Effect Of Co-channel Interference Research Articles

Effects of Co-Channel Interference on the Performance of IRS-Assisted Communications

Effects of Co-Channel Interference on the Performance of IRS-Assisted Communications

Proximal Policy Optimization for RIS-Assisted Full Duplex 6G-V2X Communications

In this work, we consider a novel reconfigurable intelligent surface (RIS)-assisted full-duplex (FD) sixth generation (6G)-vehicle-to-everything (V2X) communication network having a FD base station (BS) simultaneously communicating with a uplink (UL) and a downlink (DL) mobile vehicles with the aide of two RISs, one for each link. We provide an analytical framework to investigate the performance of this network and, consequently, formulate an optimization problem to jointly optimize the phase shift matrices at both the RISs that maximize the achievable sum-rate. Thereafter, due to the non-convex nature of the problem, we propose a low complexity proximal policy optimization (PPO)-based deep reinforcement learning (DRL) algorithm that solves the problem in continuous action spaces by reducing the overall training overhead and provides optimum values of phase-shift matrix at each RIS. Further, we extend the analysis considering multiple transmit and receive antennas at the BS that simultaneously serves multiple UL and DL vehicles. We present exhaustive simulations-based graphical results to validate the effectiveness and accuracy of the proposed algorithm compared to deep deterministic policy gradient (DDPG) and successive refinement (SR)-based solutions. Accordingly, we demonstrate the dominance of the considered FD system over its half-duplex (HD) counterpart. We also discuss the impact of the number of elements at each RIS, each vehicle's velocity and their distance from the RIS and the BS on the performance of the respective links. Moreover, we also highlight the impact of imperfect self-interference cancellation and discuss the trade-off between the UL and DL performances due to this imperfection. Additionally, it is shown that the proposed algorithm is approximately <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$10 \times$</tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$ 40 \times$</tex-math></inline-formula> faster than DDPG and SR, respectively. Finally, for the multiple vehicle case, we demonstrate the effect of co-channel interference on the DL rate and the impact of RIS elements, the number of UL and DL vehicles on the system performance.

Effects of co-channel interference on RIS empowered wireless networks amid multiple eavesdropping attempts

In this study, the secrecy performance of reconfigurable intelligent surfaces (RIS)-aided wireless networks in the existence of multiple interferers towards the destination is investigated. In particular, three critical issues in the design of secure RIS-assisted networks are examined: effects of interferers, operation of multiple eavesdroppers (colluding and non-colluding), and benefit of RISs. To examine their effects, the analytical expressions of secrecy outage probability are derived in a closed form. Additionally, asymptotic analyses at a high signal-to-noise ratio (SNR) regime are provided. Finally, the analytical results are validated through numerical simulations.

A Deep Reinforcement Learning Scheme for Sum Rate and Fairness Maximization Among D2D Pairs Underlaying Cellular Network With NOMA

Device-to-device (D2D) communication is an emerging technology in 5G and upcoming 6G networks due to its properties to enhanced spectral efficiency (SE), energy-efficiency (EE), and sum rate. Despite these advantages, co-channel and cross-channel interference, and ultra-massive connectivity are major issues which can deteriorate performance of any implemented solution in this environment. To address these issues, in this paper, we integrated the power domain non-orthogonal multiple access techniques (PD-NOMA) on the base station (BS). NOMA serves more than one user using the same resource block (RB) and reduces the effect of interference at CUs due to the presence of successive interference cancellation (SIC). The problem is formulated as a mixed-integer non-linear programming (MINLP) with associated resources and power constraints of the BS and DDPs with an aim to maximize the sum rate and fairness among the NOMA-enabled CUs and D2D pairs (DDPs). We firstly used the centralized deep deterministic policy gradient (DDPG) and arithmetic-geometric mean approximation (AGMA) technique to reduce cross-channel interference (CR-CI) and control the power. Then, to provide fairness to all the users, we transformed the proposed solution into distributed deep deterministic policy gradient (D3PG). Also, the successive convex approximation technique is then integrated into the D3PG to mitigate the effect of co-channel (CO-CI) interference among DDPs. The experimental results show that the proposed scheme has superior performance with respect to sum rate and fairness. Also, the results reveal that the proposed scheme has 21.05%, 34.21%, and 49.8% higher sum rate in comparison to DDPG, Deep dueling, and DQN scheduling.

On Outage Analysis in Overlay CCRN with RF Energy Harvesting and Co-channel Interference

This paper studies the effect of co-channel interference (CCI) on energy harvesting (EH) from radio frequency (RF) signal and the performance of reliable communication. An overlay mode of cooperative cognitive radio network (CCRN) model is considered that may support one-way communication between primary users (PUs) and two-way communications between secondary users (SUs). Closed form PU and SU outage expressions are derived in presence of CCI at two SU nodes and multiple antennas at PU transmitter. The absolute impact of CCI on the performance of the proposed system is analysed with respect to various parameters like, transmission power, interference-to-noise-ratio (INR), power splitting factor, number of CCI sources and number of antennas. About 20% and 15% improvements are achieved for PU and SU outage using two antennas compared to single antenna system model.

Study of the Effect of Adjacent and Co-Channel Interference on the Performance of a Wi-Fi Network with a hannel Width of 40 MHz in the 2.4 GHz Band

For a long time, Wi-Fi networks have used 22 MHz wide (IEEE 802.11b) and 20 MHz wide (IEEE 802.11a/g) channels only. With the advent of the IEEE 802.11n, it became feasible to combine two adjacent 20 MHz channels to make a 40 MHz channel. By doubling channel width, it is possible to double data rates. However, neighboring Wi-Fi networks using 40 and 20 MHz wide channels can negatively affect each other due to adjacent and co-channel interference. Research subject. In this paper, we present the results of an experimental study of parallel operation of two Wi-Fi networks using 40 MHz and 20 MHz channels in the 2.4 GHz band. Method. To achieve this goal, the following methods of empirical research were used: measurement and experiment. Core results. Using a test bed, parallel&#x0D; operation of neighboring Wi-Fi networks using 40 MHz and 20 MHz channels in the 2.4 GHz band was simulated. Based on the captured traffic, the effective data rate and the retry rate for both Wi-Fi networks were calculated. Practical relevance. The obtained results can be used for manual or automatic configuration of Wi-Fi routers.

Adaptive AF/DF Two-Way Relaying in FD Multiuser URLLC System With User Mobility

We consider a full-duplex (FD)-enabled multi-user two-way communication system with adaptive amplify-and-forward (AF)/decode-and-forward (DF) relaying protocol. All the users are assumed to be mobile and to have FD abilities. The effect of mobility, which results in time-selective fading, is modeled using a first-order autoregressive (AR1) process. The fading channel-based approach characterizes the residual self-interference (RSI) at the FD relay, user nodes and is modeled as a Rician distributed random variable. This paper constitutes the most critical use case of 5G, i.e., ultra-reliable low latency communication (URLLC), which adopts short-packets finite blocklength (FB) codes to spin out into the mission-critical applications where strict latency and reliability requirements are highly desirable. The outage performance of the system is studied over independent and non-identically distributed complex Gaussian (Rayleigh envelope) channels with imperfect channel state information (CSI) for with and without URLLC use cases. The closed-form expressions for the outage probability and block error rate (BLER) are derived for the absolute channel power-based scheduling scheme considering the different Doppler power spectra models and the effect of co-channel interference (CCI). The expressions for the asymptotic outage probability are also derived. The presented analysis is compared with baseline schemes, e.g., the results derived with adaptive AF/DF relaying are also compared with both AF and DF relaying, and the performance of the FD transmissions is compared to that of half-duplex (HD) transmissions. The impact of node mobility, RSI, FBL, number of user pairs, and imperfect CSI on the system performance is investigated. Moreover, essential insights are obtained related to the performance gain and region of the superiority of the adaptive AF/DF relaying scheme. The derived analytic results are validated through Monte Carlo simulations. Furthermore, at high transmit power, the outage performance for the adaptive AF/DF protocol approaches the derived asymptotic floor.

Performance of Spectrum Sharing in Hybrid Satellite Terrestrial Network with Opportunistic Relay Selection

In this paper, we consider the uplink of a hybrid satellite-terrestrial spectrum sharing system, in which satellite terminal communicates with satellite through terrestrial relay-assisted transmission. To accommodate expanding networks within limited spectrum, spectrum sharing is considered a promising candidate. For the system in which satellite terminals and terrestrial terminals share spectrum, we propose opportunistic relay selected spectrum sharing method based on decoding and forwarding protocol. Selecting the optimal relay station is aimed at minimizing the outage probability of the satellite terminal and maximizing the throughput of the system. Due to spectrum sharing policy and imperfections in the RF front end, we also consider the effects of cochannel interference (CCI) and hardware impairments (HIs). The satellite link is modeled as Shadowed-Rician fading, and the terrestrial link uses Nakagami-m fading. In addition, we deduce the closed-form analytical expressions of the satellite terminal outage probability, deduce the asymptotic expressions under the condition of high signal-to-noise ratio, and analyze their achievable diversity orders. Numerical and simulation results validate the performance gain of opportunistic relay selection compared to partial relay selection. Monte Carlo simulations confirm the correctness of the theoretical analysis and illustrate the effects of CCI and HIs on the system.

Calibration-Free 3D Indoor Positioning Algorithms Based on DNN and DIFF.

The heterogeneity of wireless receiving devices, co-channel interference, and multi-path effect make the received signal strength indication (RSSI) of Wi-Fi fluctuate greatly, which seriously degrades the RSSI-based positioning accuracy. Signal strength difference (DIFF), a calibration-free solution for handling the received signal strength variance between diverse devices, can effectively reduce the negative impact of signal fluctuation. However, DIFF also leads to the explosion of the RSSI data dimension, expanding the number of dimensions from m to , which reduces the positioning efficiency. To this end, we design a data hierarchical processing strategy based on a building-floor-specific location, which effectively improves the efficiency of high-dimensional data processing. Moreover, based on a deep neural network (DNN), we design three different positioning algorithms for multi-building, multi-floor, and specific-location respectively, extending the indoor positioning from the single plane to three dimensions. Specifically, in the stage of data preprocessing, we first create the original RSSI database. Next, we create the optimized RSSI database by identifying and deleting the unavailable data in the RSSI database. Finally, we perform DIFF processing on the optimized RSSI database to create the DIFF database. In the stage of positioning, firstly, we design an improved multi-building positioning algorithm based on a denoising autoencoder (DAE). Secondly, we design an enhanced DNN for multi-floor positioning. Finally, the newly deep denoising autoencoder (DDAE) used for specific location positioning is proposed. The experimental results show that the proposed algorithms have better positioning efficiency and accuracy compared with the traditional machine learning algorithms and the current advanced deep learning algorithms.

Improved Multi-Channel Multi-Interface Routing Protocol for Wireless Mesh Networks

In recent years, Wireless Mesh Networks (WMN) are emerging as a potential technology to enhance the ability and availability of wireless networks. WMN consists of wireless mesh routers and terminals connected by wireless multi-hop communication. Besides, in WMN, each wireless node owns many interfaces, and each interface operates on many channels. However, effectively using multiple orthogonal channels and multiple interfaces to increase the performance of WMN and decrease the radio link transmission interference is of significant challenge. In this paper, we consider routing issues in WMN. Then, we proposed an on-demand routing protocol, adaptive multi-channel multi-interface operation, improved from the AODV protocol. This protocol is capable of effectively managing communication in the WMN and limited effects of co-channel interference. The simulation results on NS2 show that our proposed protocol improves throughput, delay and packet delivery rate compared to existing traditional protocols.

Model-Driven Approach to Fading-Aware Wireless Network Planning Leveraging Multiobjective Optimization and Deep Learning

Efficient resource planning is recognized as one of the key enablers making the large-scale deployment of next-generation wireless networks available for mass usage. Modelling, planning, and software simulation tools reduce both the time needed and costs of their tuning and realization. In this paper, we propose a model-driven framework for proactive network planning relying on synergy of deep learning and multiobjective optimization. The predictions about service demand and energy consumption are taken into account. Also, the impact of degradations resulting from fading and cochannel interference (CCI) effects is also considered. The optimization task is treated as a component allocation problem (CAP) aiming to find the best possible base station allocation for the considered smart city locations with respect to performance and service demand constraints. The goal is to maximize Quality of Service (QoS) while keeping the costs and energy consumption as low as possible. The adoption of a model-driven approach in combination with model-to-model transformations and automated code generation does not only reduce the complexity, making experimentation more rapid and convenient at the same time, but also increase the overall reusability and expandability of the planning tool. According to the obtained results, the proposed solution seems to be promising not only due to achieved benefits but also regarding the execution time, which is shorter than that achieved in our previous works, especially for larger distances. Further, we adopt model-based representation of handover strategies within the planning tool, enabling examination of the dynamic behavior of user-created plan, which is not exploited in other similar works. The main contributions of the paper are (1) wireless network planning (WNP) metamodel, a modelling notation for network plans; (2) model-to-model transformation for conversion of WNP to generalized CAP metamodel; (3) prediction problem (PP) metamodel, high-level abstraction for representation of prediction-related regression and classification problems; (4) code generator that creates PyTorch neural network from PP representation; (5) service demand and energy consumption prediction modules performing regression; (6) multiobjective optimization model for base station allocation; (7) Handover Strategy (HS) metamodel used for description of dynamic aspects and adaptability relevant to network planning.

Relay-Assisted D2D Communication over Extended η-μ Fading Channels

In this paper, two cases of Device-to-Device (D2D) communication over a recently introduced extended η-μ fading channel are analyzed. Case A considers a direct D2D communication. While in case B, amplify-and-forward relay-assisted D2D communication is discussed. The effects of cochannel interference at the relay and D2D destination are also included. To combat fading, selection combining- and maximal ratio combining-based diversity schemes are also incorporated at the receiver. Power harvesting based on power splitting technique is also engulfed. Expressions of success and outage probabilities are derived with the help of characteristic function approach. Success and outage probability expressions are functions of path loss, distance between various devices and channel parameters. Based on these expressions, numerical results are presented and discussed.

Cancellation Techniques for Co-channel Interference in MIMO-OFDM Systems and Evaluating Their Performance

In a wireless communication system, the transmitted signal is exposed to various surfaces where it bounces and results in several delayed versions of the same signal at the receiver end. The delayed signals are in the form of electromagnetic waves that are diffracted and reflected from the various object surfaces. These result in co-channel interferences for wireless systems. MIMO has proven to be a striking solution for the new generation of wireless systems. MIMO-OFDM system with QPSK modulation is considered as the wireless system for studying the performance of interference cancellation techniques. The BER performance is studied in channels such as Rayleigh and Rician Fading Channels. The effects of interference are reduced to a certain extent by the inclusion of CDMA (spread spectrum technique) as Technique 1. The effects of interference on this system have been further reduced using the LMS filter as Technique 2. Hence, to show better performance in MIMO-OFDM systems, it is recommended to employ both CDMA and LMS filters to decrease the effects of co-channel interference. It is observed that the parameter BER reduces as the SNR increases for both these channels. Doi: 10.28991/esj-2021-01313 Full Text: PDF

Co-Channel Interference Effects on Downlink Power-Domain Non-Orthogonal Multiple Access

Co-Channel Interference Effects on Downlink Power-Domain Non-Orthogonal Multiple Access

Interference-aware Coordinated Access Control for Heterogeneous Cellular D2D Communication Networks

Device-to-Device (D2D) communications is expected to be a key technology of the forthcoming mobile communication networks because of its benefits in terms of spectral efficiency, energy efficiency, and system capacity. To mitigate frequency collisions as well as reduce the effects of co-channel interference between user's connections, we propose an interference-aware coordinated access control (IaCAC) mechanism for heterogeneous cellular D2D communication networks with dense device deployment of user equipment (UEs). In the proposed network setting, we consider the co-existence of both macro base stations (MBSs) and smallcell base stations (SBSs). In the proposed IaCAC mechanism, MBSs and SBSs are coordinated to perform access control to their UEs while MBSs allocate bandwidth parts dynamically to SBSs based on the interference levels measured at SBSs. Besides, to reduce D2D-to-cellular interference, device user equipments (DUEs) can perform power control autonomously. Simulation results show that the proposed IaCAC can provide higher system throughput and user throughput than those achieved by the network-assisted device-decided scheme proposed in [21]. Moreover, simulation results also reveal that the proposed IaCAC also significantly improve SINR of MUE’s and SUE’s uplink connections.

Reconfigurable Intelligent Surface for Mixed FSO-RF Systems With Co-Channel Interference

Reconfigurable intelligent surface (RIS) is an emerging technology that can achieve reconfigurable radio propagation environments for beyond 5G/6G wireless systems by smartly tuning the signal reflection via a large number of low-cost passive reflecting elements. In this letter, we investigate the effect of co-channel interference (CCI) on RIS-based dual-hop mixed free-space optical (FSO)-radio frequency (RF) communication systems. The source node, equipped with multiple FSO apertures, transmits subcarrier intensity modulated symbols on the FSO link subjected to Gamma-Gamma (GG) distributed atmospheric turbulence with pointing errors (PEs). It is assumed that the relay-RIS and RIS-destination links follow Rayleigh distribution. The destination node is corrupted by multiple CCI (each following Rayleigh distribution). The performance of the considered system is evaluated by deriving novel closed-form expressions for the outage probability (OP) and bit error rate (BER). It is shown through numerical results that RIS-based dual-hop mixed FSO-RF system provide a significant performance enhancement in comparison to a traditional dual-hop mixed FSO-RF system even in presence of CCI.

Radio Resource Management for V2V Multihop Communication Considering Adjacent Channel Interference

This paper investigates schemes for multihop scheduling and power control for vehicle-to-vehicle (V2V) multicast communication, taking into account the effects of both co-channel interference and adjacent channel interference, such that requirements on latency or age of information (AoI) are satisfied. Optimal performance can be achieved by formulating and solving mixed Boolean linear programming (MBLP) optimization problems for various performance metrics, including network throughput and connectivity. Fairness among network nodes (vehicles) is addressed by considering formulations that maximizes the worst-case network node performance. Solving the optimization problem comes at the cost of significant computational complexity for large networks and requires that (slow) channel state information is gathered at a central point. To address these issues, a clustering method is proposed to partition the optimization problem into a set of smaller problems, which reduces the overall computational complexity, and a decentralized algorithm that does not need channel state information is provided.

Evaluating the Mobility Impact on the Performance of Heterogeneous Wireless Networks Over η – μ Fading Channels

The 5G and beyond networks will intrinsically accommodate a wide range of use-case scenarios and expand the limit of legacy mobile systems. The 5G network architecture can handle the seamless operation of various wireless channels in a heterogeneous environment. The $\eta $ - $\mu $ fading model is well-suited for versatile channels as it adapts to different fading behaviors in a broad-range propagation for non-line-of-sight (NLOS) circumstances. This paper evaluates the performance of heterogeneous wireless networks using $\eta $ - $\mu $ fading channel under mobility conditions. We incorporated the random waypoint (RWP) model with $\eta $ - $\mu $ distribution to model the dynamic behavior of non-homogeneous fading. The derivation of expressions for the probability density function (PDF) and cumulative distribution function (CDF) of the received signal power for a mobile network in all three-dimensional topologies is extracted. Consequently, the outage probability (OP) and average bit error rate (ABER) are analyzed to quantify the performance of the mobile system. The effect of co-channel interference (CCI) is investigated based on a desired and interfering signal transmitted in mobile networks. The proposed novel-form can characterize the performance of a mobile user, and the derivation is useful for measuring the effect of noise and interference on the signal. Finally, the novel-form applicability analyzes the impact of mobility incorporated in different fading channels such as Nakagami-m, Nakagami-q (Hoyt), Rayleigh, and one-sided Gaussian distributions.

Analysis of Interference and Signal Quality in Cellular Wireless Networks

An analytical model to compute the effect of co-channel interference from the base stations at the Multi-cell CDMA systems is proposed. The objective is to study the effect of multiple-access interference generated by the neighbor cells on multi-cell CDMA and W-CDMA systems capacity. The potential of adaptive antennas in interference reduction and signal quality improvement in CDMA mobile communications systems is analyzed. The study shows that improvement in base-station sensitivity can boost system performance.

Partial relay selection for combating the effects of co-channel interference in RF/FSO cooperative relaying

In this research work, mixed radio frequency (RF)/free space optical (FSO) communication systems have been investigated in the presence of multiple interferers at the relay node. The considered system incorporates partial relay selection (PRS) using the available outdated channel state information (CSI) at the relay node to combat the effect of interference. The fading on the PRS-aided RF link has been modeled using the Rayleigh distribution whereas the statistics of the co-channel interferers (CCIs) at the relay node has been modeled using Nakagami-m fading distribution. On the other hand, FSO link has been assumed to undergo α−μ distributed atmospheric turbulence with pointing errors. To this end, the model on the FSO link considers the impact of both kinds of optical demodulation schemes i.e., intensity modulation direct detection (IM/DD) and coherent demodulation. For the system under study, exact closed-form expressions for the outage probability, bit error rate (BER) and ergodic capacity have been presented. Further to this, asymptotic high signal to noise ratio (SNR) approximate expressions have been derived for outage probability, BER and ergodic capacity to extract quick insights into the results. Finally, numerical examples have been demonstrated to validate the findings of the research work.