Signal Interference Noise Ratio Research Articles

Resource Allocation Based on SFLA Algorithm for D2D Multicast Communications

Multicast device-to-device (D2D) communication technology is considered as one of the new technologies in the fifth generation (5G) networks that directly addresses the need for content sharing among internet users. In fact, when direct communication is available between devices, the spectral efficiency is improved by reusing the licensed cellular spectrum. The current studies show that D2D communication increases network capacity and reduces latency. In order to achieve the alternate capabilities, coordination is required to implement interference management. We considered subcarrier allocation for the uplink, in addition to the power control that takes place on the underlay network. The completed data rate in single multicast communication is significantly reduced and limited by nodes with lower channel quality. In this paper, we used Shuffled Frog Leaping Algorithm (SFLA) for resource allocation (RA) in D2D multicast communications. We compared the results of the SFLA algorithm with the Firefly Algorithm (FA), Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO); in terms of D2D user throughput, Cellular User (CU) throughput, network average throughput, network interference and signal interference noise ratio (SINR) target. The simulation results show that SFLA clearly outperforms other algorithms in terms of data rate under the high pressure of infeasibility.

Location Mechanism and Perception Scheme of Remote Transmission Equipment Layout in Smart Water.

Whether the traditional water equipment is equipped with remote transmission unit depends on whether the power consumption of the installed equipment can meet the expected life cycle. In the paper, by using intelligent strategies to save the power consumption of sending data, more sites can be selected to install remote transmitting units. In the process of transmitting data packet sequence, the remote transmission device needs to perceive the environment, interact with the environment and make decisions, and adjust the strategy according to the effect of the decision actions. Therefore, in this paper, the transmission process is modeled as Markov sequence decision model. And the real time signal interference noise ratio of the channel and the transmission delay of the data packet are defined as the state space. The decision action space consists of immediate transmission and delayed one, and the minimum total power consumption is taken as the objective function. The model is solved by Proximal Policy Optimization (PPO) algorithm, and the optimal decision sequence of site selection threshold is obtained.

On Secrecy Performance of SWIPT Energy-Harvesting Relay Jamming Based Mixed RF-FSO Systems

This paper proposes a simultaneous wireless information and power transfer (SWIPT) energy-harvesting relay jamming based mixed RF/FSO system, and studies its security performance optimization in the presence of an eavesdropper. In this work, the RF and FSO channels experience Nakagami-m fading distribution and Málaga(M) turbulence, respectively. A two-hop decode-and-forward (DF) relay is presented in the system, and the effect of pointing errors is considered. The presence of a nearby single antenna eavesdropper that attempts to eavesdrop on the transmission is also modeled. In order to prevent eavesdropping, the relay introduces the SWIPT structure to control information delivery and wireless energy recharging. The closed expressions of secrecy outage probability (SOP) and average secrecy capacity (ASC) of the mixed RF/FSO system are derived for the above system model. In addition, the closed-form expression of the asymptotic results for SOP and ASC are derived when signal-to-noise ratios at relay and legitimate destinations tend to infinity. The correctness of these expressions is verified using the Monte Carlo method. The influence of various key factors on the safety performance of the system is analyzed by simulations. The results show that the safety performance of the system is considerably improved under good weather conditions as well as by increasing the signal-interference noise ratio, number of interferer antennas, power distribution factor and energy conversion efficiency. This study provides a new system structure and a good theoretical basis for evaluating the physical layer security performance of the mixed RF/FSO system.

Precoder and Decoder Co-Designs for Radar and Communication Spectrum Sharing.

The coexistence of radar and communication systems is necessary to facilitate new wireless systems and services due to the shortage of the useful radio spectrum. Moreover, changes in spectrum regulation will be introduced in which the spectrum is allocated in larger chunks and different radio systems need to share the spectrum. For example, 5G NR, LTE and Wi-Fi systems have to share the spectrum with S-band radars. Managing interference is a key task in coexistence scenarios. Cognitive radio and radar technologies facilitate using the spectrum in a flexible manner and sharing channel awareness between the two subsystems. In this paper, we propose a nullspace-based joint precoder–decoder design for coexisting multicarrier radar and multiuser multicarrier communication systems. The maximizing signal interference noise ratio (max-SINR) criterion and interference alignment (IA) constraints are employed in finding the precoder and decoder. By taking advantage of IA theory, a maximum degree of freedom upper bound for the -radar-communication-user interference channel can be achieved. Our simulation studies demonstrate that interference can be practically fully canceled in both communication and radar systems. This leads to improved detection performance in radar and a higher rate in communication subsystems. A significant performance gain over a nullspace-based precoder-only design is also obtained.

Performance Evaluation of Downlink Coordinated Multipoint Joint Transmission under Heavy IoT Traffic Load

Emerging 5G network cellular promotes key empowering techniques for pervasive IoT. Evolving 5G-IoT scenarios and basic services like reality augmented, high dense streaming of videos, unmanned vehicles, e-health, and intelligent environments services have a pervasive existence now. These services generate heavy loads and need high capacity, bandwidth, data rate, throughput, and low latency. Taking all these requirements into consideration, internet of things (IoT) networks have provided global transformation in the context of big data innovation and bring many problematic issues in terms of uplink and downlink (DL) connectivity and traffic load. These comprise coordinated multipoint processing (CoMP), carriers’ aggregation (CA), joint transmissions (JTs), massive multi-inputs multi-outputs (MIMO), machine-type communications, centralized radios access networks (CRAN), and many others. CoMP is one of the most significant technical enhancements added to release 11 that can be implemented in heterogonous networks implementation approaches and the homogenous networks’ topologies. However, in a massive 5G-IoT device scenario with heavy traffic load, most cell edge IoT users are severely suffering from intercell interference (ICI), where the users have poor signal, lower data rates, and limited QoS. This work is aimed at addressing this problematic issue by proposing two types of DL-JT-CoMP techniques in 5G-IoT that are compliant with release 18. Downlink JT-CoMP with two homogeneous network CoMP deployment scenarios is considered and evaluated. The scenarios used are IoT intrasite and intersite CoMP, which performance evaluated using downlink system-level simulator for long-term evolution-advanced (LTE-A) and 5G. Numerical simulation scenarios were results under high dense scenario—with IoT heavy traffic load which shows that intersite CoMP has better empirical cumulative distribution function (ECDF) of average UE throughput than intrasite CoMP approximately 4%, inter-site CoMP has better ECDF of average user entity (UE) spectral efficiency than intrasite CoMP almost 10%, and intersite CoMP has approximately same ECDF of average signal interference noise ratio (SINR) as intrasite CoMP and intersite CoMP has better fairness index than intrasite CoMP by 5%. The fairness index decreases when the users’ number increase since the competition among users is higher.

Large deviations and information theory for sub-critical signal-to-interference-plus-noise ratio random network models

The article obtains large deviation asymptotic for sub-critical communication networks modelled as signal-interference-noise-ratio(SINR) random networks. To achieve this, we define the empirical power measure and the empirical connectivity measure, as well as prove joint large deviation principles(LDPs) for the two empirical measures on two different scales. Using the joint LDPs, we prove an asymptotic equipartition property(AEP) for wireless telecommunication networks modelled as the subcritical SINR random networks. Further, we prove a local large deviation principle(LLDP) for the sub-critical SINR random network. From the LLDPs, we prove the large deviation principle, and a classical McMillan Theorem for the stochastic SINR model processes. Note that, the LDPs for the empirical measures of this stochastic SINR random network model were derived on spaces of measures equipped with the τ- topology, and the LLDPs were deduced in the space of SINR model process without any topological limitations. We motivate the study by describing a possible anomaly detection test for SINR random networks.

Large deviations, asymptotic equipartition property for super-critical SINR random networks

In this article, we obtain large deviation asymptotic for supercritical social or communication networks modelled as signal-interference-noise ratio (SINR) graphs. To do this, we define the empirical power measure and the empirical connectivity measure, and prove joint large deviation principles (LDPs) for the two empirical measures on two different scales, i.e. λ and λ 2 aλ , where λ is the intensity measure of the Poisson point process (PPP) which defines the SINR random network and aλ real-valued sequence such that λ 2 aλ → ∞ as λ → ∞Using these joint LDPs we prove an asymptotic equipartition property for the super-critical networks modelled as the SINR random networks. Furthermore, we prove a local large deviation principle (LLDP) for the SINR random network. From the LLDP we prove a large deviation principle, and a classical McMillian theorem for the SINR random network processes. Note that, for a given empirical power measure and typical empirical connectivity measure, qπ ⊗ π, we can deduce from the LLDP a bound on the cardinality of the space of SINR networks to be approximately equal to , where the connectivity probability of the network, , satisfies and qπ ⊗ π is the typical behavior of the empirical connectivity measure. Observe, the LDPs for the empirical measures of SINR random networks were obtained on spaces of measures equipped with the τ-topology, and the LLDPs were obtained in the space of SINR network process without any topological restrictions.

Evaluation of Compact Boundary of Outage Probability in HetNet

In this paper, we investigate the outage probability of per-tier in heterogeneous networks (HetNet) in the presence of aggregated interference from coexisting ad hoc networks. In ad hoc networks, a receiving node suffers the cross-tier interference signal from cellular cell and aggregated interference signal from other transmitting nodes. In order to evaluate the effect of cross-tier interference on the outage probability of ad hoc networks, we analyze the restricted region in cellular cell that the received signal interference noise ratio (SINR) of a receiving node does not exceed the SINR threshold considering the path loss model. Further, to evaluate the effect of aggregated interference of ad hoc networks, we divide the plane area into near-field area and far-field area according to whether the signal of a transmitting node could cause an outage independently or not. Based on this division, we derive the compact lower and upper boundaries of outage probability of per-tier. The computer simulations validate the results of theoretical analysis and show the effect of different factors, such as transmit power, intensity of ad hoc nodes, on the outage probability.

MBSR: MIMO Based Sink Relocation for Path Selection in IoT Based WSN

Wireless Sensor Networks have extended its functionalities by integrating with the Internet of Things and are highly proficient when it is incorporated with other technologies. This demands communication with lesser energy consumption and one such idea of low energy consumption is low energy path selection by a mobile sink node. Path selection requires a good Signal Interference Noise Ratio (SINR) which is calculated for the positioned mobile sink. Thus, a high-quality transmission path is selected by choosing a path to obtain better SINR. MBSR algorithm considers hierarchical clustering schemes and heads are elected to monitor the network. Heads of the clusters communicate to IoT applications using Multiple Input and Multiple Output Dual Antennas. The proposed MBSR scheme utilizes a path optimization technique and finds a suitable path to establish links to end user and real-time environments. The proposed MBSR mechanism employs three phases of execution. Phase 1: Cluster Creation, Phase 2: SINR Analysis for Path Selection. Phase 3: Data transmission to MIMO Devices and in turn forwards to static sinks that connect to end-user using the internet. MBSR improves transmission quality and the proposed scheme is tested for various network parameters to check transmission quality and is compared with existing methodologies.

Evolutionary Multi-Objective Optimization Algorithm for Resource Allocation Using Deep Neural Network in 5G Multi-User Massive MIMO

ABSTRACT 5G network plays a vital role in each field. Recently, the number of 5G users are increasing due to their vast merits. But, these users require various resources to operate effectively. Recently, the machine learning approaches are introduced within this 5G network field for attaining better accuracy and reliability during resource allocation. In this work, the resource allocation for multi-users in 5G massive-MIMO (mMIMO) is performed by a deep neural network (DNN). Initially, the objective functions are optimised by Multi-objective Sine Cosine algorithm (MOSCA). The objective functions applied in this optimisation method are data rate, signal-interference noise ratio (SINR), power consumption, and energy efficiency (EE). Next, these optimised objective functions are allocated to the neural network for resource allocation. DNN identifies the requirement level of each user. Based on this level, it allocates the resource to each user by maintaining high throughput and EE. Further, the fairness index for this neural network-based resource allocation process is also identified. The throughput and fairness index of the proposed method for 30 users are 275 bps, and 0.92%, respectively. The outcomes of this proposed method show that this method provides better performance in 5G mMIMO than other existing methods.

BER analysis using zero-forcing linear precoding scheme for massive MIMO under imperfect channel state information

ABSTRACTIn massive MIMO systems, inter-user interference has effect on the transmitted signals, so linear precoding techniques are employed for multiuser transmission channels to remove this inter-user interference. It is very complicated to design a suitable linear precoding technique having low computational complexity, which will give an excellent Bit Error Rate (BER) performance. In this paper, we analyse BER under imperfect Channel-State-Information (CSI) using Zero-Forcing (ZF) linear precoding scheme in the downlink, massive MIMO in Time-Division-Duplex (TDD) mode. We derive the closed-form expressions for BER that are obtained from the new expressions derived for Signal-Interference-Noise Ratio (SINR), and then analysis with different parameters using numerical and Monte Carlo simulated results is carried out in MATLAB under imperfect CSI. It was found that our theoretical analysis agrees well with the simulated results. In our analysis, BER was observed in most cases to be good when the number of Base Station (BS) antennas is large enough to accommodate the served users, but when the number of users grows up, the BER performance degrades depending on how many BS antennas are capable of handling the additional users. Also, increasing the downlink transmit power was found to improve the performance, but it is not an energy-efficient way for massive MIMO.

Robust waveform design for MIMO–OFDM‐based STAP in the presence of target uncertainty

The issue of robust orthogonal frequency division multiplexing (OFDM) multiple-input multiple-output (MIMO) radar waveform design is investigated here with target uncertainty to enhance the worst-case space-time adaptive processing (STAP) detection performance of MIMO–OFDM radar. Based on the max–min method, the robust waveform optimisation problem is constructed under the criterion of maximising the worst-case output SINR, namely, signal–interference–noise ratio, with constraints of constant modulus and target estimation errors to enhance the robustness of STAP's detection performance to target uncertainty. To handle the obtained non-linear and complicated issue, an approach based on diagonal loading (DL) is presented. By employing DL method, the optimisation issue can be relaxed to semidefinite programming one, and thus it can be tackled very efficiently. When compared with uncorrelated signals, the state-of-the-art robust and non-robust waveform design methods for MIMO–STAP, numerical simulations reveal that the developed approach can enhance the robustness of the detection performance of STAP significantly.

Performance analysis of Low-complexity MVDR beamformer in spherical harmonics domain

Abstract Finite sample size usually has a significant impact on the performance of the minimum variance distortionless response (MVDR) beamformer. Here, statistical analysis of a low-complexity spherical harmonics MVDR (LC-SHMVDR) beamformer is conducted using two unitary matrices. Based on the first unitary matrix, the true covariance matrix becomes block-centrohermitian. This block-centrohermitian property is utilized to obtain the probability distribution function (PDF) of the array output. Then, the PDFs of the estimated covariance matrix and the weight vector become available. After the second unitary transformation, the steering vector and forward-backward (FB) averaged covariance matrix become real-valued. With these exact PDFs, we derive some explicit expressions in terms of the variance of the weight vector, the output signal-interference-noise ratio (SINR) and the mean-square error (MSE) to measure the effects of finite sample and real-valued processing. Compared with the traditional MVDR beamformer, the proposed method requires less computational complexity and performs better as verified by theoretical analysis and simulation results.

Evaluating the effect of mobility speed on the performance of three handover algorithms in long term evolution networks

This work uses NS3 simulation to study the effect of mobility speed on the performance of three handover algorithms in Long Term Evolution (LTE) Networks. A realistic multi-cell LTE network was set up using NS3 simulation software. Mobility models were used to vary the location of the User Equipment (UE), hence triggering handover events across the network. The performance was measured using Signal Interference Noise Ratio (SINR) and number of completed handovers. Result revealed that at a speed between the ranges of 0 – 3 km/h, the Integrative algorithm performed best while at 4 – 60km/h, the performance of the A3RSRP algorithm was the best with an average value of 95dB. Also, at an increased speed within the range of 60 – 120 km/h, the Integrative algorithm had a slightly better performance than the A3RSRP. However, at a speed above 120 km/h, the integrative algorithm performed best with an SINR of 120dB. In terms of completed handovers, the Integrative algorithm had the least number of completed handovers throughout the entire range of considered speeds. Thus, we establish that mobility speed has a significant effect on the performance of handover algorithms.Keywords: LTE handover, LTE UE Speed, Integrative Algorithm, Power Budget Algorithm

Methods of suppressing tow ship noise with a horizontal linear array

Tow ship noise seriously influence the detection and direction of arrival (DOA) estimation performance of towed array. Null steering beamforming(NSBF), inverse beamforming(IBF) and non-data based beam-space transformation(NDBBT) are applied to suppress interference of tow ship in this paper. These methods are evaluated according to the improvement of signal interference noise ratio and DOA estimation precision. Simulation and experimental results show that all three methods can suppress interference of tow ship effectively so as to improve DOA estimation precision. In addition, IBF and NDBBT do better in suppressing interference than NSBF.

Design and simulation of MIMO and massive MIMO for 5G mobile communication system

This study concentrates on the investigation of signal detection by using Zero Forcing (ZF), Minimum Mean Square Error (MMSE) and Beam Forming (BF), for a MIMO and massive MIMO system. Outcomes show that ZF is the modest method for signal detection, though BF gives better Bit Error Rate (BER) performance with some constraints in implementation, but MMSE implementation complexity is reduced by avoiding the matrix inversion in the receiver while sustaining the optimal performance as compared to other conventional methods. For several antennas at the base location, it is too difficult to implement the weight matrix for ZF, still, it is appropriate for BF with the benefit of decent digital signal algorithms. Performance of MIMO and massive MIMO using equalisation is investigated to get the throughput of the system (BER vs. SNR). Results indicate a significant improvement in BER for 16x16 as compared to 4x4, 8x1 and 8x8 antennas at the base station. The other parameters like capacity and Signal Interference Noise Ratio (SINR) are likewise examined for massive MIMO system.

Secure massive MIMO‐enabled full‐duplex 2‐tier heterogeneous networks by exploiting in‐band wireless backhauls

AbstractTo enhance the spectrum efficiency and secrecy performance, by using in‐band full‐duplex (FD) wireless backhaul technique, a secure massive multiple input multiple output (MIMO)–enabled heterogeneous cellular network (HCN) model is presented, where the macro base stations (MBSs) are equipped with massive MIMO antenna array, whereas the small cell base stations (SBSs) and user equipment have the single antenna. The ultradense small cells underlay the macro cells and offload traffic from macro cells. With FD mode, the massive MIMO MBSs and single‐antenna SBSs are responsible, respectively, for the access traffic of macro and small cells as well as the backhaul transmission between MBSs and SBSs over the same time‐frequency resource. The transmissions of macro and small cells are exposed to non‐colluding and passive eavesdroppers that attempt to decode the signals of legitimate users. For such HCN with in‐band wireless backhaul, by modeling the network elements as the independent Possion point processes and using the stochastic geometry, we first investigate the secrecy probabilities of the macro cell downlink and small cell uplink transmissions. At the same time, to achieve a comprehensive view, we also investigate the corresponding signal‐interference‐noise ratio (SINR) coverage performance. The presented numerical results show that when the intensity of user equipment is small relatively, exploiting the in‐band backhaul interference as jamming signals can enhance the secrecy probabilities of both the macro and small cell transmissions so that the in‐band FD backhaul mode outperforms the out‐band FD one. However, for the SINR coverage, the opposite results are achieved. That is to say, the in‐band backhaul transmission degrades the SINR coverage probabilities because of the existence of wireless backhaul interference. Besides of these, in numerical analysis, we also investigate the effect of the network parameters on the secrecy and coverage performance of both the macro and small cells. The derived results can be used for guiding the design of HCNs.

An Optimized Approach on Link Stability with Load Balancing in MANET using Balanced Reliable Shortest Route AOMDV (BRSR_AOMDV)

Objectives: MANET consistency depends on the robustness of the load balancing and link between the mobile nodes of the network. This paper has been evaluated the reliability for defective nodes (transceivers) to find the average queue length and signal interference noise ratio. In order to increase the load balancing and produce high throughput. Methods/ Analysis: This paper proposes Balanced Reliable Shortest Route AOMDV (BRSR-AOMDV) a technique which handles both load balancing and link stability based on the average queue length computation and the signal strength of the each reachable links. This proposed approach uses two phases, one for discovering the path with least queue size and in the second phase among the selected paths with short queue size the path with high link stability is considered as optimal path for traversing packet from the selected source to destination nodes. Findings: The method is illustrated with an application and some imperative results are also presented. The performance is done based on different metrics for load balancing as well as link stability and the proposed method performs better than the AODV. Conclusion: BRSR-AOMDV achieves good packet delivery ratio, more network lifetime while attaining low delay overhead than the existing scheme AODV scheme. Keywords: Fault Tolerance, Load balancing, Link Stability, MANET, Queue size

An Optimized Approach on Link Stability with Load Balancing in MANET using Balanced Reliable Shortest Route AOMDV (BRSR_AOMDV)

Objectives: MANET consistency depends on the robustness of the load balancing and link between the mobile nodes of the network. This paper has been evaluated the reliability for defective nodes (transceivers) to find the average queue length and signal interference noise ratio. In order to increase the load balancing and produce high throughput. Methods/Analysis: This paper proposes Balanced Reliable Shortest Route AOMDV (BRSR-AOMDV) a technique which handles both load balancing and link stability based on the average queue length computation and the signal strength of the each reachable links. This proposed approach uses two phases, one for discovering the path with least queue size and in the second phase among the selected paths with short queue size the path with high link stability is considered as optimal path for traversing packet from the selected source to destination nodes. Findings: The method is illustrated with an application and some imperative results are also presented. The performance is done based on different metrics for load balancing as well as link stability and the proposed method performs better than the AODV. Conclusion: BRSR-AOMDV achieves good packet delivery ratio, more network lifetime while attaining low delay overhead than the existing scheme AODV scheme.

A Novel Approach for Energy EfficientReliable Routing Using TABU in WirelessAd Hoc Networks

Wireless sensor network often used in a challenging application where data transmission is daunting. In order to improve the reliability of the data transmission two novel energy-aware routing algorithms for wireless ad hoc networks called Signal Interference Noise Ratio (SINR) and TABU energy routing has been proposed in this work. SINR addresses some parameters like energy-efficiency, reliability and operation of network. It deliberates the energy consumption and the remaining battery energy of nodes as well as quality of links to find energy-efficient and reliable routes that increase the operational lifetime of the network. TABU on the other hand, is an energy-efficient routing algorithm which finds routes minimizing the total energy required for end-to-end packet traversal. RMER and RMECR are proposed of networks in which either hop-by-hop or end-to-end retransmissions ensure reliability. This makes SINR an elegant solution to increase energy-efficiency, reliability and lifespan of wireless ad hoc networks.