Interference Management Techniques Research Articles

Antijamming Schemes for the Generalized MIMO Y Channel.

Signal space alignment (SSA) is a promising technique for interference management in wireless networks. However, despite the excellent work done on SSA, its robustness against jamming attacks has not been considered in the literature. In this paper, we propose two antijamming strategies for the SSA scheme applied in the multiple-input-multiple-output (MIMO) Y channel. The first scheme involves projecting the jamming signal into the null space of each source's precoding vectors, effectively eliminating it entirely. The second scheme removes interference originating from the jammer by subtracting the disturbance estimate from the incoming signal. The estimate is derived on the basis of the criterion of minimizing the received signal energy. The block error rate (BLER) performance of the proposed strategies in various channel configurations is verified by link level simulations and is presented to show the efficiency in mitigating jamming signals within the SSA-based MIMO Y channel.

Joint uplink-downlink user-cell association for ultra-dense NOMA networks

As wireless communication systems evolve, the transition from homogeneous structures to heterogeneous ones intensifies. The need for continuous connectivity, fairness, and spectrum efficiency, such as in massive Internet of Things (IoT) networks and ultra reliable low latency communications (uRLLC), necessitates the utilization of base stations with diverse capabilities and coverage areas. As a result, the need for advanced interference management, user-cell association, and resource allocation techniques increases. This study proposes an innovative solution for the problem of non-orthogonal multiple access (NOMA) user-cell association in multi-tier ultra-dense heterogeneous networks (UD-HetNet). The proposed network constitutes a general framework that can be applied to next generation cellular communications, massive IoT, non-terrestrial and uRLLC type communications. Differing from previous studies that ignore interference and primarily focus on the received signal powers for user-cell association, this investigation advances the subject by considering the interplay between downlink received signal/interference power and uplink inter-cell interference. Due to the non-convex integer programming nature of the problem, it is proposed to employ an innovative relaxation algorithm to obtain a sub-optimal solution for the total signal-to-interference-plus-noise ratio (SINR). As verified through simulation results, the proposed association method permits concurrent communication participation of multiple users while managing the interference, rendering it as an ideal approach for systems emphasizing fairness and continuous connectivity.

Resource allocation-aware efficient interference management technique for ultra-dense Femto environment

Addressing the challenge of severe inter-layer and intra-layer interference in densely deployed Femtocells, we introduce an efficient resource allocation strategy centered on clustering. Initially, we employ the Fractional Frequency Reuse (FFR) technique to mitigate interference by segmenting cells into distinct zones.Subsequently, leveraging graph theory and convex optimization, we cluster the Femto Base Stations (FBS) to enhance efficiency. An algorithm prioritizing user fairness governs sub-channel allocation among FBSs. Additionally, a distributed power control algorithm dynamically adjusts FBS power levels, further enhancing system throughput. Comparative analysis reveals that our approach surpasses traditional non-clustered methods and three other comparison methods, exhibiting superior system throughput and Signal-to-Interference Ratio (SINR). Notably, our method significantly enhances user fairness, promoting greater satisfaction among Femto User Equipment (FUE) users.

Joint downlink user association and interference avoidance with a load balancing approach in backhaul-constrained HetNets.

In heterogeneous networks (HetNets), different lower-power base stations are added in a typically unplanned manner to the well-planned macro-only network, bringing new challenges to the network functions. Small cells experience limited backhaul capacity since cost-effective backhaul is not easily accessible to them. This study focuses on the issue of user association in backhaul-constrained HetNets. It shows that it is necessary to associate users with cells using a load balancing approach in order to fully leverage the addition of small cells. The cell association needs to be done jointly with an interference management technique that protects offloaded users and those prone to harmful interference. After modeling the system and describing the interference model, the problem of cell and subband allocation is formulated. We first examine the problem in a time-sharing mode and present a centralized heuristic solution to the cell and subband allocation problem. This is accomplished by solving the convex problem using the gradual removal method. The importance of providing distributed algorithms for HetNets leads to the development of a new algorithm through the application of the dual decomposition method to a reformulated problem and the use of an admission control mechanism. In the achieved algorithm, all computations are performed locally, with each user and base station relying only on local information. This algorithm obtains near-optimal answers, as confirmed by the simulation results. Compared with conventional cell allocation methods, our distributed algorithm prevents intensive interference for all users and achieves better load balance between network tiers, resulting in improved network utility.

Interference Management Based on Clustering Method for Ultra-Dense Networks in Multicellular Network

One of solutions to address the increasing demands for data traffic by mobile users is to implement ultra dense network (UDN). UDN consists of many femtocells that are densely deployed on macrocellular communication networks. Since femtocells radius is very short and they are tightly packed, it faces interferences problem i.e., co-tier and cross-tier interferences. This paper proposes interference management technique based on clustering method for UDN multicellular communication networks at downlink transmission. It is purposed to reduce interference effects. To evaluate the proposed clustering method, two simulation scenarios have been designed; namely baseline system and system with the proposed clustering method. The scenarios applied is to randomly distribute femtocells following a uniform distribution in three macrocells areas. Through a clustering algorithm, adjacent femtocells are grouped into one cluster and assigned different frequency channels for each femtocell in that cluster. The same cluster pattern is repeated for all femtocells. Thus, interference effect is canceled within one cluster and reduced among clusters by widening the distance among femtocells that use the same frequency channels. Through simulation experiment, the proposed clustering method is evaluated and compared to the baseline system. The simulation results show that Signal to Interference plus Noise Ratio (SINR) of femtocells increases 0.44 dB, throughput increases 1.67%, Bit Error Rate (BER) reduces, and other parameters improve as well which include spectral efficiency, network energy, and average network energy. The proposed clustering method increases performances of the networks and provides better solution for transmission data speed in densely femtocell network.

Data-Driven Spectrum Allocation and Power Control for NOMA HetNets

Towards a green communication discipline, more energy-efficient wireless networks are needed. In this paper, an energy-efficient interference management technique is proposed for heterogeneous networks (HetNets) with downlink nonorthogonal multiple access (NOMA) operating in millimeter (mm) waves. The proposed technique utilizes data-driven-based power and resource blocks (RBs) allocation scheme to maximize the energy efficiency of the entire network while managing inter-user, co-tier, and cross-tier interference. The studied interference management problem is mathematically formulated as maximizing the energy efficiency of NOMA-HetNets under constraints; quality of service (QoS), successive interference cancelation condition (SIC), maximum power allocation, and the maximum capacity of each RB, which is a non-convex and combinatorial NP-hard problem that needs exhaustive search for an optimum solution. The formulated problem is relaxed into a minimization of a linear <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> -norm problem. Then, a lowcomplex model-free data-driven based approach is proposed to find a near-optimum allocation for power and RBs based on a dynamic linearization representation of a time-varying pseudogradient parameter estimation procedure. Numerical analyses show that the proposed scheme achieves higher network energy efficiency with lower computational complexity compared to the benchmark schemes.

Energy-Efficient Power Allocation for Full-Duplex Device-to-Device Underlaying Cellular Networks with NOMA

Full-duplex (FD), Device-to-Device (D2D) and non-orthogonal multiple access (NOMA) are promising wireless communication techniques to improve the utilization of spectrum resources. Meanwhile, introducing FD, D2D and NOMA in cellular networks is very challenging due to the complex interference problem. To deal with the complex interference of FD D2D underlaying NOMA cellular networks, power allocation (PA) is extensively studied as an efficient interference management technique. However, most of the previous research works on PA to optimize energy efficiency only consider the system framework of partially joint combining techniques of FD, D2D and NOMA, and the constraints of optimization problem are very different. In this paper, in order to further improve the energy efficiency of a system, a dual-layer iteration power allocation algorithm is proposed to eliminate the complex interference. The outer-layer iteration is to solve the non-linear fractional objective function based on Dinkelbach, and the inner-layer iteration is to solve the non-convex optimization problem based on D.C. programming. Then, the non-convex and non-linear fractional objective function is transformed into a convex function to solve the optimal power allocation. In this approach, FD D2D users reuse the spectrum with downlink NOMA cellular users. Imperfect self-interference (SI) cancellation at the FD D2D users and the successive interference cancellation (SIC) at the strong NOMA user are considered in the system framework. The optimization problem is constructed to maximize the system’s energy efficiency with the constraints of successful SIC, QoS requirements, the maximum transmit power of BS and FD D2D users. Numerical results demonstrate that the proposed algorithm outperforms the traditional orthogonal multiple access (OMA) in terms of energy efficiency with a higher system sum rate.

Selective interference alignment and neutralization in coordinated multipoint using multiuser MIMO

SummaryIn wireless communication, the concept of coordinated multipoint (CoMP) transmission is more attractive, and it transpired the notion based on interference management techniques. Interference alignment (IA) and interference neutralization (IN) methods can substantially align and neutralize the interference signals. The existing work in the CoMP transmission using multiuser multi‐input and multi‐output (MU‐MIMO) had long‐held problems such as specific limit of intercell (ICI) and cochannel interference (CCI) cancelation that contain low performance in cell‐edge users. The proposed framework of the transmission signal in selective interference alignment and neutralization (SIAN) CoMP MU‐MIMO system transmits multiple data streams in multipath by using downlink coordination between base stations and receiver side. This work contributes the individual perspectives to implement the IA and IN to align and cancel the interfered signals at the receiver side. Once the perspectives mentioned above are executed, zero‐forcing (ZF) and rechanneling filter are applied on the receiver side to eliminate residual ICI. In addition, spectral efficiency significantly improves the achievable data rate and enhances the performance of cell‐edge users and reduces the CCI at the receiver side. Furthermore, the antenna configuration signals are decoded to get the exact version of interference‐free signals with null path loss of signal transmission. The effectiveness of the proposed framework analyzes and verifies the numerical evaluation of the achievable degree of freedom. Finally, the simulation demonstrates the comparison of the proposed CoMP scheme with MIMO ZF and non‐CoMP schemes, which significantly improve the performance of spectral efficiency for cell‐edge users.

Rate Splitting in MIMO RIS-Assisted Systems With Hardware Impairments and Improper Signaling

In this paper, we propose an optimization framework for rate splitting (RS) techniques in multiple-input multiple-output (MIMO) reconfigurable intelligent surface (RIS)-assisted systems, possibly with I/Q imbalance (IQI). This framework can be applied to any optimization problem in which the objective and/or constraints are linear functions of the rates and/or transmit covariance matrices. Such problems include minimum-weighted and weighted-sum rate maximization, total power minimization for a target rate, minimum-weighted energy efficiency (EE) and global EE maximization. The framework may be applied to any interference-limited system with hardware impairments. For the sake of illustration, we consider a multicell MIMO RIS-assisted broadcast channel (BC) in which the base stations (BSs) and/or the users may suffer from IQI. Since IQI generates improper noise, we consider improper Gaussian signaling (IGS) as an interference-management technique that can additionally compensate for IQI. We show that RS when combined with IGS can substantially improve the spectral and energy efficiency of overloaded networks (i.e., when the number of users per cell is larger than the number of transmit/receive antennas).

NOMA-Based Improper Signaling for Multicell MISO RIS-Assisted Broadcast Channels

In this paper, we study the performance of reconfigurable intelligent surfaces (RISs) in a multicell broadcast channel (BC) that employs improper Gaussian signaling (IGS) jointly with non-orthogonal multiple access (NOMA) to optimize either the minimum-weighted rate or the energy efficiency (EE) of the network. We show that although the RIS can significantly improve the system performance, it cannot mitigate interference completely, so we have to employ other interference-management techniques to further improve performance. We show that the proposed NOMA-based IGS scheme can substantially outperform proper Gaussian signaling (PGS) and IGS schemes that treat interference as noise (TIN) in particular when the number of users per cell is larger than the number of base station (BS) antennas (referred to as overloaded networks). In other words, IGS and NOMA complement to each other as interference management techniques in multicell RIS-assisted BCs. Furthermore, we consider three different feasibility sets for the RIS components showing that even a RIS with a small number of elements provides considerable gains for all the feasibility sets.

Handling Interference in Integrated HAPS-Terrestrial Networks Through Radio Resource Management

Vertical heterogeneous networks (vHetNets) are promising architectures to bring significant advantages for 6G and beyond mobile communications. High altitude platform station (HAPS), one of the nodes in the vHetNets, can be considered as a complementary platform for terrestrial networks to meet the ever-increasing dynamic capacity demand and provide sustainable wireless networks for future. However, the problem of interference is the bottleneck for the optimal operation of such an integrated network. Thus, designing efficient interference management techniques is inevitable. In this letter, we aim to design a joint power-subcarrier allocation scheme in order to achieve fairness for all users. We formulate the max-min fairness (MMF) optimization problem and develop a rapid converging iterative algorithm to solve it. Numerical results validate the superiority of the proposed algorithm and show better performance over other conventional network scenarios.

Closed-Form Sum-Rate Analysis of Interference Alignment with Limited Feedback Based on Scalar Quantization and Random Vector Quantization

Interference alignment (IA) is a promising interference management technique to achieve the theoretical optimal degree of freedom (DoF) performance in multi-user cooperation scenarios. However, the effective achievable sum-rate performance of IA is largely affected by the feedback overhead and accuracy of channel state information (CSI) and decoding information (DI). Therefore, it is critical to establish the exact relationship between feedback overhead and the achievable sum-rate of IA to obtain the optimal effective performance. Most existing IA performance analysis approaches focus on the vector quantization (VQ)-based feedback strategy, but the implementation complexity of VQ will be excessive when more quantization bits are required to achieve the expected quantization accuracy for larger-sized matrices or higher signal-to-noise ratio (SNR) regimes. Moreover, the obtained achievable sum-rate formulas are too complicated for quick performance evaluation. In this paper, a new sum-rate performance analysis method for IA under different quantization and feedback strategies is proposed to achieve a trade-off between accuracy and complexity, and the closed-form achievable sum-rate expressions are derived. First, in the IA case with random vector quantization (RVQ)-based CSI feedback, the quantization error of RVQ is transformed into the equivalent VQ error of the Gaussian channel error, based on which the achievable sum-rate formula is obtained. Second, in the IA case with scalar quantization (SQ)-based CSI feedback, the relationship between the effective sum-rate and SQ bits is established. Third, in the IA case with SQ-based CSI feedback and RVQ-based DI feedback, the achievable sum-rate formula is derived by combining these two kinds of quantization errors. Finally, the simulation results confirm that the theoretical results are accurate enough, which can help to determine the optimal CSI feedback overhead in practical channel conditions. Moreover, the theoretical and simulation results demonstrate that RVQ may be more applicable to IA scenarios with fewer receiving antennas and low SNR regimes.

Traffic Load-Based Spectrum Trading between Two Mobile Network Operators in HetNets Using Interference Management Technique

The pursuit of achieving higher data rates in 5G and beyond has triggered numerous technological advancements. One of these is spectrum sharing between Mobile Network Operators (MNOs). In this work, we investigate the spectrum trading between two MNOs with disparate traffic loads in heterogeneous networks. A radio resource sharing technique is proposed that exploits resource block allocation with Interference Range (RBIR) to reduce interoperator interference prompted by spectrum trading. In addition, an algorithm for cooperative load-based spectrum trading at resource block level is proposed for two MNOs with asymmetric traffic load. Two main approaches for spectrum trading, i.e., spectrum sharing (Load-Based Shared Spectrum Pool (LSSP)) and spectrum leasing (Load-Based Leased Spectrum Pool (LLSP)) are analysed, and a heterogeneous network is modeled such that both operators have a dedicated spectrum for their macro and small cell networks. Prior to spectrum trading, a conventional resource block allocation technique is used in which resource blocks from a shared or leased spectrum pool are assigned so that each user experiences the least amount of interference. The performance of LSSP and LLSP is evaluated while taking into account the constraints of both operators, such as net throughput and user satisfaction. Moreover, we evaluate the network performance with increasing interference range as small cells of different transmission/interference range that are present in the network. The performance evaluation demonstrates that when the interference is lesser, as represented by the radius of the interference range, the spectrum sharing is more advantageous in terms of delivering higher average data rates. However, when the interference is higher, then leasing is more beneficial.

Interference Management for the Coexistence of DTTV and LTE Systems within the Proposed Digital Dividend Band in Nigeria

This paper seeks to present the Interference Management for the Coexistence of DTTV and LTE Systems within the proposed digital dividend band in Nigeria. The study focused on LTE Down-link (DL) signal from the nearest cell site interfering with the Digital Terrestrial Television (DTTV) fixed outdoor receiving antenna in Port Harcourt, Nigeria. The qualitative signal analysis of the DTTV systems is essential as DTTV system cannot start to operate in the newly formed frequency band without the evaluation of the possible harmful influence of the coexisting systems. This research work investigated the Compatibility of the two systems and the Probability of interference of Channel 17 (490MHz) and Channel 51 (693MHz) when DTTV and LTE systems coexist within the proposed Digital Dividend band. A test-bed approach method was adopted for the generation of the required simulation data. Star Time transmitting Station in Port Harcourt and Smile LTE 4G Communication LTE Base Station (eNBs) Network also in Port Harcourt were adopted as the Victim Link Transmitter (VLT) and Interfering Link Transmitter (ILT) respectively. Data was obtained, analyzed, and evaluated. It was observed from the simulation result that the probability of interference is a function of the separation distance between ILT and VLR. The Compatibility analysis result shows that the resulting C/I is above the protection criteria (19dB), that is there’s a minimal rate of interference. Hence, the interference issue can be managed when the two systems coexist in700MHz band. It was also established that DTTV channel 51 suffers more interference when compared with DTTV channel 17 for the same separation distance. The study recommended the minimum protection distance approach (Interference Avoidance method) as the interference management techniques when DTTV and LTE systems coexist in the proposed digital dividend (700MHz) band in Nigeria.

On the Stability Region of Intermittent Interference Networks

Recent information-theoretic studies have resulted in several interference management (IM) techniques that promise significant capacity improvements over interference avoidance techniques. However, in practice, the stable throughput region is a more relevant metric compared to the capacity region. In this work, we focus on the stable throughput region of a two-pair intermittent interference network with distributed transmitters and propose a queue-based transmission protocol in different regimes to handle the data between queues. In this context, we translate physical-layer IM protocols to accommodate stochastic message arrivals. To evaluate our proposed techniques, we compare the stable throughput region to the capacity region and show, through simulations, that the stable throughput region matches the capacity region when the latter is known. We show that in order to achieve the optimal stable throughput region, new ingredients are needed when compared to prior results. We quantify the trade-off between encoding/decoding complexity of the proposed scheme (in terms of number of required algebraic operations), and the achievable rates. Finally, we study the lifetime of messages (i.e. the duration from arrival to successful delivery) versus the total communication time, and we observe that the average lifetime scales as the square root of the total communication time.

Harmonious wireless networks: Perspective of interference management

This paper elaborates on the harmonious wireless network from the perspective of interference management. The coexistence of useful signals and interfering signals is beneficial in throughput terms of the entire wireless network. Useful signals and interfering signals are complementary and are in juxtaposition to each other in the context of a single communication link, and are in symbiosis within the framework of the networks. The philosophy behind this could be described by the Chinese traditional culture symbol of “yin” and “yang”. A wireless network having optimal performance must be a harmonious network where the interfering and useful signals harmoniously coexist in an optimal balance. Interference management plays a critical role in achieving this optimal balance, while sophisticated interference management techniques should be designed to improve the system performance.

Deployment of Clustered-Based Small Cells in Interference-Limited Dense Scenarios: Analysis, Design, and Trade-Offs

Network densification is one of the most promising solutions to address the high data rate demands in 5G and beyond (B5G) wireless networks while ensuring an overall adequate quality of service. In this scenario, most users experience significant interference levels from neighbouring mobile stations (MSs) and access points (APs) making the use of advanced interference management techniques mandatory. Clustered interference alignment (IA) has been widely proposed to manage the interference in densely deployed scenarios with a large number of users. Nonetheless, the setups considered in previous works are still far from the densification levels envisaged for 5G/B5G networks that are considered in this paper. Moreover, prior designs of clustered-IA systems relied on oversimplified channel models and/or enforced single-stream transmission. In this paper, we explore an ultradense deployment of small cells (SCs) to provide coverage in 5G/B5G wireless networks. A novel cluster design based on a size-restrictedk-means algorithm to divide the SCs into different clusters is proposed taking into account path loss and shadowing effects, thus providing a more realistic solution than those available in the current literature. Unlike previous works, this clustering method can also cater for spatial multiplexing scenarios. Also, several design parameters such as the number of transmit antennas, multiplexed data streams, and deployed APs are analyzed in order to identify trade-offs between performance and complexity. The relationship between density of network elements per area unit and performance is investigated, thus allowing to illustrate that there is an optimal coverage area value over which the network resources should be distributed. Moreover, it is shown that the spectral-efficiency degradation due to the intercluster interference in ultradense networks (UDNs) points to the need of designing an interference management algorithm that accounts for both intracluster and intercluster interferences. Simulation results provide key insights for the deployment of small cells in interference-limited dense scenarios.

Alignment Chain-Based Closed-Form IA Solution for Multiple User MIMO Interference Networks

As a potential interference management technique, interference alignment (IA) can enormously improve the system capacity in the future mobile communication networks. However, the general closed-form IA solution in the multiple user scenario is still an open problem, which hinders the implementation due to the high complexity of iterative IA design. In this paper, a alignment chain-based closed-form IA solution scheme is proposed for generalized $K (K > 3)$ -user multiple-input multiple-output (MIMO) interference channel. The alignment chains are sophisticatedly designed, on the basis of compressing the interference subspace and improving the degree of freedom (DoF) as much as possible. Then based on the alignment chains, the alignment chain equations are built, and the least-squares IA solution with optimal DoF or the exact IA solution with reduced DoF is provided, by using the theory of matrices. A series of simulation experiments are carried out to verify the proposed closed-form IA solution, and simulation results demonstrate its effectiveness and low computational complexity.

Joint Interference Alignment and Power Allocation Based on Stackelberg Game in Device-to-Device Communications Underlying Cellular Networks

As a promising wireless communication technique, Device-to-Device (D2D) can improve the utilization of spectrum resources, overall system throughput and reduce end-to-end delay, energy consumption by exploiting the direct radio link between local devices. Meanwhile, introducing D2D in cellular networks is very challenging due to the complex interference problem. To deal with the complex interference of D2D Underlying Cellular Networks, Interference alignment (IA) as an efficient interference management technique is extensively studied for D2D communications underlaying the cellular networks. However, most of the previous researches on IA only consider the equal power allocation for users, which leads to suboptimal overall system throughput. In order to further improve the system performance, in this paper, we propose a joint power allocation based on stackelberg game and interference alignment algorithm (STPA-IA) to eliminate the complex interference in D2D communications underlaying cellular networks. In this joint approach, the base station (BS) is modeled as the leader while the D2D pairs are followers. The performance of network system and that of D2D users are regarded as the revenues of leader and followers in stackelberg game. The strategy of the leader (BS) is to get the maximum benefits by reducing the interference, while the followers tend to (D2D pairs) maximize their own utility according to leader's strategy. The non-cooperative game is proved to get the nash equilibrium by the above strategies. Moreover, the close-form expression of the allocated power by maximum the unity function of leader and followers is derived. Extensive simulation results demonstrate that the proposed algorithm outperforms previous works in terms of sum-rate with lower time complexity.

Interference management in 6G space and terrestrial integrated networks: Challenges and approaches

The Space-Terrestrial Integrated Network (STIN) is considered to be a promising paradigm for realizing worldwide wireless connectivity in sixth-Generation (6G) wireless communication systems. Unfortunately, excessive interference in the STIN degrades the wireless links and leads to poor performance, which is a bottleneck that prevents its commercial deployment. In this article, the crucial features and challenges of STIN-based interference are comprehensively investigated, and some candidate solutions for Interference Management (IM) are summarized. As traditional IM techniques are designed for single-application scenarios or specific types of interference, they cannot meet the requirements of the STIN architecture. To address this issue, we propose a self-adaptation IM method that reaps the potential benefits of STIN and is applicable to both rural and urban areas. A number of open issues and potential challenges for IM are discussed, which provide insights regarding future research directions related to STIN.