded by SINR and the maximum KLD value range is between 0 and the Jenson–Shannon divergence (J-divergence) value. Simulation results show that under the SINR constraint, the MI-based optimal signal waveform can make full use of the transmitted energy to target information extraction and put the signal energy in the frequency bin where the target spectrum is larger than the clutter spectrum. The KLD-based optimal signal waveform can therefore make full use of the transmitted energy to detect the target and put the signal energy in the frequency bin with the maximum target spectrum.

Subcarrier Wise Scheduling Methods for Multi-antenna and Multi-carrier Systems

In this paper, multiuser scheduling algorithms are evaluated for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) networks. These scheduling schemes allocate M [number of transmit antennas at base station (BS)] number of independent data streams from BS to the M most favourable users experiencing the highest signal-to-interference-plus-noise-ratio (SINR). Here, SINR is used to convey the channel state information (CSI) to the BS. We have investigated the system throughput and feedback overhead attained by these scheduling schemes for different scenarios as: (a) the maximum CSI is sent to the BS by every user and (b) the maximum CSI sent to the BS corresponding to every BS antenna. The overall feedback overhead incurred by MIMO-OFDM system increases linearly with number of users, number of subcarriers and number of transmit antennas. Hence, to reduce the feedback overhead, a scheme is proposed where users with SINR values greater than or equal to a predefined threshold value are only allowed to feedback the channel state information to BS. The relation between system throughput and various thresholds is also studied. The achievable system throughput results are validated by comparing the probability density function of achieved SINR values by different scheduling schemes.

MIMO Radar Transmit–Receive Design for Moving Target Detection in Signal-Dependent Clutter

This paper deals with the joint design of Multiple-Input Multiple-Output (MIMO) Space-Time Transmit Code (STTC) and Space-Time Receive Filter (STRF) to improve the detectability of a moving target embedded in signal-dependent clutter in the presence of uncertainties on the target azimuth angle and Doppler frequency. The Signal to Interference plus Noise Ratio (SINR) is considered as a figure of merit to maximize and multiple restrictions on STTC are forced at the design stage, i.e., similarity and modulus constraints as well as a uniform power requirement among the transmit antennas. To deal with the resulting non-convex design problem, a novel polynomial-time iterative procedure based on Successive Greedy Optimization (SGO) framework ensuring that SINR monotonically increases and converges to a finite value, is developed. Each iteration of the proposed algorithm involves the generalized eigenvalue decomposition to design STRF and a nested iterative technique involving Dinkelbach's procedure and an Alternating Direction Penalty Method (ADPM) to obtain STTC. Numerical results are provided to assess the performance of the proposed algorithm against some counterparts in terms of the optimized SINR value and computational complexity.

Coordinated multicell beamforming and power allocation for massive MIMO: A large system analysis

This paper is concerned with coordinated multicell beamforming and power allocation for downlink massive multiple input and multiple output (MIMO) system. The design objective is to minimize the total transmit power under users’ signal to interference plus noise ratio (SINR) constraints. Another closely related optimization problem is to maximize the minimum of all users’ SINR values under a total power limitation, and we employ the relationship between the two problems to solve the former one. In particular, the power minimization problem can be transformed to a max-min SINR problem with an appropriate power limitation. This power limitation value is found by using the bisection method. Then, the max-min SINR problem is settled by solving a conditional eigenvalue problem. Note that the whole calculation process is done in the asymptotic regime where base station (BS) antenna number and user number both tend to infinity. Simulation results demonstrate that this algorithm is effective, and can achieve the near optimal performance with low complexity.

Signal-dependent interference reduction based on a new transmit covariance matrix and receive filter design for colocated MIMO radar

Waveform design is an important topic in diverse radars, especially MIMO radars. In this paper, the signal-to-interference plus noise ratio (SINR) has been improved using the proposed covariance matrix and filter coefficients in colocated MIMO radars. In the proposed method, transmit waveform covariance matrix and receive filter coefficients have been jointly optimized to make the desired transmit beam pattern to the target direction, reject a maximum number of signal-dependent interfering sources and prepare suitable SINR and degree of freedom (DOF). Simulation results show that the proposed method has appropriate and significant SINR values, DOF and computational time in comparison with other methods. Moreover, the constant and equal power is transmitted through each antenna element in the proposed method and similar elements can be used to design the transmitters. Therefore, the suitable computational time and complexity and also the simple design of transmitters have made the proposed method more practical than other compared methods.

Maximizing First-Order Approximate Mean of SINR Under Imperfect Channel State Information for Throughput Enhancement of MIMO Interference Networks

In this research paper approximate mean of signal-to-interference-plus-noise ratio (SINR) under imperfect channel state information (CSI) is computed and maximized for throughput enhancement of MIMO interference networks. Each transmitter and receiver has respectively M and N antennas and network operates in a time division duplex mode. Each transceiver adjusts its filter to maximize the expected value of SINR. The proposed New Approach for Throughput Enhancement under imperfect CSI utilizes the reciprocity of wireless networks to maximize the estimated mean. The sum rate performance of the proposed algorithm is verified using Monte Carlo simulations.

Filter Bank Multicarrier in Massive MIMO: Analysis and Channel Equalization

We perform an asymptotic study of the performance of filter bank multicarrier (FBMC) in the context of massive multi-input multi-output (MIMO). We show that the effects of channel distortions, i.e., intersymbol interference and intercarrier interference, do not vanish as the base station (BS) array size increases. As a result, the signal-to-interference-plus-noise ratio (SINR) cannot grow unboundedly by increasing the number of BS antennas, and is upper bounded by a certain deterministic value. We show that this phenomenon is a result of the correlation between the multi-antenna combining tap values and the channel impulse responses between the mobile terminals and the BS antennas. To resolve this problem, we introduce an efficient equalization method that removes this correlation, enabling us to achieve arbitrarily large SINR values by increasing the number of BS antennas. We perform a thorough analysis of the proposed system and find analytical expressions for both equalizer coefficients and the respective SINR.

Coexistence of RF-powered IoT and a Primary Wireless Network With Secrecy Guard Zones

This paper studies the secrecy performance of a wireless network (primary network) overlaid with an ambient RF energy harvesting Internet of Things (IoT) network (secondary network). The nodes in the secondary network are assumed to be solely powered by ambient RF energy harvested from the transmissions of the primary network. We assume that the secondary nodes can eavesdrop on the primary transmissions due to which the primary network uses secrecy guard zones . The primary transmitter goes silent if any secondary receiver is detected within its guard zone. Using tools from stochastic geometry, we derive the probability of successful connection of the primary network as well as the probability of secure communication. Two conditions must be jointly satisfied in order to ensure successful connection: 1) the signal-to-interference-plus-noise ratio (SINR) at the primary receiver is above a predefined threshold, and 2) the primary transmitter is not silent. In order to ensure secure communication, the SINR value at each of the secondary nodes should be less than a predefined threshold. Clearly, when more secondary nodes are deployed, more primary transmitters will remain silent for a given guard zone radius, which will in turn impact the amount of energy harvested by the secondary network. Our results concretely show the existence of an optimal deployment density for the secondary network that maximizes the density of nodes that are able to harvest sufficient amount of energy. Furthermore, we show the dependence of this optimal deployment density on the guard zone radius of the primary network. In addition, we show that the optimal guard zone radius selected by the primary network is a function of the deployment density of the secondary network. This interesting coupling between the performance of the two networks is studied using tools from game theory. We propose an algorithm that can assist the two networks to converge to Nash equilibrium. The convergence of this algorithm is verified using simulations. Overall, this paper is one of the few concrete works that symbiotically merge tools from stochastic geometry and game theory.

Downlink Resource Allocation Under Time-Varying Interference: Fairness and Throughput Optimality

We address the problem of downlink resource allocation in the presence of time-varying interference. We consider a scenario where users served by a base station face interference from a neighboring base station. We model the interference from the neighboring base station as an ON/OFF renewal process, that arises due to its idle and busy cycles. The users feedback their downlink signal to interference plus noise ratio (SINR) values to their base station, but these values are outdated. In this setting, we characterize how the resource allocation layer can optimally exploit the reported SINR values, which could be unreliable due to time-varying interference. In particular, we propose resource allocation policies in two well-known paradigms. First, we address the problem of $\alpha $ –fair scheduling, and propose a policy that ensures asymptotic convergence to the optimal $\alpha $ –fair throughput. Second, we propose a throughput optimal resource allocation policy, i.e., a policy that can stably support the largest possible set of traffic rates under the interference scenario considered. Estimating the outage probability from the outdated SINR values plays an important role in both scheduling paradigms, and we accomplish this using tool from renewal theory.