Co-channel Interference Mitigation Research Articles

Examination of 5G NR, LTE, and NB-IoT Radio Interfaces and Their Vulnerabilities to Interference

Modern cellular wireless communication systems of the fourth (4G) and fifth generation (5G) face a problem of various types of interference or intentional jamming. Consequently, a degradation of the services provided and an incorrect network operation may occur. In this paper, configuration of the networks' physical layer is investigated, with the said investigation preceded by the measurement of parameters of commercial networks operating in two different environments, to assess their vulnerabilities to interference or intentional jamming. Finally, a method for analyzing the radio signal received with the use of 5G New Radio (NR), Long Term Evolution (LTE), and Narrowband Internet of Things (NB-IoT) radio interfaces is proposed, to detect and mitigate the negative impact of unwanted signals. Software-based implementation of the proposed method allows one to detect and mitigate co-channel interference, intentional jamming and maintain compatibility of user equipment (UE) with the 3rd Generation Partnership Project (3GPP) standard, as it does not affect operations performed, for instance, at the time and frequency synchronization or channel parameter estimation phases.

Deep Learning Based Cooperative MIMO Systems for Wireless Body Area Networks

Wireless Body Area Network (WBAN) is widely applied in various fields, including healthcare, sports, wellness, and assistive technologies, by offering the benefits of convenience, reliability, low latency, privacy, and customization. However, the propagation characteristics of the WBAN channel can impact the reliability of transmission, which is particularly crucial in healthcare systems. To address this issue, this article presents a novel approach using deep learning-based cooperative Multiple-Input Multiple-Output (MIMO) systems that leverage the autoencoder (AE) technique. In our proposed approach, we utilize the AE-based cooperative MIMO systems with two different techniques: Amplify-and-Forward (AE-AF) and Decode-and-Forward (AE-DF). The AE-AF scheme operates without needing training parameters at the relay node, whereas the AE-DF scheme necessitates training parameters at the relay node. Both schemes aim to overcome challenges such as multipath propagation phenomena, thereby enhancing the performance of on-body communication systems. Additionally, we introduce two combinators, Minimum Mean Square Error (MMSE) scheme and Radio Transformation Network (RTN), to effectively mitigate co-channel interference (CCI) in the received signal streams and improve the bit error rate performance of the AE-AF and AE-DF systems. We assess the performance of these systems in scenarios with and without direct links. Simulation results demonstrate significant performance improvements compared to baseline cooperative MIMO systems using MMSE combining, namely AF-MMSE and DF-MMSE systems. Notably, the proposed systems employing RTN combination, including both direct and relay paths, achieve a 7.5 dB gain over the baseline when all nodes are equipped with two transceiver antennas.

Co-Channel Interference Mitigation in 5g Network using Particle Swarm Optimization

The co-channel interference problem in 5G wireless networks is the subject of this research project. Even with the improvements brought forth by 5G, co-channel interference still degrades network speed and signal quality. Particle Swarm Optimization (PSO) is the method used in this study to minimize this interference and improve network performance by fine-tuning resource allocation settings. PSO-based interference mitigation, network modeling, simulation, an overview of the literature, and comparative analysis are all included in the study. The study is valuable for communication engineers since it explores PSO as a means of improving network quality and expanding our knowledge of wireless technology, even though it is restricted to co-channel interference and PSO. In the sphere of 5G wireless communication, this discovery represents a substantial advancement. The application of particle swarm optimization has shown to be innovative in addressing the complex problem of co-channel interference. Insights into the possibilities of clever optimization strategies for interference reduction can be gained from the applied models and results. With 5G networks set to revolutionize the digital environment, these findings provide a strong basis for future research efforts focused at refining interference avoidance techniques and ultimately boosting the performance and dependability of these networks.

Learning-based user association and dynamic resource allocation in multi-connectivity enabled unmanned aerial vehicle networks

Unmanned Aerial Vehicles (UAVs) as aerial base stations to provide communication services for ground users is a flexible and cost-effective paradigm in B5G. Besides, dynamic resource allocation and multi-connectivity can be adopted to further harness the potentials of UAVs in improving communication capacity, in such situations such that the interference among users becomes a pivotal disincentive requiring effective solutions. To this end, we investigate the Joint UAV-User Association, Channel Allocation, and transmission Power Control (J-UACAPC) problem in a multi-connectivity-enabled UAV network with constrained backhaul links, where each UAV can determine the reusable channels and transmission power to serve the selected ground users. The goal was to mitigate co-channel interference while maximizing long-term system utility. The problem was modeled as a cooperative stochastic game with hybrid discrete-continuous action space. A Multi-Agent Hybrid Deep Reinforcement Learning (MAHDRL) algorithm was proposed to address this problem. Extensive simulation results demonstrated the effectiveness of the proposed algorithm and showed that it has a higher system utility than the baseline methods.

Reference signal design to mitigate co-channel interference in 5G OFDM systems with multiple numerologies

The 5G cellular technology is expected to support diverse services by flexible use of the allocated spectrum. It is achieved by allowing multiple subcarrier spacing and dynamically changing downlink (DL) and uplink (UL) transmissions based on the instantaneous traffic and latency requirements. The problem of mitigating co-channel interference (CCI) with different subcarrier spacings becomes more challenging, and the dynamic DL–UL configuration makes it further difficult. In this paper, a reference signal design to measure the CCI is proposed along with detailed mathematical analysis. Furthermore, novel algorithms to estimate the CCI are proposed which along with advanced receivers are used to effectively mitigate the interference. Simulations are performed to evaluate the performance of reference signal design and the proposed estimation algorithms. The results confirm the efficacy of the proposed methods.

Active and Passive Components for Broadband Transmit Phased Arrays: Broadband Transmit Front-End Components

Phased-array antennas have penetrated a large application space, and in this article, we present some of the critical components for phased-array front ends, as described in <xref ref-type="fig" rid="fig1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Figure 1</xref> . We focus on an octave-bandwidth 6- to 12-GHz transmit implementation, but the methodology and component designs are scalable in frequency. Over the past few decades, phased-array applications have expanded from radar to wireless and satellite communications, as well as medical imaging and various sensing modalities. By tracking users with individual high-gain beams, spatial multiplexing enables cochannel interference mitigation, enhancing signal levels, and power management in wireless communications systems. For example, <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> shows a 64-element phased-array transceiver operating in the 28-GHz band with 52-dBm effective isotropic radiated power (EIRP) for 5G applications with up to 12 Gb/s of throughput, and <xref ref-type="bibr" rid="ref2" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[2]</xref> demonstrates a system-level development of a 384-element, 16-tile, W-band phased array with 52-dBm EIRP in 0.18-μm silicon–germanium bipolar CMOS (BiCMOS) technology. In satellite broadcasting and communication systems, phased-array antennas enable beam shaping over countries and continents, tracking at the end-user side, and rain fading mitigation, e.g., <xref ref-type="bibr" rid="ref3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[3]</xref> . In <xref ref-type="bibr" rid="ref4" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[4]</xref> , advances in phased arrays for satellite applications developed at Lockheed Martin are described from an industry perspective.

Intelligent Resource Management Using Multiagent Double Deep Q-Networks to Guarantee Strict Reliability and Low Latency in IoT Network

With the rapid adoption of the Internet of Things, it is necessary to go beyond fifth-generation applications and apply stringent high reliability and low latency requirements, closely related to strict delay demands. These requirements support massive network connectivity for multiple Internet of Things devices. Hence, in this paper, we optimize energy efficiency and achieve quality-of-service requirements by mitigating co-channel interference, performing efficient power control of transmitters, and harvesting energy using time-slot exchanges. Due to a nonconvex optimization problem, we propose an iterative algorithm for power allocation and time slot interchange to reduce the computational complexity. To achieve a high degree of ultra-reliability and low latency with quality-of-service-aware instantaneous reward under massive connectivity, we efficiently employ multiagent reinforcement learning by addressing the intelligent resource management problem via a novel Double Deep Q Network. The network prioritizes experience replay to exploit the best policy and maximize accumulative rewards. It also learns the optimal policy and enhances learning efficiency by maximizing its reward function to make decisions with high intelligence and guarantee strict ultra-reliability and low latency. The simulation result shows that the Double Deep Q Network with prioritized experience replay can guarantee stringent ultra-reliability and low latency. As a result, the co-channel interference between transmission links and the high-power consumption density associated with the massive connectivity of the Internet of Things devices are mitigated.

Distributed Channel Assignment for Ultra-Dense Wireless Networks Using Belief Propagation

An efficient channel assignment plays an important role in mitigating co-channel interference in ultra-dense wireless networks. A simple solution is to separate interfering network nodes into orthogonal channels to reduce the interference among them. However, determining the optimal channel assignment is considered to be a non-linear problem, which may also be associated with practical implementation issues such as high computational complexity and control signaling issues. In an effort to cope with these challenging issues, we propose a distributed channel assignment algorithm that efficiently finds the optimal channel configuration by utilizing the concept of belief propagation. Based on a message-passing framework, the proposed distributed channel assignment algorithm maximizes the overall sum rate of the ultra-dense network with a low computational load for each network node. In addition, we design a network protocol and frame format to implement the proposed message-passing framework to real-world wireless networks. The main advantage of the proposed approach is that network nodes autonomously determine the optimal channel assignment and rapidly adapt to dynamic changes of the network. Simulation results confirm that the proposed distributed channel assignment algorithm outperforms conventional algorithms in terms of various network performance aspects, such as the sum rate, scalability, latency, and user mobility.

A Graph Convolutional Network-Based Deep Reinforcement Learning Approach for Resource Allocation in a Cognitive Radio Network.

Cognitive radio (CR) is a critical technique to solve the conflict between the explosive growth of traffic and severe spectrum scarcity. Reasonable radio resource allocation with CR can effectively achieve spectrum sharing and co-channel interference (CCI) mitigation. In this paper, we propose a joint channel selection and power adaptation scheme for the underlay cognitive radio network (CRN), maximizing the data rate of all secondary users (SUs) while guaranteeing the quality of service (QoS) of primary users (PUs). To exploit the underlying topology of CRNs, we model the communication network as dynamic graphs, and the random walk is used to imitate the users’ movements. Considering the lack of accurate channel state information (CSI), we use the user distance distribution contained in the graph to estimate CSI. Moreover, the graph convolutional network (GCN) is employed to extract the crucial interference features. Further, an end-to-end learning model is designed to implement the following resource allocation task to avoid the split with mismatched features and tasks. Finally, the deep reinforcement learning (DRL) framework is adopted for model learning, to explore the optimal resource allocation strategy. The simulation results verify the feasibility and convergence of the proposed scheme, and prove that its performance is significantly improved.

Cooperative NOMA for Downlink Asymmetric Interference Cancellation

This letter advances the non-orthogonal multiple access (NOMA) technique for cellular downlink co-channel interference mitigation, via exploiting the (limited) cooperation among base stations (BSs). Specifically, we consider a simplified but practically relevant scenario of two co-channel cells with asymmetric interference, i.e., only the user in one cell receives the strong interference from the BS in the other cell. To mitigate such interference, we propose a new cooperative NOMA scheme, where the interfered user's serving BS sends a superposed signal comprising both the desired message and the co-channel user's message (shared by the interfering BS). The co-channel user's signal is aimed to add constructively with the interfering BS's signal at the interfered user's receiver so that the combined interference with enhanced power can be effectively decoded and cancelled. This thus leads to a new problem on how to optimally allocate the transmit power for the two superposed messages. We provide the closed-form solution to this problem and investigate the conditions under which the performance of the proposed scheme is superior over the existing schemes.

Fast Optimization Algorithm for Evanescent-Mode Cavity Tuner Optimization and Timing Reduction in Software-Defined Radar Implementation

Dynamic spectrum allocation will require cognitive radar transmitters to change operating frequency and bandwidth in real time. This will require high-power reconfigurable circuitry to improve radar performance by simultaneously increasing 1) the output power of the transmit waveform and 2) the power-added efficiency of the power amplifier. This circuitry is also used to mitigate cochannel interference by maintaining sufficiently linear performance so that the output waveform conforms to a given spectral mask. In this approach, a 90-W evanescent-mode cavity tuner is reconfigured using a specially designed gradient search to find the best combination of resonant cavity position numbers. This approach will be much more flexible for field use than typical Smith-chart-based load-pull searches, which require a characterization that is susceptible to drift. Experimental results are presented showing that the efficiency, output power, spectral performance, and estimated maximum radar detection range are improved significantly by retuning the matching network at each operating frequency. Additionally, this article discusses innovations to reduce or eliminate time bottlenecks in a cognitive radar system for impedance tuning, reducing the time needed for complete impedance tuning searches from minutes to seconds. This significant timing reduction makes tunable power amplifiers a feasible option for future use in spectrum sharing by cognitive radar systems.

DIYA: Tactile Internet Driven Delay Assessment NOMA-Based Scheme for D2D Communication

Device-to-device (D2D) two-hop cooperative communication improves the network coverage and throughput to provide the quality of service and quality of experience to the end users. Nonorthogonal multiple access (NOMA) can be used at the D2D transmitter to improve the spectral efficiency of the network. But, two-hop transmission with NOMA suffers from delay and interference from the neighboring nodes. To resolve the aforementioned issues, in this paper, we propose Tactile Internet (TI) driven delay assessment for D2D communication (DIYA) scheme, which works in two phases. In the first phase, a full duplex communication at relays (intermediate nodes) is used to have the first- and second-hop transmission simultaneously in the same time slot. Then, TI-based communication is used at D2D transmitter to increase the speed of transmission. In the second phase, pricing-based three-dimensional (3-D) matching is proposed to improve the throughput of the cell edge users along with the mitigation of cochannel interference. Also, the power of the D2D transmitter is optimized using successive convex approximation with low complexity, which converts the nonconvex optimization problem of subchannel allocation and power control into convex problem. Numerical results demonstrate that DIYA achieves higher throughput with reduced delay in comparison to other existing orthogonal multiple access (OMA) and NOMA-based schemes.

Distributed Stable Routing with Adaptive Power Control for Multi-Flow and Multi-Hop Mobile Cognitive Networks

In most existing routing algorithms for mobile ad hoc cognitive networks (MACNets), nodes are configured with a fixed even maximal transmission power. Links set up by such the algorithms often suffer from excessive co-channel interference, which significantly downgrades performance of MACNets because the link stability highly depends on not only node mobility but also co-channel interference. In this paper, we investigate how to improve route stability through jointly considering routing with adaptive power adjustment and mobility control. We first propose a set of power adjustment policies which dynamically sets up transmission power of cognitive nodes to enable the duration of links potentially interfered as long as possible. We, then, design a routing metric called integrated link stability (ILS) to quantitatively measure the link stability. This novel metric ILS considers both node mobility and channel interference. Finally, we propose a Joint Stable Routing and Adaptive Power Adjustment (J-SRAPA) algorithm for multi-flow and multi-hop MACNets, with the objective of maximizing network throughput. J-SRAPA dynamically adjusts the transmission power in a distributed way to mitigate co-channel interference and to improve channel utilization ratio accordingly, during both route setup and data transmission. NS2-based simulation results demonstrate that our J-SRAPA significantly outperforms related routing algorithms in terms of network throughput, end-to-end transmission delay, and packet loss ratio; and the higher channel interference degree MACNets experience, the more improvement our J-SRAPA will bring to the networks.

Doppler Effect Assisted Wireless Communication for Interference Mitigation

Doppler effect is a fundamental phenomenon that appears in wave propagation, where a moving observer experiences dilation or contraction of the wavelength of a wave. It also appears in radio frequency (RF) wireless communication when there exists a relative movement between the transmitter and the receiver, and is widely considered as a major impairment for reliable wireless communication. The current paper proposes Doppler assisted wireless communication (DAWC) that exploits Doppler effect and uses kinetic energy for co-channel interference (CCI) mitigation. The proposed system also exploits the propagation environment and the network topology and consists of an access point (AP) with a rotating drum antenna. The rotating drum receive antenna is designed in such a way that it shifts the interfering signals away from the desired signal band. This paper includes a detailed system model, and the results show that under favorable fading conditions, CCI can be significantly reduced. Therefore, it is anticipated that more sophisticated wireless systems and networks can be designed by extending the basic ideas proposed herein.

Interference and Resource management strategy for handover in femtocells

Interference in femtocells due to neighboring femtocells and macrocells is a major issue of two-tier networks. Handover should be made to reduce interference, if and only if, when resources are available. Otherwise, it will further degrade network performance. Resource management should be made in an efficient manner that will not cause interference between macrocells and neighboring femtocells. Since distance between macro base station (MBS) and femto access point (FAP) is short, therefore, it is very hard to sustain low handover probability when macro user moves from MBS to FAP. We proposed handover algorithm for uplink co-channel interference mitigation that will make handover decision on the basis of time-to-stay and signal to interference plus noise ratio thresholds along with efficient resource management mechanism to reduce number of handovers and also resolve interference problem.

MF-TDMA Scheduling Algorithm for Multi-Spot Beam Satellite Systems Based on Co-Channel Interference Evaluation

Very high throughput satellites (VHTS) are the new trend in satellite communications systems in order to satisfy the increasing demand for both higher throughput and ubiquitous connectivity. Implementing an IP interactive network over a VHTS would enable the satellite to compete with terrestrial networks by offering ubiquitous added value services for end-user traffic. Even so, the simulations presented in this paper show that a 30% of throughput can be lost due to co-channel interferences. In existing interactive satellite networks such as REDSAT or AmerHis, the return uplink transmissions are inherently benefited from the MF-TDMA scheduling to mitigate the co-channel interferences present in VHTS. In such networks dynamic resource assignation (DAMA) is executed at each SuperFrame period (<100 ms). Therefore, any feasible optimization on the scheduling shall be performed in real time. In this paper, two parallel problems are faced at the same time: co-channel interference mitigation and real time scheduling. In particular, two novel interference-aware scheduling algorithms for a DVB-RCS2 return uplink are presented. Despite other previous works, the proposed algorithms are designed on the basis to be executed in real time on a fixed SuperFrame period basis. The performance assessment of the proposed algorithms is carried out through system-level simulations based on realistic satellite scenarios and interactive traffic models using DAMA in real time.

Antenna array techniques for nonuniform cell zooming and adaptive frequency planning

SummaryThis paper proposes the antenna array system and the techniques for the nonuniform cell zooming and adaptive frequency planning which is suitable for the energy‐efficient LTE network and multitier 5G heterogeneous network. The antenna array system is designed for the beam width control and scan control in the azimuth plane. The beam tilt is controlled in the elevation plane to control the cell radius. The first feature of the antenna array system is to perform nonuniform sector size control in order to deal with the nonuniform traffic distribution. The second feature of the antenna array system is to control the beam scan in the azimuth plane for the adaptive frequency planning. The footprint control of the current work is evaluated considering the antenna array's radiation pattern and all the physical parameters. Adaptive frequency planning can mitigate cochannel interference (CCI), which may be caused due to the cell zooming techniques proposed in this work. The footprint simulations confirm that the antenna array system can control the sector size with the highest possible flexibility. The antenna array system due to these features can effectively mitigate the interference. The results also confirm that the current antenna array system outperforms the existing antenna array systems.

Time-Frequency Energy Sensing of Communication Signals and Its Application in Co-Channel Interference Suppression.

As the number of mobile users and video traffics grow explosively, the data rate demands increase tremendously. To improve the spectral efficiency, the spectrum are reused inter cell or intra cell, such as the ultra dense network with multi-cell or the cellular network with Device-to-Device communications, where the co-channel interferences are brought and needs to be suppressed. According to the time-frequency energy sensing to the communication signals, the desired signal and the interference signal have different energy concentration areas on the time frequency plane, which provide opportunities to suppress the co-channel interference with time varying filter. This paper analyzes the time-frequency distributions of the Gaussian pulse shaping signals, discusses the effect of the analyzing window length on the time-frequency resolution, exploits the equivalence between the time frequency analysis at the baseband and at the radio front end, and finally reveals the advantages of the proposed masking threshold constrained time varying filter based co-channel interference mitigation method. The pass region for the linear time varying filter is generated according to the time-varying energy characteristics of the I/Q separated 4-QAM pulse shaping signals, where the optimum masking threshold is obtained by the optimum-BER criterion. The proposed co-channel interference suppression method is evaluated in aspect of BER performance, and simulation results show that the proposed method outperforms existing methods with low-pass or band-pass filters.

Priority Access and General Authorized Access Interference Mitigation in the Spectrum Access System

To meet the capacity needs of next generation wireless communications, the U.S. Federal Communications Commission has recently introduced the spectrum access system. Spectrum is shared between three tiers—incumbents, priority access licensees (PAL), and general authorized access (GAA) licensees. When the incumbents are absent, PAL and GAA share the spectrum under the constraint that GAA ensure the interference to PAL is no more than $-$ 40 dBm with at least 99% confidence. We consider the scenario where locations are not shared between PAL and GAA. We propose a PAL–GAA cochannel interference mitigation technique that does not expose base station locations. Our approach relies on GAA sharing the distribution and maximum number of transmitters in a finite area. We show how PAL can derive the distribution of the aggregate interference using the probability density function and characteristic function, and notify GAA about the exclusion zones in space that will guarantee that the interference requirement is met. We also propose a numerical approximation using inverse fast Fourier and discrete Fourier transforms. Analytically calculated distribution aligns well with the numerical results. Additionally, we formulate an optimization problem for the optimal exclusion zone size. We analytically prove convexity of the problem. Our approach reduces the exclusion zone size by over 42%, which gives significantly more spectral opportunities to GAA in the spatial domain.

Fair Optimal Resource Allocation in Cognitive Radio Networks With Co-Channel Interference Mitigation

In this paper, we study the utility fairness resource allocation in a multi-user orthogonal-based cognitive radio network with cochannel interference (CCI) mitigation. In our proposed system model, we introduce the correct reception probability (CRP) model as a network utility metric. Furthermore, useful bounds on CRP are derived to analyze the performance of proposed allocation schemes. The optimal resource allocation is formulated as a worst-case user CRP maximum problem with both average CCI and average power budget constraints. However, this problem is non-convex and generally challenging to solve. Therefore, we solve this problem by successively performing subchannel allocation and power allocation. Firstly, a $k$ -means clustering inspired subchannel allocation strategy is proposed to divide secondary users (SUs) into multiple groups by minimizing the average mutual-signal-to-interference-ratio degree between any two SUs. The concept of reference user is employed to guarantee the quality of service of the primary user. In each subchannel, we formulate a max-min utility optimal power allocation problem. The non-linear Perron Frobenius theory is applied to solve this power allocation problem. Simulation results show that the proposed resource allocation scheme is fair and has relatively fast convergence.