Inter-cell Interference Research Articles

Interference mitigation using optimised angle diversity receiver in LiFi cellular network

Light-fidelity (LiFi) is an emerging technology for high-speed short-range mobile communications. Inter-cell interference (ICI) is an important issue that limits the system performance in an optical attocell network. Angle diversity receivers (ADRs) have been proposed to mitigate ICI. In this paper, the structure of pyramid receivers (PRs) and truncated pyramid receivers (TPRs) are studied. The coverage problems of PRs and TPRs are defined and investigated, and the lower bound of field of view (FOV) for each PD is given analytically. It is shown that the lower bound of FOV for TPR and PR are 20° and 30°, respectively. The impact of random device orientation and diffuse link signal propagation are taken into consideration. The performances of PRs and TPRs are compared, and optimised ADR structures are proposed by jointly considering the impact of tilt angle, FOV, and the number of PDs. For a transmitter-bandwidth limited system, the optimal PD values are 6 for PR and 9 for TPR, whereas, for a receiver-bandwidth limited system, the optimal PD value is 15. In addition, the double source (DS) cell system, where each LiFi AP consists of two sources transmitting the same information signals but with opposite polarity, is proved to outperform the single source cell (SS) system in interference limited or noise-plus-interference limited scenario. However, the SS cell system outperforms the DS cell system in a noise-limited scenario.

Pilot Assignment for Cell Free Massive MIMO Systems: A Successive Interference Cancellation Approach

In the contemporary era, considerable attention has been directed towards exploring cell-free massive multiple-input multiple-output (CF-M-MIMO) systems. This novel network paradigm has gained prominence as a potential solution for tackling the persistent challenge of inter-cell interference prevalent in traditional cellular MIMO networks. This study investigates a pilot assignment approach based on Successive Interference Cancellation (SIC) aimed at alleviating pilot contamination issues inherent in CF-M-MIMO systems. Through comprehensive numerical analyses and simulations, we demonstrate the efficacy and enhanced performance of the SIC-based approach competed with common random and greedy pilot assignment strategies. The proposed methodology addresses the critical challenge of pilot contamination, a phenomenon that severely impacts system performance and spectral efficiency. By iteratively decoding signals and canceling interference, the SIC algorithm optimizes pilot assignments, resulting in improved data rates and more efficient resource utilization. Our findings underscore the robustness and scalability of the SIC-based scheme across diverse system parameters and deployment scenarios, affirming its potential as a promising solution for enhancing the performance of CF-M-MIMO systems. Overall, this study contributes valuable insights into the design and optimization of pilot assignment strategies, offering a pathway for further research and development in the field of CF-M-MIMO systems.

RAN Slicing with Inter-Cell Interference Control and Link Adaptation for Reliable Wireless Communications

RAN Slicing with Inter-Cell Interference Control and Link Adaptation for Reliable Wireless Communications

Ergodic analysis of IRS-NOMA with inter-cell interference and Imperfect-CSI and SIC over Nakagami-m faded channel

Future wireless technology requires higher data rates, low latency, and flexibility to provide services to users. To fulfil these demands, various multiple access techniques are proposed. Among these techniques, the non-orthogonal multiple access technique (NOMA) is providing better features compared to orthogonal multiple access (OMA) techniques, such as more number of radio resources with low latency. In NOMA based communication system, if a user is lying on the cell's edge, their performance is poor. Recently, intelligent reflecting surfaces (IRS)-NOMA system is introduced to enhance its performance. To implement IRS-NOMA in a real-time scenario, the impact of inter-cell interference and imperfect-channel state information (CSI) and successive interference cancellation (SIC) is very much required. In this work, we derived analytical expressions to evaluate the Ergodic capacity of the IRS-NOMA over the Nakagami-m faded channel by considering inter-cell interference, imperfect-CSI, and SIC. By considering these factors, this work offers a comprehensive understanding of the system's capabilities and limitations. Here, two user IRS-NOMA is considered and also evaluated the analytical results by varying fading parameter (m), number of interferers (K), error in CSI and SIC, and IRS elements. These results are also supported by simulated results.

Retransmission performance in a stochastic geometric cellular network model

Suppose sender–receiver transmission links in a downlink network at a given data rate are subject to fading, path loss, and inter-cell interference, and that transmissions either pass, suffer loss, or incur retransmission delay. We introduce a method to obtain the average activity level of the system required for handling the buffered work and from this derive the resulting coverage probability and key performance measures. The technique involves a family of stationary buffer distributions which is used to solve iteratively a nonlinear balance equation for the unknown busy-link probability and then identify throughput, loss probability, and delay. The results allow for a straightforward numerical investigation of performance indicators, are in special cases explicit and may be easily used to study the trade-off between reliability, latency, and data rate.

Chip-Level Defect Analysis with Virtual Bad Wafers Based on Huge Big Data Handling for Semiconductor Production

Semiconductors continue to shrink in die size because of benefits like cost savings, lower power consumption, and improved performance. However, this reduction leads to more defects due to increased inter-cell interference. Among the various defect types, customer-found defects are the most costly. Thus, finding the root cause of customer-found defects has become crucial to the quality of semiconductors. Traditional methods involve analyzing the pathways of many low-yield wafers. Yet, because of the extremely limited number of customer-found defects, obtaining significant results is difficult. After the products are provided to customers, they undergo rigorous testing and selection, leading to a very low defect rate. However, since the timing of defect occurrence varies depending on the environment in which the product is used, the quantity of defective samples is often quite small. Unfortunately, with such a low number of samples, typically 10 or fewer, it becomes impossible to investigate the root cause of wafer-level defects using conventional methods. This paper introduces a novel approach to finding the root cause of these rare defective chips for the first time in the semiconductor industry. Defective wafers are identified using rare customer-found chips and chip-level EDS (Electrical Die Sorting) data, and these newly identified defective wafers are termed vBADs (virtual bad wafers). The performance of root cause analysis is dramatically improved with vBADs. However, the chip-level analysis presented here demands substantial computing power. Therefore, MPP (Massive Parallel Processing) architecture is implemented and optimized to handle large volumes of chip-level data within a large architecture infrastructure that can manage big data. This allows for a chip-level defect analysis system that can recommend the relevant EDS test and identify the root cause in real time even with a single defective chip. The experimental results demonstrate that the proposed root cause search can reveal the hidden cause of a single defective chip by amplifying it with 90 vBADs, and system performance improves by a factor of 61.

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.

Power control in LTE based on heuristic game theory for interference management

In the conventional LTE homogeneous network, sufficient transmit power of user equipment (UE) is determined by open-loop power control (OL-PC) and closed-loop power control (CL-PC) schemes. However, in a Het-Net environment, setting the UE’s transmit power requires delicate responsiveness to handle the severe and complicated uplink interference. In this paper, an interference-aware uplink power control mechanism based on Heuristic game theory approach is proposed for devices coexisting in a heterogeneous wireless network. Various wireless constraints like channel response, path loss, fading, shadowing, interference and metrics like SNR, SINR, throughput and bit rates are considered. Uplink power is controlled by suitably selecting the penalization factor (β) based on a simple Heuristic game theory approach considering the possible wireless constraints of each user depending on its location in the cell under consideration. The algorithm is framed in such a way to reduce inter-cell interference, limit transmit power, enhance bit rates and throughput of users. A significant improvement of 5.2% in the user coverage/distribution is achieved as a result of interference management compared to conventional power control scheme and power control with convex pricing.

A Deep Learning Approach for Universal NPRACH Detection With Inter-Cell Interference

A Deep Learning Approach for Universal NPRACH Detection With Inter-Cell Interference

Economic assesment of cellular technologies deployment under carrier aggregation techniques for inter radio access technologies

Purpose: The deployment of the fifth-generation (5G) of wireless communications that was launched worldwide in 2020 is entering its final stage in some countries. In this stage carriers apply new techniques that are boosting network performance without heavy investments of the initial build of the infrastructure. This techniques include but are not limited to carrier aggregation, 5G Non-standalone(NSA) and standalone(SA) NR modes, mmWave frequency range and higher bandwidth. Given considerable research in the area about economic and financial validation of the 5G, this work is an extension of a techno-economical assess of the cellular networks under these technologies.
 Method: Computer simulations, theroretical derivations.
 Findings: Major factors such as spectral efficiency, intercell interference and deployment cost are revisited, and updated to fit realities of the current technological progress. Finally, we use abovementioned theory and present simulation results from the city center of Kyiv city using recently developed pysim5G network simulator.
 Paper type: Scientific and practical.

AP cooperation in Wi-Fi: Joint transmission with a novel precoding scheme, resilient to phase offsets between transmitters

Multi Access-Point (M-AP) cooperation is expected to play a key role in the next-generation Wi-Fi standard (namely the upcoming IEEE WLAN 802.11bn/UHR, dubbed Wi-Fi-8), particularly in dense deployments where inter-cell interference hinders further increase in network capacity. Among the various considered AP-cooperation techniques, coherent Joint Transmission (JT) is the most ambitious, aiming at deploying an M-AP cluster as a single ‘super-AP’ serving multiple stations in a downlink Multi-User Multiple-Input Multiple-Output (DL MU-MIMO) fashion. Ideally, in the absence of practical impairments – predominantly inter-AP phase misalignment – prior-art JT schemes exhibit superior performance relative to simpler M-AP precoding schemes such as Coordinated Beam-Forming (Co-BF), equivalent to ∼10 dB Signal-to-Interference-plus-Noise-Ratio gain in certain scenarios. However, the Wi-Fi standard – being based on low-cost implementation and deployment strategies as a major driver for success – cannot guarantee the required tight inter-AP synchronization levels, thus jeopardizing the JT advantage in practice (essentially wiping out the gain relative to Co-BF, in the above scenarios). As a cure, we develop a novel MIMO-precoding scheme, which preserves most of the JT gain (∼7 out of the ∼10 dB above) while being inherently resilient to phase offsets between the APs, thus paving the way to practical incorporation of JT into Wi-Fi-8.

Two-Timescale Design for RIS-Aided Multicell MIMO Systems with Transceiver Hardware Impairments

This paper investigates the reconfigurable intelligent surface (RIS)-aided uplink multicell massive multiple-input multiple-output (mMIMO) communication system with transceiver hardware impairments (THWIs), and the practical and feasible two-timescale scheme is used to design the phase shifts of the RIS. We consider the Rician channel model and use maximal-ratio combining (MRC) technology to process the received signal at the base stations (BS). The expression of the uplink achievable rate is derived and analyzed. Moreover, the genetic algorithm (GA) is used to optimize the phase shifts of the RIS to maximize the data rate. Finally, the accuracy of the derived results is verified. The simulation results show that appropriately increasing the number of RIS reflecting elements can compensate for the performance loss caused by inter-cell interference and THWIs and reduce the demand for BS antennas, which can significantly reduce the hardware costs at the BS.

Optimum Base Station Antenna Tilt Angle for Inter-Cell Interference Limited Mobile Cellular System

This paper investigates the effect of base station (BS) antenna tilt angle on the performance of LTE-Advanced physical layer downlink channel in Inter-Cell Interference (ICI) limited scenario for five cell ranges, two carrier frequencies, and two BS antenna heights. The cellular system is deployed following the 3GPP hexagonal grid with a frequency reuse factor of one and three sectors per site. An urban based 3D ray-tracing tool is used to model the wireless channel for many BS and user equipment (UE) links. System performance is evaluated in terms of Signal power to Interference plus Noise power Ratio (SINR), received signal power, received interference power, achievable throughput (THR), Average Spectrum Efficiency (ASE) and UEs outage probability. The objective is to find the BS antenna tilt angle that provides the maximum ASE, minimum UEs outage probability, or optimum ASE and UE outage probability. The obtained simulation results unveil that the maximum ASE occurs at a tilt angle where the mean of the SINR is maximum and the mean of rms delay spread is minimum, while the minimum UEs outage occurs at a tilt angle where the received signal power is maximum. This is an important finding to facilitate the planning and the deployment of cellular system in the presence of ICI. Moreover it is found that the optimum tilt angles decrease as the cell range increase and BS antenna height decrease. The results also show that these optimum tilt angles are independent of the carrier frequency.

A New Framework of RIS-Aided User-Centric Cell-Free Massive MIMO System for IoT Networks

With its merit of inter-cell interference elimination and enhanced throughput, cell-free (CF) massive multiple-input multiple-output (MIMO) system, has attracted considerable interests in evolution of 6G Internet-of-Things (IoT) networks. Meanwhile, reconfigurable intelligent surface (RIS) has shown its potential benefit in enhancing both capacity and energy efficiency (EE). In this paper, a new framework of RIS-aided CF massive MIMO system is proposed for IoT networks, in which extra active APs are deployed closely to the passive RISs, in that way, the RIS-user channels can be approximately obtained by parameters estimated at those extra APs with acceptable loss. To avoid extra power consumption, user-centric AP selection strategy in CF system is suggested, on the basis of which, an optimization problem related to power control, precoding and RIS phase shift is formulated to maximize the sum rate. To deal with this tough three-variable optimization, a Lagrangian dual transformation and fractional programming based algorithm is proposed. In particular, the proposed algorithm can extend to optimize EE and well adapt to other RIS-aided CF systems. Simulation results reveal that the proposed algorithm can achieve superior performance in terms of both sum rate (SR) and EE.

Algorithm-Unrolling-Based Distributed Optimization for RIS-Assisted Cell-Free Networks

The user-centric cell-free network has emerged as an appealing technology to improve the wireless communication’s capacity of the internet of things (IoT) networks thanks to its ability to eliminate inter-cell interference effectively. However, the cell-free network inevitably brings in higher hardware cost and backhaul overhead as a larger number of base stations (BSs) are deployed. Additionally, severe channel fading in high-frequency bands constitutes another crucial issue that limits the practical application of the cell-free network. In order to address the above challenges, we amalgamate the cell-free system with another emerging technology, namely reconfigurable intelligent surface (RIS), which can provide high spectrum and energy efficiency with low hardware cost by reshaping the wireless propagation environment intelligently. To this end, we formulate a weighted sum-rate (WSR) maximization problem for RIS-assisted cell-free systems by jointly optimizing the BS precoding matrix and the RIS reflection coefficient vector. Subsequently, we transform the complicated WSR problem to a tractable optimization problem and propose a distributed cooperative alternating direction method of multipliers (ADMM) to fully utilize parallel computing resources. Inspired by the model-based algorithm unrolling concept, we unroll our solver to a learning-based deep distributed ADMM (D-ADMM) network framework. To improve the efficiency of the D-ADMM in distributed BSs, we develop a monodirectional information exchange strategy with a small signaling overhead. In addition to benefiting from domain knowledge, D-ADMM adaptively learns hyper-parameters and non-convex solvers of the intractable RIS design problem through data-driven end-to-end training. Finally, numerical results demonstrate that the proposed D-ADMM achieve around 210% improvement in capacity compared with the distributed noncooperative algorithm and almost 96% compared with the centralized algorithm.

On-Demand Coordinated Spectrum and Resource Provisioning Under an Open C-RAN Architecture for Dense Small Cell Networks

Mobile networks have seen more than a thousand times traffic increases in the past decade. Network operators face an ever increasing demand and cost to deploy denser networks in order to maintain the quality of services. In view of this paradigm shift, an open cloud radio access network (C-RAN) service model is studied in this work. Integrating the cross-layer functions of spectrum resource sharing, channel and power allocation, and interference management in a C-RAN architecture, we explore the feasibility of providing a scalable yet efficient broadband wireless service with dense small cell networks (DSN). The proposed methods and architecture can be applied to DSN that support the functions of (further enhanced) inter-cell interference cancelation (feICIC/ICIC) techniques of 3GPP standard, and have the potential to provide a cost-effective solution for high-quality DSN. Simulation results across an area of 100 km <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{2}$</tex-math></inline-formula> show that the proposed scheme can offer an aggregate downlink throughput of 21 Gbps over a maximum channel bandwidth of 20 MHz, which is 5 times the throughput with a typical ICIC method. Moreover, the service satisfaction degree can reach 85% under the proposed C-RAN architecture, making it a promising and cost-effective solution for future broadband wireless services.

Radio Environment Map Based Inter-Cell Interference Coordination for Massive-MIMO Systems

Massive-MIMO (M-MIMO) allows to schedule users with high gain narrow beams and to reduce intra-cell inter-beam interference. Close to cell edge, users may experience high interference from beams of neighboring cells which degrades their performance. This paper introduces low complexity inter-cell interference coordination between neighboring cells for M-MIMO systems implementing Grid of Beams (GoB) using Radio Environment Maps (REMs). The REMs are designed using the Kriging with the Covariance Tapering spatial interpolation technique and are created for the serving and the interfering beams. The interference coordination is introduced as constraints to the schedulers that avoid simultaneous scheduling of users served by highly interfering beams from the neighboring cells. The coordination decision is based on information retrieved from REMs and its quality depends on the REMs' precision. Around 72 percent performance gain in terms of mean user throughput is achieved by the REM based coordination with respect to a baseline solution without coordination, and around 40 percent gain with respect to a state of the art solution that implements coordination using information at beam level resolution.

Dynamic Resource Allocation Approach for Interference Mitigation based on NOMA in Network Operating in Both Uplink and Downlink

The new notion of Internet of Vehicles (IoV) supports Vehicle-to-Everything (V2X) communications, which play a very important role in 5G systems. Ultra-Dense-Network (UDN) and the new scheme Non-orthogonal multiple access (NOMA) are two important concepts to meet the requirements of V2X services with their remarkable capacity. However, the concept of NOMA technology, which allows multiple vehicles to be served by the same resource, can lead to interference between different active users. In addition, the extensive placement of small base stations (SBS) in UDN causes severe interference and degrades the network performance. To solve these problems, interference mitigation is widely used to avoid interference in NOMA-based UDN. In this document, we suggested a dynamic resource allocation method named Intra-cell-Inter-cell Interference Mitigation for V2X communication for UDN in uplink and downlink sense (Intra-Inter IMVN). Our algorithm aims to achieve five principals objectives, namely applying the same algorithm for both downlink and uplink modes, reducing the degree of interference, improving network performance in aspects like error rates and throughput, minimizing cost and delay when using this alternative, combining dynamic metrics to support many V2X scenarios and requirements, and dealing with two categories of interference such as inter-cell interference and intra-cell interference. Numerical results demonstrate that our suggested Intra-Inter IMVN approach offers higher performance compared to other existing algorithms as a function of various parameters.

Inter-Cell Interference Mitigation for Cellular-Connected UAVs Using MOSDS-DQN

Inter-Cell Interference Mitigation for Cellular-Connected UAVs Using MOSDS-DQN

Spatial modeling and reliability analyzing of reconfigurable intelligent surfaces-assisted Fog-RAN with repulsion

Reconfigurable Intelligent Surface (RIS), fog computing, and Cell-Free (CF) network architecture are three promising technologies for application to the Ultra-Reliable Low Latency Communication (URLLC) scenario in 6G mobile communication systems. This paper considers a RIS-assisted FogRadio Access Network (Fog-RAN) architecture where a) the repulsively distributed Fog-Access Points (F-APs) communicate in a CF manner to suppress inter-cell interference, b) RISs are introduced into the CF network to avoid shadowing and enhance the system performance, and c) fog computing evolved as cloud services providers at the edge of the network and an enabler for constructing a multi-layer computing power RAN. Then, we derive and validate the integral form of the maximum F-AP offloading probability and Successful Delivery Probability (SDP) of this RIS-assisted Fog-RAN over composite Fisher-Snedecor F fading, where the spatial effects are reconsidered with the assumption that the F-APs are modelled as a Beta Ginibre Point Process (β-GPP). The numeric and simulation results indicate that for the investigated RIS-assisted Fog-RAN, the β-GPP-based deployment of F-APs can increase maximum of 8% of the SDP within the repulsion-effective range, compared with the Matern Cluster Process (MCP)-based ones. Also, deploying more RISs per F-AP offers more significant SDP improvements.