Inter-cluster Interference Research Articles

Interference Avoidance through Periodic UAV Scheduling in RIS-Aided UAV Cluster Communications

This article investigates the transmission of downlink control signals for multiple unmanned aerial vehicle (UAV) clusters in collaborative search and rescue operations in mountainous environments. In this scenario, a reconfigurable intelligent surface (RIS) mounted on the UAV is utilized to overcome obstacles between the ground base station (BS) and UAVs. By leveraging the fixed channel of the RIS to the BS, the line-of-sight (LoS) path characteristics of the air-to-air channel, and the position information of the UAV, the RIS forms a directional beam by adjusting the RIS coefficient, which points towards UAVs in the cluster. To ensure low delay in control signaling and UAV state transmission, we adopt semi-persistent scheduling (SPS), which allocates pre-specified periodic intervals to each UAV for the formation of corresponding RIS coefficients. The allocation of time slots is constrained by the transmission intervals required by different UAVs and the number of RISs available. We propose a time slot scheduling scheme for UAVs to reduce inter-cluster interference caused by RIS beams. The time slot allocation problem is formulated as a combinatorial optimization problem. To solve this problem, we first propose an intuitive greedy scheme called local interference minimization (LIM). Building upon the LIM scheme, we propose a rollout-based algorithm called rollout interference minimization (RIM). Through simulation, we compare the LIM and RIM schemes with the benchmark scheduling scheme. The results demonstrate that our proposed scheme significantly reduces interference between UAV clusters while satisfying the conditions of periodic transmission and RIS quantity constraints.

Energy-Efficient Beamforming and Resource Optimization for AmBSC-Assisted Cooperative NOMA IoT Networks

In this manuscript, we present an energy-efficient alternating optimization framework based on the multi-antenna ambient backscatter communication (AmBSC) assisted cooperative non-orthogonal multiple access (NOMA) for next-generation (NG) internet-of-things (IoT) enabled communication networks. Specifically, the energy-efficiency maximization is achieved for the considered AmBSC-enabled multi-cluster cooperative IoT NOMA system by optimizing the active-beamforming vector and power-allocation coefficients (PAC) of IoT NOMA users at the transmitter, as well as passive-beamforming vector at the multi-antenna assisted backscatter node. Usually, increasing the number of IoT NOMA users in each cluster results in inter-cluster interference (ICI) (among different clusters) and intra-cluster interference (among IoT NOMA users). To combat the impact of ICI, we exploit a zero-forcing (ZF) based active-beamforming, as well as an efficient clustering technique at the source node. Further, the effect of intra-cluster interference is mitigated by exploiting an efficient power-allocation policy that determines the PAC of IoT NOMA users under the quality-of-service (QoS), cooperation, SIC decoding, and power-budget constraints. Moreover, the considered non-convex passive-beamforming problem is transformed into a standard semi-definite programming (SDP) problem by exploiting the successive-convex approximation (SCA) approximation, as well as the difference of convex (DC) programming, where Rank-1 solution of passive-beamforming is obtained based on the penalty-based method. Furthermore, the numerical analysis of simulation results demonstrates that the proposed energy-efficiency maximization algorithm exhibits an efficient performance by achieving convergence within only a few iterations.

UAV-Assisted Multi-Cluster Over-the-Air Computation

In this paper, we study unmanned aerial vehicles (UAVs) assisted wireless data aggregation (WDA) in multi-cluster networks, where multiple UAVs simultaneously perform different WDA tasks via over-the-air computation (AirComp) without terrestrial base stations. This work focuses on maximizing the minimum amount of WDA tasks performed by each cluster by optimizing the UAV trajectory and transceiver design as well as cluster scheduling and association, while considering the WDA accuracy requirement. Such a joint design is critical for interference management in multi-cluster AirComp networks, via enhancing the signal quality between each UAV and its associated cluster for signal alignment while reducing the inter-cluster interference between each UAV and its non-associated clusters. Although it is generally challenging to optimally solve the formulated non-convex mixed-integer nonlinear programming, an efficient iterative algorithm as a compromise approach is developed by exploiting bisection and block coordinate descent methods, yielding an optimal transceiver solution in each iteration. The optimal binary variables and a suboptimal trajectory are obtained by using the dual method and successive convex approximation, respectively. Simulations show the considerable performance gains of the proposed design over benchmarks and the superiority of deploying multiple UAVs in increasing the number of performed tasks while reducing access delays.

Outage Performance and Ergodic Capacity of User Pairing in Downlink MIMO-NOMA systems with Imperfect SIC Over Nakagami-m Fading Channels

Non-orthogonal multiple access (NOMA) has been envisaged as a key driving scheme for future wireless communication systems because of its huge connecting ability and superior spectrum efficiency. Integrating the concepts of Multiple-input-multiple-output (MIMO) into NOMA enhance the system capacity at the cost of hardware complexity. In this article, we consider an MIMO-NOMA-based system in which the users are partitioned to form a cluster. A beamforming vector that helps to maximize the channel gain has been designed to remove the inter-cluster interference. This work presents the effect of user pairing in downlink MIMO-NOMA systems. User pairing has a significant impact on the performance of MIMO-NOMA systems. Outage probability and Ergodic Capacity (EC) are analyzed for MIMO-NOMA systems. Exact outage probability expressions are provided for user pairing to reveal some useful insights that pairing two users with dissimilar channel conditions increases the probability that NOMA achieves a larger sum rate than traditional orthogonal multiple access (OMA) systems. This mathematical investigation is carried out by considering Nakagami-m fading channel. Furthermore, this notion of user pairing is presented for imperfect successive interference cancellation (SIC). Diversity order is also derived for the strong and weak users. Extensive simulation results are provided to validate the derived analytic expressions. Furthermore, it is also demonstrated that the EC of MIMO-NOMA systems is improved significantly when compared with traditional OMA systems.

Energy-Efficient Resource Allocation for NOMA HetNets in Millimeter Wave Communications

The integration of millimeter-wave (mmWave) and non-orthogonal multiple access (NOMA) has attracted academic and industrial interest as a promising enabling approach due to their massive bandwidth support and greater spectral efficiency. In this paper, we consider NOMA heterogeneous network (HetNet) in mmWave communications, consisting of the macro-cell and small cell tiers connected through the wireless backhaul. Following this, we propose a user grouping algorithm to significantly simplify the user clustering process where each cluster consists of highly correlated users to suppress the inter-cluster interference. We then propose a hybrid analog/digital precoding scheme at the macro base station. The goal is to maximize the system’s total energy-efficiency (EE) in NOMA HetNet by jointly optimizing the transmission of hybrid precoding, power allocation, and bandwidth partition. Next, we formulate an optimization problem within the proposed framework under the minimum data rate and total maximum transmission power constraints. Due to the non-convexity nature of the formulated problem, it is challenging to obtain the optimal solution. As a result, we transform the original problem into a quasi-convex equivalent by analyzing its structure. Then we propose energy-efficient distributed power allocation algorithms to optimize the resource allocation of macro-cell and small cells. Finally, we exhibit the simulation results to demonstrate the proposed algorithm’s performance gains. The simulation results reveal that the proposed algorithmic approach surpasses state-of-the-art and traditional mmWave orthogonal multiple access systems in both capacity and EE.

Numerical investigation of fracture interference effects on multi-fractures propagation in fractured shale

Since fracture morphology is jointly influenced by inter-cluster interference and natural fractures, multi-cluster fracture propagation behaviors are complicated during staged volume fracturing. Although there are many studies on complex fracture propagation, the engineering-scale investigation of multi-cluster fracture interactive propagation behaviors is still needed. In this paper, a coupled fracture propagation PF model is developed and an engineering-scale natural fracture characterization method based on seismic interpretation results is introduced. The effectiveness of the model is validated by comparing fracture propagation behaviors with the fracturing experimental result, and this model is applied to study interactive behaviors of multi-cluster fractures in fractured shale. The results indicate that inter-cluster stress interference affects the induced stress field and leads to merging, diverting, and restraining fracture behaviors, activating NFs can effectively reduce the interference and is beneficial for forming complex fractures, and the NF occurrence is a decisive factor that affected fracture morphologies. To enhance the stimulation efficiency, the fracturing mode with multi-cluster and close-spacing is recommended for fractured shale stimulation.

On the Beamforming Design and Transmit Power Analysis for Single- and Multi-Cluster NOMA

This paper is on the beamforming design and performance analysis of the power-domain non-orthogonal multiple access (NOMA) systems. First, a closed-form linear beamforming design is proposed for single-cluster NOMA systems with two users to minimize the required transmit power with users' signal-to-interference-plus-noise-ratios (SINRs) guaranteed. The average power consumption and the power scaling law are derived for the proposed beamforming design. For multi-cluster NOMA, we exploit a two-stage beamforming design where the first stage eliminates the inter-cluster interference via zero-forcing (ZF) and the second stage aims at saving the required transmit power within each cluster by using the proposed single-cluster beamforming design based on the effective channel vectors. Numerical results are provided to show the superiority of NOMA transmissions with our proposed beamforming comparing to other transmission schemes in terms of the required transmit power and the outage performance.

Double-Layer Precoder and Cluster-Based Power Allocation Design for LEO Satellite Communication With Massive MIMO

In this work, we propose a double-layer precoder and cluster-based power allocation design for low earth orbit (LEO) satellite communication with massive multiple input multiple output (MIMO). Specifically, spectral efficiency (SE) is chosen as the evaluation metric with hardware complexity, transmit power, instantaneous channel state information (iCSI) and statistical channel state information (sCSI) considered. We simplify the three-dimension (3D) air-to-ground MIMO channel under satellite environment with the angular spread model. Then, a double-layer precoder is proposed to reduce the hardware complexity and eliminate the inter-user interference (IUI) among each user cluster. With angle of departure (AoD) information, the user clustering criteria to maximize the SE and eliminate inter-cluster interference (ICI) is derived. After that, a cluster-based power allocation scheme is proposed by dividing the total transmit power into two parts, one to meet the user’s minimum service requirement and the other to get optimal SE performance by waterfilling algorithm. Simulation results show that the proposed scheme achieves better SE performance compared with other feasible approaches.

Energy-Efficient IRS-Aided NOMA Beamforming for 6G Wireless Communications

This manuscript presents an energy-efficient alternating optimization framework based on intelligent reflective surfaces (IRS) aided non-orthogonal multiple access beamforming (NOMA-BF) system for 6G wireless communications. Specifically, this work proposes a centralized IRS-enabled design for the NOMA-BF system to optimize the active beamforming and power allocation coefficient (PAC) of users at the transmitter in the first stage and passive beamforming at IRS in the 2nd stage to maximize the energy efficiency (EE) of the network. However, an increment in the number of supportable users with the NOMA-BF system will lead to NOMA user interference and inter-cluster interference (ICI). To mitigate the effect of ICI, first zero-forcing beamforming along with efficient user clustering algorithm is exploited and then NOMA user interference is tackled efficiently through a proposed iterative algorithm that computes PAC of NOMA user through simplified closed-form expression under the required system constraints. In the 2nd stage, the problem of passive beamforming is solved through a technique based on difference-of-convex (DC) programming and successive convex approximation (SCA). Simulation results demonstrate that the proposed alternating framework for energy-efficient IRS-assisted NOMA-BF system can achieve convergence within a few iterations and provide efficient performance in terms of EE of the system with low complexity.

Effective User Clustering and Power Control for Multiantenna Uplink NOMA Transmission

This paper investigates the user clustering and power control in the uplink multiple-input single-output non-orthogonal multiple access (MISO-NOMA) networks. A joint optimization problem is formulated to minimize the system transmit power. The formulated optimization problem is prohibitively complicated, especially when the number of users is large. Alternatively, a two-step user clustering and power control algorithm is proposed. First, a K-means-based algorithm is proposed for user clustering, where both channel gain and channel correlation among users are taken into account for the distance measurement to reduce the intra- and inter-cluster interference. Then, a semi-orthogonal user selection (SUS) algorithm is designed, with which the optimal cluster number and cluster centers can be dynamically obtained. Further, the closed-form expression of the optimal intra-cluster power control is derived, and the resulting inter-cluster power control problem is solved by designing an efficient iterative algorithm. Simulation results show that the proposed K-means-based iterative power control scheme outperforms other reference methods, and can approach the optimal performance in terms of power consumption and energy efficiency at a much lower computational complexity.

Performance analysis of multi user MIMO NOMA network with hierarchical clustering

ABSTRACT In this paper, a multi-user multiple input multiple output network is considered with a user clustering technique so that groups of users can be served on a common resource. A hierarchical clustering algorithm defined on the distance metric has been used to form the user clusters. Users within a cluster exploit the non-orthogonal multiple access method to serve the users on the same time and frequency resource blocks, thus resulting in a spectrally efficient transmission. While the different clusters of users are served on several focussed beams, the popular zero-forcing beamforming method is adopted to cancel the inter-cluster interference. Performance evaluation in terms of the sum rate of users and fairness has been done to establish the efficiency of the proposed network model.

Multicluster-Coordination Industrial Internet of Things: The Era of Nonorthogonal Transmission

The imminent industrial Internet of Things (IIoT) aims to provide massive device connectivity and support ever-increasing data demands, putting today’s production environment on the edge of a new era of innovations and changes. In a multicluster IIoT, devices may suffer severe intercluster interference due to the intensive frequency reuse among adjacent access points (APs), thus deteriorating their quality of service (QoS). To address this issue, conventional multicluster coordination in the IIoT provides orthogonal code-, frequency-, time- or spatial-domain multiple access for interference management, but this results in a waste of resources, especially in the context of the explosively increased number of devices.

A Unified Framework for Distributed RIS-Aided Downlink Systems Between MIMO-NOMA and MIMO-SDMA

The combination of reconfigurable intelligent surface (RIS) and non-orthogonal multiple access (NOMA) has been recognized as a critical method to improve the sixth generation networks performance. In this paper, a distributed RIS-aided downlink multiple-input multiple-output (MIMO) NOMA systems with discrete phase shifts are studied, where the channel directions from base station to paired users can be manipulated with the assistance of RISs by employing the concept of signal alignment. In order to ensure base station can flexibly serve some users with NOMA and others users with spatial division multiple access, a unified precoder and decoder are provide to cancel inter-cluster interference. Subsequently, the channel statistics over Nakagami- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula> fading channels are derived for near and far users. In particular, considering the cascade channel gain may exists two different cases, Beaulieu series is further adopted to characterize their corresponding cumulative distribution function. In what follows, the outage probability and ergodic rate for three situations within one cluster are derived by utilizing the obtained channel statistics, respectively. Based on the derived results, we also analyze the diversity order and high signal-to-noise ratio slope to provide essential insights into the considered systems. Finally, simulation results are presented to reveal that: 1) selecting the setting of 3-bits resolution can realize a near-aligned performance for our proposed systems; 2) the cascade channel statistic caused by RIS can be evaluated with any number of RIS element and any channel gain via Beaulieu series.

Interference and secrecy analysis based on randomly spacial model in clustered WSNs

Clustering and layering are widely employed in large-scale wireless sensor networks (WSNs) to alleviate data implosion, reduce transmission delay and improve energy efficiency. It is vital to conduct performance analysis in clustered WSNs for better defining and designing networks. Here, a general analytical framework based on a randomly spacial model is proposed to conduct inter-cluster interference analysis and physical-layer security analysis for clustered WSNs. It is assumed that two adjacent cluster heads exchange confidential massage with a passive eavesdropper and the non-head nodes in clusters could be selected as cooperative jamming (CJ) nodes to disturb the eavesdropper. All mentioned nodes are randomly located in their specific areas. Under the above settings, three scenarios, namely interference, eavesdropping and CJ are considered, and a stochastic geometry tool based on kinematic measure is employed for analysis. Comparing to existing stochastic geometry methods, the proposed analytical framework can handle arbitrarily shaped, disjoint and tiered networks. The results obtained from extensive simulations have verified the rationality of the framework and demonstrated the impact of different parameters on the performance metrics of interest. The comparison with PPP also shows the advantages of this proposed model.

Energy Efficiency Optimization with SINR Constraints in Downlink MIMO-NOMA Systems

In downlink multiple-input, multiple-output, (MIMO) and non-orthogonal multiple access (NOMA) systems, the inter-cluster interference can be cancelled by optimizing pre-coding and detection matrices. Thus, the MIMO-NOMA channel is decomposed into multiple single-input, single-output and (SISO)-MOMA channels. Then, we formulate an energy efficiency (EE) optimization problem subject to the signal-to-interference-plus-noise ratio (SINR) constraints which is non-convex. To solve the problem, we propose the algorithm based on one-dimensional linear search and first-order Taylor expansion. Moreover, as in conventional communication systems, EE and spectrum efficiency (SE) cannot always be improved simultaneously. Thus, the trade-off between EE and SE is investigated based on the formulated problem. Numerical analyses and simulation results verify the proposed algorithm. In addition, the performance in terms of EE and the EE-SE trade-off can be improved by optimizing the user pairing method.

Interference Management of Analog Function Computation in Multicluster Networks

Computation over multiple access channels (CoMAC) has been proposed to solve the problem of spectrum scarcity in wireless networks, which combines communication and computation efficiently using the superposition property of wireless channels. In this paper, we consider a multi-cluster CoMAC network, whose performance is affected by the inter-cluster interference and the non-uniform fading. To minimize the sum mean squared error of signals aggregated at different fusion centers (FCs), we propose a transceiver design for multi-cluster CoMAC. Specifically, we adopt a uniform-forcing transmitter design to formulate the receiver design as a quadratic sum-of-ratios problem with nonconvex quadratic constraints. Then, we propose a branch-and-bound algorithm to find its optimal solution with a given error tolerance. To solve the problem in a decentralized way, we develop a distributed algorithm based on the primal decomposition theory. Each subproblem is solved by using the successive convex approximation method. Further combining Lagrange duality, we derive the optimal solution structure of each subproblem, based on which we can find the solution with lower complexity. Simulation results demonstrate the effectiveness of the proposed distributed transceiver design.

Learning-Based User Clustering in NOMA-Aided MIMO Networks With Spatially Correlated Channels

This paper considers the integration of non-orthogonal multiple access (NOMA) into massive multi-input multi-output (MIMO) systems for downlink transmission. We consider the joint design of user clustering, transmit beamforming, and power allocation to minimize the total transmit power while meeting the signal-to-interference-and-noise ratio targets. We decompose this challenging mixed-integer programming problem into three separate subproblems to solve. We propose a low-complexity learning-based user clustering algorithm, which is a modified version of mean shift clustering with a new channel correlation based clustering metric. The proposed clustering algorithm determines the clusters to trade-off between spatial dimension and power dimension offered by respective MIMO and NOMA for user multiplexing. We then design zero-forcing transmit beamformers to eliminate inter-cluster interference and optimize power allocation to minimize the total transmit power. We provide two case studies for both co-located and distributed massive MIMO systems in spatially highly correlated prorogation environments. Simulation results show that our proposed algorithm forms NOMA clusters based on the available degrees of freedom in the system to effectively use both spatial and power dimensions, which results in a substantial performance improvement over MIMO-only methods or other existing clustering methods in such environments.

Joint optimization scheme based on beam selection and interference cancellation in lens millimeter wave NOMA systems

Non-orthogonal multiple access (NOMA) has been integrated in millimeter-wave (mmWave) Massive MIMO systems to further enhance the spectrum efficiency, but NOMA has not been fully considered in lens mmWave systems. The fusion of these two technologies requires the joint design of beam selection and interference cancellation. In addition, when users follow the spatial cluster distribution, although the user clustering schemes based on K-means algorithm have been applied, the influence of the virtual and actual cluster center users on achievable sum rate has not been differentiated and analyzed in detail. To solve the above problems, a joint optimization scheme is proposed to maximize the achievable sum rate. The optimization problem is NP-hard, which is solved by using the divide-and-conquer approach. Concretely, based on the signal power loss analysis of directional deviation, a beam selection algorithm is designed for inter-cluster interference cancellation based on the K-means algorithm. Further for intra-cluster interference cancellation, a power allocation algorithm based on the bisection method is designed to guarantee the fairness of users in each cluster. The simulation results show that the proposed scheme offers a significant performance improvement in terms of both achievable sum rate and energy efficiency, and it is suitable for the large-scale user scenario due to its low complexity.

Modeling and Performance Analysis in UAV-Assisted Cellular Networks with Clustered Edge Users

A UAV-assisted cellular network can provide ubiquitous links to everything and it is considered to be one of the key technologies for 6G wireless networks. In this paper, we consider an uplink wireless network with a macrobase station (MBS) and cellular users. However, the coverage equality of edge users cannot be guaranteed in scenarios where data service is dense. Specifically, a novel topology of the UAV-assisted wireless network is considered. UAVs are deployed upon the cell edge to serve edge users with poor communication quality. To avoid larger interference caused by users and UAVs in the overlapping area, the locations of these UAVs are modeled as a homogeneous Poisson point process (HPPP) under the Poisson cluster distance constraint (PCDC). In addition, we assume that edge users cluster around each UAV and model their locations as Poisson cluster processes (PCPs). Initially, the Laplace transforms of intra-cluster interference, inter-cluster interference, and other interference are derived. Subsequently, coverage probability and area spectrum efficiency are derived for UAVs and MBS using tools from stochastic geometry. Moreover, the energy efficiency of the system is obtained. Simulation results are examined to validate the accuracy of theoretical analysis and provide insights into the effects of the system parameters as well as useful guidelines for practical system design.

Subcarrier BD with Cooperative Communication for MIMO-NOMA System

With the rapid evolution of Internet of things (IoT), many edge devices require simultaneous connection in 5G communication era. To afford massive data of IoT devices, multiple input multiple output non-orthogonal multiple access (MIMO-NOMA) method has been considered as a promising technology. However, there are numerous drawbacks due to error propagation and inter-user interferences. Therefore, proposed scheme aims to improve the reliability of the MIMO-NOMA system with digital beamforming and intra-cluster cooperative multi point (CoMP) to efficiently support IoT system. In the conventional MIMO-NOMA system, user entities are grouped into clusters. Block diagonalization (BD) is applied to efficiently eliminate the inter-cluster interference of the MIMO-NOMA system. However, since the channel path of the data stream from a single antenna to a single cluster doesn’t hold other cluster’s data, the system can’t fully utilize the selective subcarrier channel states. It indicates that there can be better channel paths for a data stream at a certain subcarrier index. Therefore, proposed scheme allocates data streams to antennas adaptively considering selective channel states. Additionally, intra-cluster CoMP method is adjusted to enhance the reliability of the system in the clusters. The simulation results show that the proposed scheme improves BER and throughput performance compared to the conventional MIMO-NOMA system.