Coordinated Multipoint Research Articles

An energy-efficient JT-CoMP enabled framework with adaptive OMA/NOMA in HetNets

The increasing demand for higher data rates and improved energy efficiency (EE) in next-generation wireless networks necessitates the optimized selection of multiple-access and coordination techniques. A hybrid joint transmission (JT)-coordinated multi-point (CoMP) enabled orthogonal multiple access (OMA)/non-orthogonal multiple access (NOMA) technique, combining the spectral efficiency (SE) and capacity benefits of CoMP NOMA with the interference mitigation of CoMP OMA, offers a highly adaptable solution for future wireless networks. This paper studies the joint optimization of CoMP/non-CoMP selection, OMA/NOMA selection, power allocation, and user pairing, with the objective of maximizing the EE in the network. A Dynamic CoMP user selection with energy-efficient adaptive multiple access (DCEAMA) algorithm to solve the formulated problem is proposed. Our Monte Carlo simulations show that the DCEAMA surpasses both the pure CoMP OMA and CoMP NOMA schemes in terms of EE, with an average increase of 38% and 26% respectively. We compare our heuristic technique to an exhaustive search strategy to evaluate its efficiency. The findings indicate that our strategy produces comparable EE across various power levels with reduced computational complexity.

Design of Visual Communication Experience Based on Virtual Reality Technology

Visual communication experiences have been revolutionized by virtual reality (VR) technology, offering users immersive and captivating interactions with digital content. Through VR headsets and immersive environments, users can engage with visual content in unprecedented ways, feeling as though they are physically present within the digital space. Whether exploring virtual art galleries, immersive storytelling experiences, or interactive visualizations, VR technology provides users with a sense of presence and agency, enhancing their connection to the content. Furthermore, VR enables creators to design highly engaging and interactive visual experiences that transcend traditional media formats, allowing for innovative storytelling techniques and immersive narratives. This paper presents the design of a novel visual communication experience leveraging virtual reality (VR) technology enhanced by Multi-Spectral Multi-Point Co-Ordination (MSMPC). The proposed design aims to create immersive and engaging visual experiences that transcend traditional media formats. Through simulated experiments and empirical validations, the effectiveness of the MSMPC-enhanced VR-based visual communication experience is evaluated. Results demonstrate significant improvements in user engagement, immersion, and satisfaction compared to conventional approaches. The users interacting with the MSMPC-enhanced VR experience reported a 40% increase in immersion levels and a 25% improvement in overall satisfaction ratings. Additionally, the design enabled creators to optimize visual storytelling techniques based on real-time user feedback and performance data, leading to more impactful and effective communication. These findings highlight the potential of MSMPC in enhancing visual communication experiences based on VR technology, paving the way for innovative and immersive storytelling in various domains.

Covert performance enhancement in NOMA enabled CoMP network with optimal RIS selection

In this paper, we consider the covert rate maximization problem for the cell edge user in a reconfigurable intelligent surface (RIS) aided downlink non-orthogonal multiple access (NOMA) network with coordinated multipoint (CoMP) transmission in the presence of channel estimation errors. We derive the analytical expression for the detection error probability (DEP) at the adversary (Willie) assuming the worst case scenario where they employ optimal detection threshold. With the derived analytical expression, we propose an optimal RIS selection scheme to boost the covert rate. To further improve the covert performance, we optimize the NOMA power allocation coefficients and phase shifts of the selected RIS subject to the target rate and covertness constraints. Simulation results demonstrate the improvement in covert rate and robustness offered by the proposed scheme in the presence of channel estimation errors over other benchmarks.

Fountain Coded Coordinated Multipoint for 5G MBMS UAV Relay

Fountain Coded Coordinated Multipoint for 5G MBMS UAV Relay

On the Application of Quasi-Degradation to Network NOMA in Downlink CoMP Systems

The application of network non-orthogonal multiple access (N-NOMA) technique to coordinated multi-point (CoMP) systems has attracted significant attention due to its superior capability to improve connectivity and maintain reliable transmission for CoMP users simultaneously. Based on the concept of quasi-degraded channel for N-NOMA, this paper studies the precoding design for downlink N-NOMA scenarios with two base stations (BSs) equipped with multiple antennas. In specific, under quasi-degraded channels, simple linear precoding based N-NOMA can achieve the same minimal total transmission power as theoretically optimal but complicated dirty paper coding (DPC) scheme, when the users’ target rates and minimal transmission power of each BS are given. In this paper, the channel quasi-degradation (QD) condition is first rigorously derived for the scenario with single CoMP user and two NOMA users. The closed-form optimal precoders for N-NOMA under quasi-degraded channels are also provided. Then, based on QD condition, a novel hybrid N-NOMA (H-N-NOMA) scheme is proposed, which is a mixture of N-NOMA and conventional zero-forcing beamforming (ZFBF) scheme. Further, for the scenarios with more users, a low-complexity QD based user pairing (QDUP) algorithm is proposed, which is then combined with H-N-NOMA to make a novel scheme termed H-N-NOMA/QDUP into being. Numerical results are presented to reveal the impact factors on QD channels, and also demonstrate the superior performance of the proposed H-N-NOMA/QDUP scheme. It is shown that the proposed H-N-NOMA/QDUP scheme can effectively exploit the benefit of multi user diversity.

A Survey on User Grouping Schemes in Non- Orthogonal Multiple Access (NOMA)

In wireless networks, managing an increasing number of users becomes increasingly challenging as user density rises. To address these challenges, various algorithms are employed to divide users into smaller, more controllable groups. This approach is crucial for optimizing the performance of Non-Orthogonal Multiple Access (NOMA) systems, which are a key component of nextgeneration wireless networks like 5G and 6G. User grouping schemes in NOMA systems are essential for optimizing resource allocation, mitigating interference, improving spectral efficiency, ensuring fairness, and reducing complexity. As wireless networks evolve, particularly with the integration of advanced technologies like Coordinated Multi-Point (CoMP), Internet of Things (IoT), Millimeter- Wave (mmWave), Terahertz (THz), Unmanned Aerial Vehicles (UAVs), Multi-Input Multi-Output (MIMO), and 5G-6G, effective user grouping will become increasingly critical. This research paper provides a systematic classification and analysis of various user grouping schemes, offering valuable insights for enhancing network performance in next-generation wireless networks.

Adaptive refined random orthogonal matching pursuit algorithm for FBMC/OQAM MIMO framework

The fifth generation of wireless communication is anticipated to provide improved quality of service and enhanced data rates to the end users. One such technology that stands out as a potential transmission scheme for 5G systems is Filter Bank Multicarrier using Offset Quadrature Amplitude Modulation (FBMC/OQAM) with an effective channel estimation technique for improved performance. However, due to the inherent imaginary interference, channel estimation methods relying on preamble structures in FBMC/OQAM systems exhibit sub-optimal performance, particularly within Multiple-Input Multiple-Output (MIMO) setups. For channel estimation schemes based on compressed sensing, the inherent sparsity of wireless channels can be exploited for accurate channel reconstruction and overall performance improvement.We propose a novel compressed sensing based algorithm namely, Adaptive Refined Random Orthogonal Matching Pursuit (ARROMP), for MIMO-FBMC system with Coordinated MultiPoint (CoMP) scheduling. This algorithm adaptively selects a support set by utilizing a double threshold for the minimization of mean squared error and for accurate channel reconstruction. The proposed algorithm's performance is compared with existing Orthogonal Matching Pursuit (OMP) schemes such as random OMP, refined random OMP, and least square-based estimation. The numerical simulations suggest that the proposed adaptive algorithm provides performance improvement in terms of reduced Mean Squared Error (MSE) of channel reconstruction and Bit Error Rate (BER). Moreover, the proposed ARROMP algorithm for MIMO-FBMC is rigorously tested with CoMP scheduling for a cellular network using frequency division duplex mode. The proposed system presents significant improvements in throughput and spectral efficiency for all types of cell users, including cell-edge users. The simulation results validate the improved performance of the proposed algorithm with CoMP scheduling over the existing single-cell system with no coordination.

Impact of Power Consumption Models on the Energy Efficiency of Downlink NOMA Systems

While non-orthogonal multiple access (NOMA) improves spectral efficiency, it adds complexity to the receivers due to successive interference cancellation (SIC). Prior studies on the energy efficiency of NOMA overlook the SIC overhead and rely on simplistic power consumption models (PCM). To fill this gap, we first introduce PCM-κ that accounts for SIC-related power expenditure. Then, to investigate the energy efficiency of NOMA and joint transmission (JT)-coordinated multipoint (CoMP) NOMA, we formulate a power allocation problem for maximizing the energy efficiency and propose a global approach running at a centralized entity and a local algorithm running at a base station. We evaluate the energy efficiency using PCM-κ and two PCMs commonly used in the literature. Numerical analysis suggests that using simplistic PCMs leads to a few orders of magnitude overestimation of energy efficiency, especially when the receivers have low rate requirements. Despite the superiority of JT-CoMP NOMA over conventional NOMA in finding a feasible power allocation, the difference in their energy efficiency is only marginal when users have identical rate requirements and more significant in more heterogeneous settings with users having different rate requirements. Moreover, when conventional NOMA is feasible, the optimal solution for JT-CoMP NOMA converges to conventional NOMA.

Collaborative CoMP and trajectory optimization for energy minimization in multi-UAV-assisted IoT networks with QoS guarantee

For the Internet of Things (IoT) networks, the coverage may be drastically degraded when disasters or breakdowns occur due to the destroyed communication network. Using unmanned aerial vehicles (UAVs) as flying base stations for IoT emergency coverage is possible because of their agility and low-altitude deployment. With the deployment of UAVs, strong co-channel interference may be formed in the network because of the line-of-sight channels between UAVs and the ground terminals. To address this issue, in this paper, coordinated multi-point (CoMP) technique along with the proper deployment of UAVs is developed in a multi-UAV-assisted IoT network. However, CoMP is difficult to implement for the entire network due to its processing delay and overhead. Therefore, the network is splatted into overlapped clusters by employing a user-centric clustering approach. We aim to minimize the system’s energy consumption, including propulsion and communication energy, while optimizing the CoMP clusters and beamforming vectors, as well as the UAVs’ trajectories and velocities. The energy minimization problem is formulated subject to target information rate for IoT users, UAVs’ mobility, and maximum transmit power constraints. Since the formulated problem suffers from nonconvexity, an efficient solution is proposed to deal with it. First, for fixed clusters and beamforming vectors, the UAVs’ trajectories and velocities are optimized. Then, for fixed UAVs’ deployment, we optimize the CoMP clusters and beamforming vectors. Finally, two sub-problems are solved alternatively using an alternating optimization technique. Numerical results verify that the proposed solution is effective.

Performance Analysis and Optimization of Worst Case User in CoMP Ultra Dense Networks

In the cellular system, the Worst Case User (WCU), whose distances to three nearest BSs are the similar, usually achieves the lowest performance. Improving user performance, especially the WCU, is a big problem for both network designers and operators. This paper works on the WCU in terms of coverage probability analysis by the stochastic geometry tool and data rate optimization with the transmission power constraint by the reinforcement learning technique under the Stretched Pathloss Model (SPLM). In analysis, only fast fading from the WCU to the serving Base Stations (BSs) is taken into the analysis to derive the lower bound coverage probability. Furthermore, the paper assumes that the Coordinated Multi-Point (CoMP) technique is only employed for the WCU to enhance its downlink signal and avoid the explosion of Intercell Interference (ICI). Through the analysis and simulation, the paper states that to improve the WCU performance under bad wireless environments, an increase in transmission power can be a possible solution. However, in good environments, the deployment of advanced techniques such as Joint Transmission (JT), Joint Scheduling (JS), and reinforcement learning is an suitable solution.

Joint trajectory and CoMP clustering optimization in UAV-assisted cellular systems: a coalition formation game approach

In this paper, the flexibility of unmanned aerial vehicles (UAVs), as well as the benefits of coordinated multi-point (CoMP) transmission, are utilized for mitigating the interference in cellular networks. Specifically, the joint problem of CoMP clusters and UAVs’ trajectories is addressed for downlink transmission in a UAV-assisted cellular system. The problem is presented as a non-convex optimization problem that aims to maximize the sum rate of the ground users by taking into account the clustering, UAV mobility and backhaul capacity constraints. Since the formulated problem is known to be NP-hard, we partition it into two sub-problems. Particularly, by using coalitional game theory, the CoMP clusters are obtained with a given UAVs’ trajectories. Then, UAVs’ trajectories are optimized with given CoMP clusters using successive convex approximation technique. Based on the block coordinate descent method, the two sub-problems are solved alternatively until convergence. Numerical results are conducted and demonstrated the effectiveness of the proposed algorithm.

Uplink CoMP Transmission for Cellular-Connected UAV Networks

In this letter, we study the coordinated multipoint (CoMP) scheme in the uplink cellular-connected UAV network. By considering the LoS and NLoS components in air-to-ground (A2G) transmission, we adopt the strongest average received signal strength (RSS)-based CoMP scheme. We then develop an analytical framework to evaluate the network performance in terms of coverage probability and area spectral efficiency (ASE) for the case of two cooperative base stations (BSs), followed by an extension to a generalized number of cooperative BSs. Compared to the CoMP scheme with single UAV tier and Non-CoMP baseline, the considered CoMP scheme is able to leverage favored Line-of-Sight (LoS) transmission, lower path loss and BS cooperation gain.

Single and Multi-Point Non-Orthogonal Multiple Access based Power Adaptive Design for Improving Bit Error Ratio

Abstract In the framework of next-generation communication systems, Non-Orthogonal Multiple Access (NOMA) has attracted considerable interest. The fundamental advantage is that it has greater spectrum utilization than its orthogonal equivalents. This proposed work integrates Single-Input Single-Output NOMA (SISO) with Coordinated Multi-Point (CoMP). It uses both systems based on Quadrature Phase-Shift Keying (QPSK). A power-tolerant NOMA reduces the system’s vulnerability to erroneous power allocation by adaptively modifying each user’s signal power. The transmitted data is used to modify the power in the Power-Adaptive NOMA (PANOMA). PANOMA helps improve the Bit Error ratio and also improves the computational complexity. The Bit Error Rate (BER) and the lower limit capacity efficiency across Rayleigh fading channels are determined in precise closure representations of more than two consumer situations to measure its capability. The proposed method PA-CoMP-NOMA improves the Bit Error ratio in both systems. It improves the average BER among all users. Compared to its orthogonal cousin, NOMA has higher spectral efficiency. Nevertheless, our proposed method retains this feature as well as superior BER performance, although its spectral effectiveness is lower than that of the classic sum-rate based power NOMA.

Outage-Minimization Coordinated Multi-Point for Millimeter-Wave OFDM With Random Blockages

We consider millimeter-wave (mmWave) orthogonal frequency division multiplexing (OFDM) systems subjected to random propagation path blockages and propose a new Coordinated multi-point (CoMP) transmission scheme that minimizes the outage probability of users with respect to given target data rates. To this end, a stochastic sum-outage-probability minimization problem is formulated for joint beamforming design, data rate allocation, and power allocation over subcarriers. In order to solve this problem efficiently, a block statistic learning approach is introduced using training data generated from <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a priori</i> knowledge of path blockage probabilities. To initialize the stochastic learning solver, the novel initial beamforming is also proposed based on the upper bound of the original objective function, which improves convergence without tuning hyper-parameters. Numerical results confirm the effectiveness of the proposed block stochastic learning approach in terms of both convergence behavior and outage probability. Furthermore, these results confirm that the proposed approach with only blockage probabilities is comparable to the outage performance of a CoMP sum rate maximization (SRM) transmission scheme with perfect channel state information (CSI) and perfect knowledge of blockages.

OTFS Signaling for SCMA With Coordinated Multi-Point Vehicle Communications

This paper investigates an uplink coordinated multi-point (CoMP) coverage scenario, in which multiple mobile users are grouped for sparse code multiple access (SCMA), and served by the remote radio head (RRH) in front of them and the RRH behind them simultaneously. We apply orthogonal time frequency space (OTFS) modulation for each user to exploit the degrees of freedom arising from both the delay and Doppler domains. As the signals received by the RRHs in front of and behind the users experience respectively positive and negative Doppler frequency shifts, our proposed OTFS-based SCMA (OBSCMA) with CoMP system can effectively harvest extra Doppler and spatial diversity for better performance. Based on maximum likelihood (ML) detector, we analyze the single-user average bit error rate (ABER) bound as the benchmark of the ABER performance for our proposed OBSCMA with CoMP system. We also develop a customized Gaussian approximation with expectation propagation (GAEP) algorithm for multi-user detection and propose efficient algorithm structures for centralized and decentralized detectors. Our proposed OBSCMA with CoMP system leads to stronger performance than the existing solutions. The proposed centralized and decentralized detectors exhibit effective reception and robustness under channel state information uncertainty.

CoMP-Enhanced Flexible Functional Split for Mixed Services in Beyond 5G Wireless Networks

With explosively escalating service demands, beyond fifth generation (B5G) aims to realize various requirements for multi-service networks, i.e., higher performance of mixed enhanced mobile broadband (eMBB) and ultra-reliable low-latency communication (URLLC) services than 5G. To flexibly serve diverse traffic, various functional split options (FSOs) are specified by 5G protocols enabling different network functions. In order to improve signal qualities for edge users, we consider FSO-based coordinated multi-point (CoMP) transmission as a prominent technique capable of supporting high traffic demands. However, due to conventional confined hardware processing capability, a processor sharing (PS) model is introduced to deal with high latency for multi-service FSO-based networks. Therefore, it becomes essential to assign CoMP-enhanced functional split modes under PS model. A more tractable FSO-based network in terms of ergodic rate and reliability is derived by stochastic geometry approach. Moreover, we have proposed CoMP-enhanced functional split mode allocation (CFSMA) scheme to adaptively assign FSOs to provide enhanced mixed throughput and latency-aware services. The simulation results have validated analytical derivation and demonstrated that the proposed CFSMA scheme optimizes system spectrum efficiency while guaranteeing stringent latency requirement. The proposed CFSMA scheme with the designed PS FFS-CoMP system outperforms the benchmarks of conventional FCFS scheduling, non-FSO network, fixed FSOs, and limited available FSO selections in open literature.

Impact of Decoding Order on User Pairing in NOMA-CoMP Joint Transmission

This correspondence investigates the optimal decoding order and its impact on user pairing in non-orthogonal multiple access (NOMA)-enabled coordinated multipoint (CoMP) joint transmission (JT) to maximize the sum rate of users. First, the optimal solution of power control for a user pair is obtained under different decoding orders, where closed-form expressions and a low-complexity algorithm are given by monotonic optimization. Then, a criterion for finding the optimal decoding order is derived for any given user pair in the considered scenario. Results show that the optimal decoding order is distinct for different user pairs, which can be achieved separately. This indicates that the decoding order is not a necessary prerequisite for user pairing in NOMA-enabled CoMP systems. Moreover, the optimal decoding order is shown to depend on the differentials of channel gains between the user served by JT and coordinated base stations.

STAR-RIS-UAV-Aided Coordinated Multipoint Cellular System for Multi-User Networks

Different from conventional reconfigurable intelligent surfaces (RIS), simultaneous transmitting and reflecting RIS (STAR-RIS) can reflect and transmit signals to the receiver. In this paper, to serve more ground users and increase deployment flexibility, we investigate an unmanned aerial vehicle (UAV) equipped with STAR-RIS (STAR-RIS-UAV)-aided wireless communications for multi-user networks. Energy splitting (ES) and mode switching (MS) protocols are considered to control the reflection and transmission coefficients of STAR-RIS elements. To maximize the sum rate of the STAR-RIS-UAV-aided coordinated multipoint (CoMP) cellular system for multi-user networks, the corresponding beamforming vectors as well as transmitted and reflected coefficient matrices are optimized. Specifically, instead of adopting the alternating optimization, we design an iteration method to optimize all variables for both the ES and MS protocols at the same time. Simulation results reveal that the STAR-RIS-UAV-aided CoMP system has a much higher sum rate than systems with conventional RIS or without RIS. Furthermore, the proposed structure is more flexible than fixed STAR-RIS and could greatly promote the 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.

Converging Game Theory and Reinforcement Learning For Industrial Internet of Things

The fifth-generation (5G) wireless network provides high-rate, ultra-low latency, and high-reliability connections that can meet the Industrial Internet of Things (IIoT) requirements in factory automation, especially for robot motion control. In this paper, we address 5G service provisioning in an automated warehouse scenario, where swarm robotics is controlled by an industrial controller that provides routing and job instructions over the 5G network. Leveraging the coordinated multipoint (CoMP), we formulate a time-varying joint CoMP clustering and 5G ultra-reliable low-latency communication (URLLC) beamforming design problem to control the robots that move around the automated warehouse for goods storage with the planned reference tracks. Traditional iterative optimization approaches are impractical in such a dynamic wireless environment due to high computational time. We propose a game-theoretic CoMP clustering algorithm combined with the Proximal Policy Optimization method to obtain a stationary solution closed to that of the exhaustive search algorithm considered as the global optimal solution.