Reduce Co-channel Interference Research Articles

Energy-Efficient Device-to-Device Communications for Green Internet of Things Using Unmanned Aerial Vehicle-Mounted Intelligent Reflecting Surface

The Internet of Things (IoT) serves as a crucial element in interconnecting diverse devices within the realm of smart technology. However, the energy consumption of IoT technology has become a notable challenge and an area of interest for researchers. With the aim of achieving an IoT with low power consumption, green IoT has been introduced. The use of unmanned aerial vehicles (UAVs) represents a highly innovative approach for creating a sustainable green IoT network. UAVs offer advantages in terms of flexibility, mobility, and cost. Moreover, device-to-device (D2D) communication is essential in emergency communications, due to its ability to support direct communication between devices. The intelligent reflecting surface (IRS) is also a hopeful technology which reconstructs the radio propagation environment and provides a possible solution to reduce co-channel interference resulting from spectrum sharing for D2D communications. The investigation in this paper hence focuses on energy-efficient UAV-IRS-assisted D2D communications for green IoT. In particular, a problem of optimization aimed at maximizing the system’s average energy efficiency (EE) is formulated, firstly, by simultaneously optimizing the power coefficients of all D2D transmitters, the UAV’s trajectory, and the base station (BS)’s active beamforming, along with the IRS’s phase shifts. Second, to address the problem, we develop a multi-agent twin delayed deep deterministic policy gradient (MATD3)-based scheme to find a near-optimal solution, where D2D transmitters, the BS, and the UAV cooperatively learn to improve EE and suppress the interference. To conclude, numerical simulations are conducted to assess the availability of the proposed scheme, and the simulation results demonstrate that the proposed scheme surpasses the baseline approaches in both convergence speed and EE performance.

Interference Management Based on Meta-Heuristic Algorithms in 5G Device-to-Device Communications

Device-to-Device (D2D) communication is an emerging technology that is vital for the future of cellular networks, including 5G and beyond. Its potential lies in enhancing system throughput, offloading the network core, and improving spectral efficiency. Therefore, optimizing resource and power allocation to reduce co-channel interference is crucial for harnessing these benefits. In this paper, we conduct a comparative study of meta-heuristic algorithms, employing Genetic Algorithms (GAs), Particle Swarm Optimization (PSO), Bee Life Algorithm (BLA), and a novel combination of matching techniques with BLA for joint channel and power allocation optimization. The simulation results highlight the effectiveness of bio-inspired algorithms in addressing these challenges. Moreover, the proposed amalgamation of the matching algorithm with BLA outperforms other meta-heuristic algorithms, namely, PSO, BLA, and GA, in terms of throughput, convergence speed, and achieving practical solutions.

Interference-Aware Deployment for Maximizing User Satisfaction in Multi-UAV Wireless Networks

In this letter, we study the deployment of Unmanned Aerial Vehicle mounted Base Stations (UAV-BSs) in multi-UAV cellular networks. We model the multi-UAV deployment problem as a user satisfaction maximization problem, that is, maximizing the proportion of served ground users (GUs) that meet a given minimum data rate requirement. We propose an interference-aware deployment (IAD) algorithm for serving arbitrarily distributed outdoor GUs. The proposed algorithm can alleviate the problem of overlapping coverage between adjacent UAV-BSs to minimize inter-cell interference. Therefore, reducing co-channel interference between UAV-BSs will improve user satisfaction and ensure that most GUs can achieve the minimum data rate requirement. Simulation results show that our proposed IAD outperforms comparative methods by more than 10% in user satisfaction in high-density environments.

Multi-Leakage Source Localization of Safety Valve Based on Uniform Circular AE Array and Improved MUSIC Algorithm.

The safety valve is the core component of the pressure-relief protection device for pressure-bearing special equipment. When the safety valve leaks, the medium of the pressure vessel will be lost and wasted, which may cause safety accidents. With the aim to solve the problem of accurately locating the multiple leakage sources of safety valves, a localization method combining a uniform circular array acoustic emission detection and an improved multiple signal classification (MUSIC) algorithm is proposed. First, an improved wavelet threshold function denoising method is introduced to extract acoustic emission signals with high SNR, thereby reducing the rank of the covariance matrix, weakening the noise dispersion caused by eigenvalue reconstruction, avoiding signal and noise cross-confusion, and improving positioning accuracy. By introducing a windowed fast Fourier transform (FFT) frequency division processing link to obtain narrowband signal, the premise of using MUSIC positioning algorithm is established. In addition, a forward/backward spatial smoothing algorithm is introduced in the decoherence link to reduce co-channel interference, reduce the rank loss of the signal covariance matrix, and improve the positioning accuracy of the algorithm. The results show that when the working pressure is 0.70 MPa, 0.75 MPa, and 0.80 MPa, the deviation between the azimuth angle and elevation angle positioning results of each leakage source obtained by the improved MUSIC algorithm and the actual angle does not exceed 2°, and the relative error does not exceed 3.5%. Therefore, the improved MUSIC algorithm can accurately locate multiple leakage sources of the safety valve, and as the working pressure of the safety valve increases, the positioning accuracy of the improved MUSIC algorithm also increases accordingly.

An efficient resource optimization scheme for D2D communication

With the rapid development of wireless technologies, wireless access networks have entered their Fifth-Generation (5G) system phase. The heterogeneous and complex nature of a 5G system, with its numerous technological scenarios, poses significant challenges to wireless resource management, making radio resource optimization an important aspect of Device-to-Device (D2D) communication in such systems. Cellular D2D communication can improve spectrum efficiency, increase system capacity, and reduce base station communication burdens by sharing authorized cell resources; however, can also cause serious interference. Therefore, research focusing on reducing this interference by optimizing the configuration of shared cellular resources has also grown in importance. This paper proposes a novel algorithm to address the problems of co-channel interference and energy efficiency optimization in a long-term evolution network. The proposed algorithm uses the fuzzy clustering method, which employs minimum outage probability to divide D2D users into several groups in order to improve system throughput and reduce interference between users. An efficient power control algorithm based on game theory is also proposed to optimize user transmission power within each group and thereby improve user energy efficiency. Simulation results show that these proposed algorithms can effectively improve system throughput, reduce co-channel interference, and enhance energy efficiency.

Solution for Interference in Hotspot Scenarios Applying Q-Learning on FFR-Based ICIC Techniques.

This work explores interference coordination techniques (inter-cell interference coordination, ICIC) based on fractional frequency reuse (FFR) as a solution for a multi-cellular scenario with user concentration varying over time. Initially, we present the problem of high user concentration along with their consequences. Next, the use of multiple-input multiple-output (MIMO) and small cells are discussed as classic solutions to the problem, leading to the introduction of fractional frequency reuse and existing ICIC techniques that use FFR. An exploratory analysis is presented in order to demonstrate the effectiveness of ICIC techniques in reducing co-channel interference, as well as to compare different techniques. A statistical study was conducted using one of the techniques from the first analysis in order to identify which of its parameters are relevant to the system performance. Additionally, another study is presented to highlight the impact of high user concentration in the proposed scenario. Because of the dynamic aspect of the system, this work proposes a solution based on machine learning. It consists of changing the ICIC parameters automatically to maintain the best possible signal-to-interference-plus-noise ratio (SINR) in a scenario with hotspots appearing over time. All investigations are based on ns-3 simulator prototyping. The results show that the proposed Q-Learning algorithm increases the average SINR from all users and hotspot users when compared with a scenario without Q-Learning. The SINR from hotspot users is increased by 11.2% in the worst case scenario and by 180% in the best case.

Design of microstrip patch antenna to deploy unmanned aerial vehicle as UE in 5G wireless network

The use of unmanned aerial vehicle (UAV) has been increasing rapidly in the civilian and military applications, because of UAV's high-performance communication with ground clients, especially for its intrinsic properties such as adaptive altitude, mobility, and flexibility. UAV deployment can be monitored and controlled through 5G wireless network as user equipment (UE) along with other devices. A highly directive microstrip patch antenna (MPA) could establish long-distance communication by overcoming air attenuation and reduce co-channel interference in the limited region if UAV uses a specifically dedicated band, which might enhance spatially reuse of the spectrum. Also, MPA is highly recommended for UAV because of its low weight, low cost, compact size, and flat shape. In this paper, we have designed a highly directive single-band 2×2 and 4×4 antenna array for 5.8 GHz and 28 GHz frequency respectively for UAV application in a focus to deploy UAV through 5G wireless network. Here, The Roger RT5880 (lossy) material utilize as a substrate due to its lower dielectric constant which achieves higher directivity and good mechanical stability. Inset feed technique used to feed antenna for lowering input impedance which provides higher antenna efficiency. The results show a wider bandwidth of 702 MHz and 1.596 GHz for 5.8 GHz and 28 GHz antenna array correspondingly with a compact size.

Channel Estimation for Intelligent Reflecting Surface Assisted MIMO Systems: A Tensor Modeling Approach

Intelligent reflecting surface (IRS) is an emerging technology for future wireless communications including 5G and especially 6G. It consists of a large 2D array of (semi-)passive scattering elements that control the electromagnetic properties of radio-frequency waves so that the reflected signals add coherently at the intended receiver or destructively to reduce co-channel interference. The promised gains of IRS-assisted communications depend on the accuracy of the channel state information. In this paper, we address the receiver design for an IRS-assisted multiple-input multiple-output (MIMO) communication system via a tensor modeling approach aiming at the channel estimation problem using supervised (pilot-assisted) methods. Considering a structured time-domain pattern of pilots and IRS phase shifts, we present two channel estimation methods that rely on a parallel factor (PARAFAC) tensor modeling of the received signals. The first one has a closed-form solution based on a Khatri-Rao factorization of the cascaded MIMO channel, by solving rank-1 matrix approximation problems, while the second one is an iterative alternating estimation scheme. The common feature of both methods is the decoupling of the estimates of the involved MIMO channel matrices (base station-IRS and IRS-user terminal), which provides performance enhancements in comparison to competing methods that are based on unstructured LS estimates of the cascaded channel. Design recommendations for both methods that guide the choice of the system parameters are discussed. Numerical results show the effectiveness of the proposed receivers, highlight the involved trade-offs, and corroborate their superior performance compared to competing LS-based solutions.

Optimize Cellular Network Performance Using Phased Arrays

In conventional telecommunication systems, the base station does not know the user equipment location; it broadcast in all directions to fully cover the entire cell area. This represents power waste in addition to transmitting the signal in directions where users do not exist, which seen as interference for co-channel cells. This reduces SNR that limits the capacity and impedes the use of the spectrum effectively. This consideration led to the use of smart antenna (SA) technology that uses the Space-division multiple access (SDMA technique, Based on extracting spatial data for users within the network. In this work, Phased Arrays are used to improve the performance of the GSM network in terms of (decrease power, raise coverage, increase capacity, reduce co-channel interference) with the comparison to conventional antennas. Simulation has studied and realized using Matlab, simulation results, and performances have presented. Introduction.

Analysis and performance evaluation of Relay Assisted OFDMA cellular systems with different Beamforming techniques

This paper addresses the Co-Channel Interference (CCI) reduction in Relay Assisted (R-A) cellular systems using Beamforming (BF) techniques. Analytical treatments are conducted. The network performance improvements through reducing the CCI are evaluated using three different configurations of applying BF. These configurations represent Relay Station (RS) do BF only, Base Station (BS) do BF only and both RS and BS do BF. Additionally, the considered BF techniques denote the horizontal, vertical, and Three Dimensional (3D) BF techniques. Therefore, each configuration consists of three different scenarios. Accordingly, nine different scenarios are studied. A comparison of these scenarios is introduced to enhance the network Quality of Service (QoS). Moreover, closed-form expressions for worst-cases Cell Edge User’s (CEU’s) Signal to Interference Ratio (SIR), Cell Center User’s (CCU’s) SIR and inner radius are implemented. Furthermore, various performance evaluation metrics are used to compare the different scenarios. The results reveal, that the performance of vertical BF is close to that of the 3D BF in low Path-loss (PL) exponent range. Therefore, applying vertical BF is preferable from the network cost and power consumption perspectives. Furthermore, it is observed, that the configuration of RS do BF is superior to other configurations when horizontal or vertical BF technique is employed. Additionally, the configuration of both RS and BS do BF outperforms the other configurations when 3D BF is applied. However, as unexpected it performs worse than them when the other BF techniques are applied. The work outcomes attain much higher CEU’s SIR improvement. Therefore, the coverage probability is increased. Thus, more users can be served by the network. Accordingly, the total network cost is reduced. So, this treatment not only improves the network performance, but also it reduces the total network cost.

Overlapping Coalition-Based Resource and Power Allocation for Enhanced Performance of Underlaying D2D Communication

Device-to-Device (D2D) communication is seen as a promising technology to offload exponentially increasing cellular data traffic. This also enhances spectral and energy efficiency of the cellular network. However, co-channel interference restricts the potential gain of Underlay-D2D (U-D2D) communication technology. In this paper, we propose a novel resource allocation scheme coupled with distributed power control strategy to reduce co-channel interference and improve overall system sum rate. Resource allocation is based on overlapping coalition formation game model. Overlapping coalitions allow a single D2D pair to utilize multiple resource blocks, which provides enhanced transmission bandwidth per user. But, this improved bandwidth is achieved at the cost of increased co-channel interference. The proposed scheme mitigates this problem by distributed control of D2D transmit power in accordance with the interference sensed on each resource block allocated for that particular D2D pair. It is shown through numerical results that there is a significant improvement in overall U-D2D system performance in terms of system sum rate and D2D transmission ratio in comparison with other existing techniques.

Joint interference optimization and user satisfaction improvement for multicast routing and channel assignment in wireless mesh networks

Multicast communication is a key technology for wireless mesh networks. In order to reduce co-channel interference in multicast transmission, we jointly study multicast tree construction and channel assignment in this paper. First, interference in multicast is analyzed and measured with considerations of hidden node problem and user coverage. Then, an algorithm called CIOMT is proposed to construct multicast routing tree, In which we find the path with minimum interference to root and add it to the constructing multicast tree, give an upper limit to the source-to-destination distance for QoS consideration, and tree structure is optimized to relieve interference among multicast links. Moreover, we propose a channel assignment algorithm for the constructed multicast tree with the name CIOCA. In CIOCA algorithm, in order to provide good service to the users as much as possible, we take the user coverage of each destination as the top priority in channel assignment, and the nodes are assigned the sending channels by descending order of priority. In each step, we find the channel with minimum interference to the whole tree, and assign it to the related nodes. For making full use of spectrum resources, the non-overlapping and overlapping channels are both taken into consideration. At last, simulation is done, and the results show the effectivity of the proposed multicast routing scheme. As far as user satisfaction is concerned, the proposed scheme has much better performance than the other two classic algorithms.

A New Construction of Optical Zero-Correlation Zone Codes

Abstract A new method for constructing optical zero-correlation zone (OZCZ) codes based on the Hadamard matrix and the concatenation operation is proposed. The most important property of the obtained codes is that the periodic correlation function of the proposed codes is zero for the phase shifts within the zero-correlation zone. The structure of the proposed OZCZ code is simple and their construction is more flexible. The proposed code is expected to be useful for reducing co-channel interference in optical code division multiple access system.

Stackelberg‐type channel state information feedback control game for energy efficiency in wireless networks

Efficient use of energy has recently become an essential research topic for wireless communications. Channel state information (CSI) feedback has been well recognised to have great significances for the energy-efficiency (EE) of the closed-loop wireless networks. However, works on EE focus mostly on the feed-forward data link by performing precoding and upper layer resource allocation and scheduling approaches. Unlike traditional work, the authors propose to study the EE by controlling the CSI feedback, where the mobile transmitter and receiver pairs exchange data by precoding for co-channel interference reduction. The EE maximisation problem can be formulated in the analytical settings of a game-theoretic framework by a two-level Stackelberg-type CSI feedback control game (SCFC), which can balance the power consumptions and the bandwidth. Specifically, the leader maximises the EE objective by introducing a price factor in the higher level. In lower level, multiple mobile receivers compete for the feedback channel utilisation to maximise their own utilities. The existence of the equilibriums is corroborated and the convergence behaviour is discussed. Simulation results demonstrate that the proposed distributed SCFC game can greatly enhance the EE performance by adjusting the pricing factor which can achieve close optimal performances in comparison with the centralised scheme.

Neighbor discovery and routing schemes for mobile ad-hoc networks with beamwidth adaptive smart antennas

The use of smart directional antennas in ad-hoc networks has recently received much attention since this technology offers a way to optimize power consumption, increase spatial reuse and reduce co-channel interference. Neighbor discovery is an important first step for these self-configured networks because it makes it possible to identify the active nodes surrounding a given node and this information is essential for other higher layer protocols like medium access control, routing and topology control protocols. In this article, we present two algorithms that aim to take full advantage of the capabilities of smart antennas. The first one aims to increase the number of discovered nodes by considering the nodes that are located in the second-hop neighborhood of a node. The second algorithm seeks to reduce the number of hops in a route between source and destination nodes by using the extended range that can be achieved when the nodes are equipped with directional antennas. The results of the simulations have shown a reduction in the end-to-end delay and an increase in the network throughput when the scheme is compared with other reactive routing protocols.

A Utility-Based and QoS-Aware Power Control Scheme for Wireless Body Area Networks

Power control is widely used to reduce co-channel interference in wireless networks and guarantee the signal-to-interference plus noise ratio (SINR) of ongoing connections. This technique is also effective for wireless body area networks (WBANs). Although achieving satisfactory SINR is important for WBAN users, they may not be willing to achieve it at arbitrarily high power levels since power is a scarce resource in WBANs. Besides, for WBANs with different purposes, the QoS requirements and concern about the power consumption may be different. This motivates us to formulate the power control problem using the concepts from microeconomics and game theory. In this paper, the QoS objective is viewed as a utility function, which represents the degree of user satisfaction, while the power consumption is viewed as a cost function. The power control problem consequently becomes a non-cooperative multiplayer game, in which each player tries to maximize its net utility, i.e., the utility minus the cost. Within this framework, we investigate the Nash equilibrium existence and uniqueness in the game and derive the best response solution to reach the Nash equilibrium. To obtain the optimal transmission power in a distributed way, we further propose a utility-based and QoS-aware power control algorithm (UQoS-PCA). Tunable cost coefficient in UQoS-PCA enables this scheme to be flexible to satisfy diverse service requirements. Simulation results show the convergence and effectiveness of the proposed scheme as well as improvements over existing algorithm.

Realistic interference-free channel assignment for dynamic wireless mesh networks using beamforming

To make the most efficient use of scarce bandwidth, channel assignment methods for wireless mesh networks (WMNs) should try to minimize the number of frequency channels used while achieving maximum network throughput. Beamforming is a well-known technique that improves spatial reuse in wireless networks. However, there are no channel assignment methods for WMNs that use beamforming to reduce the number of frequency channels. We develop the first channel assignment method for dynamic WMNs that incorporates beamforming in the conflict graph and matrix. This reduces co-channel interference significantly, thereby reducing the number of frequency channels required (NCR) to ensure interference-free communication among the mesh nodes while achieving maximum network throughput. Our novel Linear Array Beamforming-based Channel Assignment (LAB-CA) method significantly increases the spectrum utilization efficiency of WMNs at the expense of increased hardware complexity. It outperforms classical omni-directional antenna pattern-based channel assignment (OAP-CA) in terms of NCR. In a heterogeneous WMN where mesh nodes have differing numbers of radio interfaces, LAB-CA also outperforms OAP-CA in terms of NCR in both sparse and dense scenarios. A further significant reduction in NCR is achieved when the number of antennas in the linear antenna arrays of mesh nodes is increased.

An Energy-Efficient Resource Allocation and Interference Management Scheme in Green Heterogeneous Networks Using Game Theory

In heterogeneous networks (HetNets), energy-efficient resource allocation and intercell-interference management are important issues. In this paper, we address these issues using a two-level dynamic scheme. First, we assign the MUs with the optimum number of subchannels that achieves an operator's required balance between macro users' satisfaction and maximization of network efficiency. Then, the remaining subchannels are left to be shared by a number of small cells. In the latter step, a transmit power adaptation method using a noncooperative game-theoretic approach is developed to reduce cochannel interference in the whole network. The problem is formulated by allowing multiple neighboring small cells to share each subchannel (i.e., universal frequency reuse in the small cell level). We fully characterize the pricing factor in the penalty part of the utility function. The existence and uniqueness of the Nash equilibrium (NE) are analyzed and proved. Then, a distributed iterative algorithm based on the fixed-point theorem is proposed to attain the equilibrium of the game. Simulation results are presented to show the effectiveness of the proposed scheme in different network topologies.

Femtocell base station clustering and logistic smooth transition autoregressive‐based predicted signal‐to‐interference‐plus‐noise ratio for performance improvement of two‐tier macro/femtocell networks

The aim of this study is to improve the performance of two-tier macro/femtocell networks using a power control approach. In wireless networks, power control plays an important role in improving a number of performance parameters such as co-channel interference and outage probability reduction, throughput increasing, and power saving. This study explores the evolution of centralised power control algorithm based on femtocell base station (FBS) clustering and predicted signal-to-interference-plus-noise ratio (SINR) of users. To reduce the computational complexity of centralised algorithm, dense deployed femtocells are considered in different clusters. In this case, femtocells inside one cluster make considerable interference to each other, while the interferences from femtocells of other clusters are negligible. Moreover, because of the non-linearity of SINR samples, non-linear logistic smooth transition autoregressive (LSTAR) model is used to model the SINR data, and then the next SINR samples are predicted from the previous samples. According to the clustered FBSs and predicted SINR, the proposed power control scheme is applied to femtocell network in the downlink. The results demonstrate that the introduced method improves the outage probability and throughput and outperforms previous methods significantly.

Implementation of WLAN N and Estimation of Co Channel and Adjacent Channel Interference

Implementation of WLAN N and Estimation of Co Channel and Adjacent Channel Interference An enhanced Wireless network pLAN is needed to replace the existing WLANs. The introduction of WLAN/N offers the flexibility to dynamically locate users and devices, and to provide scalability to the network. In this research paper, the signals over non-line-ofsight propagation of 802.11/g and 802.11/n in indoor environment of the multi storied building are examined. Usually, an IEEE 802.11 variation is chosen based on their bandwidth and their coverage premises. In addition, suitable positioning of access points (AP) is significant to determine the efficiency of the network. Test bed and experiment has been carried out in terms of RSSI (Received Signal Strength Indication), coverage area, and signal interference computation between channels. The signal levels were measured using Com view and Tamo Graph tools and were compared with the Motley-Keenan model. The observed results have shown considerable reduction of Co-channel and adjacent channel interference in using 802.11/n compared to 802.11/g. This study will be the advantage to the researchers to choose the best technology depending on their deployment and requirement.