Search Results (13)

In densely populated areas, resource management is a challenge when mobile users in a session increase. The result of this is high inter-cell interference. Since interference is a function of power, we develop power control models aimed at addressing inter-cell interference among macrousers and femtousers in a 5G network. The models consider both cooperative and noncooperative game-theoretic theories. These are implemented within the framework of system dynamics. The models are developed using feedback loops and system dynamics approaches. The game-theoretic models are verified to establish a basis for developing mathematical models to implement power control in 5G networks. The comparative simulation demonstrates the superiority of cooperative game-theoretic power control in 5G NR in terms of signal-to-interference-plus-noise ratio (SINR), data rate, spectral efficiency (SE), and utility in interference-prone environments. While noncooperative strategies offer simplicity and lower signaling overhead, they result in poorer performance due to unmanaged interference and selfish resource utilization. The results demonstrate that the cooperative game-theoretic power control technique substantially enhanced network performance, achieving an average SINR improvement of 58.82% and an average SE improvement of 69.03%. Full article

In a multi-cell network, interference management between adjacent cells is a key factor that determines the performance of the entire cellular network. In particular, in order to control inter-cell interference while providing a high data rate to users, it is very important for the base station (BS) of each cell to appropriately control the transmit power in the downlink. However, as the number of cells increases, controlling the downlink transmit power at the BS becomes increasingly difficult. In this paper, we propose a multi-agent deep reinforcement learning (MADRL)-based transmit power control scheme to maximize the sum rate in multi-cell networks. In particular, the proposed scheme incorporates a long short-term memory (LSTM) architecture into the MADRL scheme to retain state information across time slots and to use that information for subsequent action decisions, thereby improving the sum rate performance. In the proposed scheme, the agent of each BS uses only its local channel state information; consequently, it does not need to receive signal messages from adjacent agents. The simulation results show that the proposed scheme outperforms the existing MADRL scheme by reducing the amount of signal messages exchanged between links and improving the sum rate. Full article

Over the past few years, wireless communication has grown dramatically, and the consumer demand for wireless services has seen a significant jump. One of the main challenges for beyond fifth generation (B5G) networks is the increased capacity of the network. The continuously increasing number of network users and the limited radio spectrum in wireless technologies have led to severe congestion in communication channels. This issue leads to traffic congestion at base stations and introduces interference in the network, thereby degrading system capability and quality of service. Interference reduction has thus become a major design challenge in wireless communication systems. This review paper comprehensively explores interference management (IM) strategies in B5G networks. We critically analyze and summarize existing research on interference issues related to device-to-device communication, heterogeneous networks, inter-cell interference, and artificial intelligence (AI)-based frameworks. The paper reviews a wide range of methodologies, highlights the strengths and limitations of state-of-the-art approaches, and discusses standardized techniques such as power control, resource allocation, spectrum separation and mode selection, carrier aggregation, load balancing and cell range expansion, enhanced inter-cell interference coordination, coordinated scheduling and beamforming, coordinated multipoint, and AI-based interference prediction methods. A structured taxonomy and comparative summary are introduced to help categorize these techniques. Several related works based on their methodologies, shortcomings, and future directions have been critically reviewed. In addition, the paper identifies open research challenges and outlines key trends that are shaping future B5G IM systems. A comparative visualization is also provided to highlight dominant and underexplored optimization objectives across IM domains. This review serves as a valuable reference for researchers aiming to understand and evaluate current and emerging solutions for interference mitigation in B5G wireless systems. Full article

In beyond fifth-generation networks, millimeter wave (mmWave) is considered a promising technology that can offer high data rates. However, due to inter-cell interference at cell boundaries, it is difficult to achieve a high signal-to-interference-plus-noise ratio (SINR) among users in an ultra-dense mmWave network environment (UDmN). In this paper, we solve this problem with the cooperative transmission technique to provide high SINR to users. Using coordinated multi-point transmission (CoMP) with the joint transmission (JT) strategy as a cooperation diversity technique can provide users with higher data rates through multiple desired signals. Nonetheless, cooperative transmissions between multiple base stations (BSs) lead to increased energy consumption. Therefore, we propose a multi-agent Q-learning-based power control scheme in UDmN. To satisfy the quality of service (QoS) requirements of users and decrease the energy consumption of networks, we define a reward function while considering the outage and energy efficiency of each BS. The results show that our scheme can achieve optimal transmission power and significantly improved network energy efficiency compared with conventional algorithms such as no transmit power control and random control. Additionally, we validate that leveraging channel state information to determine the participation of each BS in power control contributes to enhanced overall performance. Full article

This paper addresses the problem of side lobe interference in 5G networks by proposing a unique collaborative beamforming strategy based on Deep Q-Network (DQN) reinforcement learning. Our method, which operates in the sub-6 GHz band, maximizes beam steering and power management by using a two-antenna system with DQN-controlled phase shifters. We provide an OFDM cellular network environment where inter-cell interference is managed while many base stations serve randomly dispersed customers. In order to reduce interference strength and improve signal-to-interference-plus-noise ratio (SINR), the DQN agent learns to modify the interference angle. Our model integrates experience replay memory with a long short-term memory (LSTM) recurrent neural network for time series prediction to enhance learning stability. The outcomes of our simulations show that our suggested DQN approach works noticeably better than current DQN and Q-learning methods. In particular, our technique reaches a maximum of 29.18 dB and a minimum of 5.15 dB, whereas the other approaches only manage 0.77–27.04 dB. Additionally, we significantly decreased the average interference level to 5.42 dB compared to competing approaches of 38.84 dB and 34.12 dB. The average sum-rate capacity is also increased to 3.90 by the suggested strategy, outperforming previous approaches. These findings demonstrate how well our cooperative beamforming method reduces interference and improves overall network performance in 5G systems. Full article

Long-Term Evolution for Metro (LTE-M) is adopted as the data communication system in urban rail transit to exchange bio-direction train-wayside information. Reliable data communication is essential in LTE-M systems for ensuring trains’ operation safety and efficiency. However, the inter-cell inference problem exists in LTE results in throughput reduction, especially when trains are in the edge area of adjacent cells, and has negative effects on train operation. The uplink power control and radio resource scheduling scheme is studied in LTE-M system which differentiates from public cellular networks in user numbers and the availability of the trains’ locations. Since the locations of the trains are available, the interferences from the neighbouring cells can be calculated, and a location based algorithm together with soft frequency reuse is designed. In addition, a proportional fair algorithm is taken to improve uplink radio resource scheduling considering the fairness to different train-wayside communication service requirements. Through simulation, the practicability of the proposed schemes in communication system of urban rail transit is verified in aspects of radio power control and data communication throughput. Full article

Cellular mobile systems aim at aggressive spectrum reuse to achieve high spectral efficiency. Unfortunately, this leads to unacceptable interference near cell borders. To control this, network multi-input multiple-output (MIMO) can be adopted to improve coverage and cell-edge throughput through multi-cell cooperation. With network MIMO, multiple geographically separated base stations (BSs) cooperatively serve their cell-edge users (CEUs) using their antennas, acting together as a network of distributed antenna array. It can be single-user (SU) or multi-user (MU) network MIMO by coordinating channel allocation in adjacent cells. In this paper, we make a capacity comparison of SU- and MU-network MIMO. In network MIMO, a collaborative BS simultaneously serves its own cell-center users (CCUs) and CEUs, and the CEUs of other partner BSs under a power constraint. As a result, power management among three types of users (intra-cell CCUs/CEUs, inter-cell CEUs) becomes necessary. Accordingly, we propose power management methods to help raise the signal strength of inter-cell CEUs and in the meantime gratify the performance of intra-cell users. Simulation results show that MU-network MIMO with superposition coding offers much better CEU capacity than SU-network MIMO. As for the CCU capacity, MU-network MIMO is generally better than SU-network MIMO. Full article

In low-power wide area networks (LPWAN), a considerable number of end devices (EDs) communicate with the gateway in a certain area, whereas for transmitted data, a low data rate and high latency are allowed. Long-range (LoRa), as one of the LPWAN technologies, considers pure ALOHA and chirp spread spectrum (CSS) in the media access control (MAC) and physical (PHY) layers such that it can improve the energy efficiency while mitigating inter-cell interference (ICI). This paper investigates the system throughput of LoRa networks under the assumption that the interferences between EDs for exclusive regions are ignored using CSS. In order to establish an analytical model for the performance of LoRa, we introduce the pure ALOHA capture model, which is the power threshold model. For this model, we assume that the interfering power is proportional to the length of the time overlapped. In addition, we discuss LoRa gain by comparing the total throughput of LoRa with that of non-CSS. Full article

In the notion of communication system resource provision specifically, beam-forming is a concept of proficient utilization of the power of transmission. Network densification and massive MIMO allows us to control the power efficiency and can be effectively distributed among different users by reducing cost. We presented a practical scenario for the performance of massive MIMO and multi-small cell system to analyze the overall performance of the system. Our work is based on the resource allocation with optimal structural constraints to maintain the cost effectiveness while considering economic implications. The base stations located far away from the users receive attenuated signals and give rise to path loss, whereas the problems of inter cell interference also arise due to transmission from a base station to others cells. The performance of the cellular system can be enhanced with the combination of massive Mimo and small cells, where we simulate and also provide an analysis on practical system with optimal and low complexity beam-forming. The proposed scenario illustrates a structure with an optimal linear transmit beamforming regarding an efficient number of parameters to not lose optimality, which is extendable to designate any specific cellular network in consideration. Our approach exploited schemes with low complexity that are facilitating in complete solution formation, and tested them in various and all possible cases and scenarios. Full article

In this study, we enhance the almost blank subframe (ABSF) algorithm in a Long Term Evolution (LTE) heterogeneous network (HetNet) by providing a relay function. The ABSF is a technique proposed by the Third Generation Partnership Project to reduce interference in a HetNet. Despite the fact that the ABSF effectively mitigates intercell interference, it has two major disadvantages. First, the ABSF algorithm alters the scheduling policy of macro base stations. Second, it degrades the capacity of users served by femto base stations. Our proposed enhanced algorithm applies a relay function to assist victim macro user equipment (VMUE), and it reduces the side effects caused by the ABSF algorithm. Taking resource allocation and power control into account, the relay function assists VMUE in such a way that interference with other users is minimized. Via simulation results, the proposed algorithm exhibits improvements of 18% and 8% for system throughput and user satisfaction, respectively, in comparison with the conventional ABSF. Full article

The femtocell has evolved as a great solution for improving coverage and traffic offloading from the current LTE cellular networks, and it accomplishes the dreams of the high data rate for indoor mobile users. However, the exponentially expanding LTE femtocells cause interference in the network, as they share the same licensed spectrum with a macrocell. To tackle this issue, numerous interference mitigation techniques have been proposed in the literature. In this paper, we proposed an Active Power Control (APC) technique, which not only reduces Inter-Cell Interference (ICI) in a Macro User Equipment (MUE), generated from the downlink transmission power of an inadequately deployed femtocell, but also reduces unnecessary power consumption to achieve a green femtocell network. The simulation results show that the proposed APC technique effectively reduces ICI and optimizes the throughput performance of the MUE. Compared with the existing power control techniques, the APC technique provides a balanced trade-off in attaining necessary Quality-of-Service (QoS) of the Femto User Equipment (FUE) and reducing ICI to the victim MUE existing in the close proximity of the femtocell. Full article

The overlay integration of low-power femtocells over macrocells in a heterogeneous network (HetNet) plays an important role in dealing with the increasing demand of spectral efficiency, coverage and higher data rates, at a nominal cost to network operators. However, the downlink (DL) transmission power of an inadequately deployed femtocell causes inter-cell interference (ICI), which leads to severe degradation and sometimes link failure for nearby macrocell users. In this paper, we propose an adaptive network sensing (ANS) technique for downlink power control to obviate the ICI. The simulation results have shown that the ANS power control technique successfully decreases the cell-edge macro user’s interference and enhances the throughput performance of macro users, while also optimizing the coverage and capacity of the femtocell. When compared with the Femto User Equipment (FUE)-assisted and Macro User Equipment (MUE)-assisted power control technique, the proposed technique offers a good tradeoff in reducing interference to macro users, while maintaining the quality of service (QoS) requirement of the femtocell users. Full article

Most of the energy used to operate a cellular network is consumed by a base station (BS), and reducing the transmission power of a BS can therefore afford a substantial reduction in the amount of energy used in a network. In this paper, we propose a distributed transmit power control (TPC) algorithm inspired by bird flocking behavior as a means of improving the energy efficiency of a cellular network. Just as each bird in a flock attempts to match its velocity with the average velocity of adjacent birds, in the proposed algorithm, each mobile station (MS) in a cell matches its rate with the average rate of the co-channel MSs in adjacent cells by controlling the transmit power of its serving BS. We verify that this bio-inspired TPC algorithm using a local rate-average process achieves an exponential convergence and maximizes the minimum rate of the MSs concerned. Simulation results show that the proposed TPC algorithm follows the same convergence properties as the flocking algorithm and also effectively reduces the power consumption at the BSs while maintaining a low outage probability as the inter-cell interference increases; in so doing, it significantly improves the energy efficiency of a cellular network. Full article