Inter-cell Interference Problem Research Articles

Joint AP Selection and Task Offloading Based on Deep Reinforcement Learning for Urban-Micro Cell-Free UAV Network

The flexible mobility feature of unmanned aerial vehicles (UAVs) leads to frequent handovers and serious inter-cell interference problems in UAV-assisted cellular networks. Establishing a cell-free UAV (CF-UAV) network without cell boundaries effectively alleviates frequent handovers and interference problems and has been an important topic of 6G research. However, in existing CF-UAV networks, a large amount of backhaul data increases the computational pressure on the central processing unit (CPU), which also increases system delay. Meanwhile, the mobility of UAVs also leads to time-varying channel conditions. Therefore, designing dynamic resource allocation schemes with the help of edge computing can effectively alleviate this problem. Thus, aiming at partial network breakdown in an urban-micro (UMi) environment, an urban-micro CF-UAV (UMCF-UAV) network architecture is proposed in this paper. A delay minimization problem and a dynamic task offloading (DTO) strategy that jointly optimizes access point (AP) selection and task offloading is proposed to reduce system delay in this paper. Considering the coupling of various resources and the non-convex feature of the proposed problem, a dynamic resource cooperative allocation (DRCA) algorithm based on deep reinforcement learning (DRL) to flexibly deploy AP selection and task offloading of UAVs between the edge and locally is proposed to solve the problem. Simulation results show fast convergence behavior of the proposed algorithm compared with classical reinforcement learning. Decreased system delay is obtained by the proposed algorithm compared with other baseline resource allocation schemes, with the maximize improvement being 53%.

Quantum Computing Based Optimization for Intelligent Reflecting Surface (IRS)-Aided Cell-Free Network

Intelligent reflecting surface (IRS) enables the control of propagation characteristics and is attracting considerable attention as a technology to improve energy utilization efficiency in 6th generation mobile communication systems. As cell-free networks with multiple distributed base stations (BSs) can communicate in a coordinated manner, they are being actively researched as a new network architecture to resolve the problem of inter-cell interference in conventional cellular networks. The introduction of the IRS into the cell-free network can avoid shadowing at a lower cost with less power consumption. Thus, in this study, we considered the case of communication with user equipment (UE) in a shadowing environment using IRS in a cell-free network that contained distributed BSs with a single antenna. Moreover, the selection of multiple access methods was derived according to the numbers of BSs, IRSs, and UEs. In addition, we proposed a quadratic unconstrained binary optimization formulation to optimize the IRS reflection coefficient using quantum computing. The simulation results verified that the application of the proposed method resulted in a more efficient communication. Thus, this study clarifies that the optimum control method in every communication environment and aims to act as a stepping stone to optimize the entire cell-free system.

Writing on dirty flash memory: Combating inter-cell interference via coding with side information

High-density flash memories suffer from inter-cell interference (ICI) which threatens the reliability of stored data. In order to cope with the ICI problem, we propose a channel coding scheme with channel state information of flash memories (i.e., side information of ICI). This side information is obtained before writing data into flash memories and incorporated during the encoding stage. We show that flash memories under ICI problem can be transformed into the model of memory with defective cells due to the unique asymmetry property between write (page write) and erase (block erase) operations. Then, the channel coding for memory with defective cells is employed to combat ICI. Simulation results support that the proposed scheme with the ICI side information can effectively improve the decoding failure probability.

Resource Allocation in NOMA-Based Self-Organizing Networks Using Stochastic Multi-Armed Bandits

To achieve better connectivity in future communication networks, the deployment of different types of access points (APs) is underway. APs are expected to be equipped with self-organizing capabilities to reduce costs. Moreover, due to the spectrum crunch, frequency reuse among the deployed APs is inevitable, exacerbating the problem of inter-cell interference (ICI). Therefore, ICI mitigation in self-organizing networks (SONs) is commonly identified as a key radio resource management mechanism to enhance performance. To this end, this paper proposes a novel solution for the uncoordinated channel and power allocation problems. Based on the multi-armed bandits (MAB) framework, the proposed technique does not require any communication between the APs. The case of varying channel rewards across APs is considered. In contrast to previous work on channel allocation using the MAB framework, APs are permitted to choose multiple channels for transmission. Moreover, non-orthogonal multiple access is used, allowing multiple APs to access each channel simultaneously. This results in an MAB model with varying channel rewards, multiple plays and non-zero reward on collision. The proposed algorithm has an expected regret in the order of <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">O</i> (log <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> T), with extensive numerical results revealing it significantly outperforms a well-known baseline algorithm in terms of energy efficiency.

Location-Based Resource Allocation in Ultra-Dense Network with Clustering.

With the rapid deployment of present-day mobile communication systems, user traffic requirements have increased tremendously. An ultra-dense network is a configuration in which the density of small base stations is greater than or equal to that of the user equipment. Ultra-dense networks are considered as the key technology for 5th generation networks as they can improve the link quality and increase the system capacity. However, in an ultra-dense network, small base stations are densely positioned, so one user equipment may receive signals from two or more small base stations. This may cause a severe inter-cell interference problem. In this study, we considered a coordinated multi-point scenario, a cooperative technology between base stations to alleviate the interference. In addition, to suppress the occurrence of severe interference at the cell edges, link formation was carried out by considering the degree of cell load for each cluster. After the formation of links between all the base stations and user equipment, a subcarrier allocation procedure was performed. The subcarrier allocation method used in this study was based on the location of base stations with clustering to improve the data rate and reduce the interference between the clusters. Power allocation was based on the channel gain between the base station and user equipment. Simulation results showed that the proposed scheme delivered a higher sum rate than the other resource allocation methods reported previously for various types of user equipment.

Distributed Precoding Using Local CSIT for MU-MIMO Heterogeneous Cellular Networks

Cell densification is a key driver to increase area spectral efficiencies in multi-antenna cellular systems. As increasing the density of base stations (BSs) and users that share the same spectrum, however, both inter-user-interference (IUI) and inter-cell interference (ICI) problems give rise to a significant loss in spectral efficiencies in such systems. To resolve this problem under the constraint of local channel state information per BS, in this paper, we present a novel noncooperative multi-user multiple-input multiple-output (MIMO) precoding technique, called signal-to-interference-pulse-leakage-pulse-noise-ratio (SILNR) maximization precoding. The key innovation of our distributed precoding method is to maximize the product of SILNRs of users per cell using local channel state information at the transmitter (CSIT). We show that our precoding technique only using local CSIT can asymptotically achieve the multi-cell cooperative bound attained by cooperative precoding using global CSIT in some cases. We also present a precoding algorithm that is robust to CSIT errors in multi-cell scenarios. By multi-cell system-level simulations, we demonstrate that our distributed precoding technique outperforms all existing noncooperative precoding methods considerably and can also achieve the multi-cell bound very tightly even with not-so-many antennas at BSs.

CoMP Transmission in Downlink NOMA-Based Heterogeneous Cloud Radio Access Networks

In this paper, we investigate the integration between the coordinated multipoint (CoMP) transmission and the non-orthogonal multiple access (NOMA) in downlink heterogeneous cloud radio access networks (H-CRANs). In H-CRAN, low-power high-density small remote radio heads (SRRHs) are underlaid by high-power low-density macro RRH (MRRH). However, co-channel deployment of the different RRHs gives rise to the problem of inter-cell interference that significantly affects system performance especially the cell-edge users. Thus, the users are first categorized into Non-CoMP users and CoMP users based on the relation between the useful signal to the dominant interference signal. The Non-CoMP user is the user equipment (UEs) having high signal-to-interference-plus-noise-ratio (INR) and hence associates with only one RRH. On the other hand, the CoMP user, cell-edge user, is the UE that experiences less distinctive received power with the best two RRHs. In the proposed CoMP-NOMA framework, each RRH schedules CoMP-UE and non-CoMP-UE over the same transmission channel using NOMA. We first design an analytical framework based on tools from the stochastic geometry to evaluate the performance of the proposed framework (CoMP-NOMA) which is based on H-CRAN in terms of the average achievable data rate for each NOMA UE. We then examine the spectral efficiency of the proposed CoMP-NOMA based H-CRAN. Simulation results are provided to validate the accuracy of the analytical models and to reveal the superiority of the proposed CoMP-NOMA framework compared with conventional CoMP orthogonal multiple access (CoMP-OMA) techniques. By reaping the benefits of both JT-CoMP and NOMA, we prove that the proposed framework can successfully deal with the inter-cell interference by using CoMP and improve the network's spectral efficiency through NOMA technique. We also show that, with an appropriate power allocation coefficient setting at the Non-CoMP-UEs, a fairness performance can be achieved between the CoMP-UEs and the Non-CoMP-UEs.

Dynamic Clustering and Coordinated User Scheduling for Cooperative Interference Cancellation on Ultra-High Density Distributed Antenna Systems.

This paper proposes dynamic clustering and user scheduling for previously conceived inter-cluster interference cancellation scheme on ultra-high density distributed antenna system (UHD-DAS). UHD-DAS is composed of one central unit (CU) and densely deployed remote radio units (RUs) serving as small cell access points. It can enhance spatial spectral efficiency by alleviating traffic load imposed per radio unit; however, intenser small cell deployment revives the inter-cell interference (ICI) problem. Cell clustering, cooperation of multiple RUs, can mitigate ICI partially, whereas inter-cluster interference (ICLI) still limits its possible capacity. Simplified ICLI cancellation based on localized RU cooperation was previously proposed to mitigate interference globally. The resolved issue is that it required frequency reuse distance to fully obtain its interference cancellation ability. This paper introduces dynamic clustering with coordinated user scheduling to ensure reuse distance without extra frequency reuse. Joint dynamic clustering and ICLI cancellation can effectively work and almost reaches ideal performance as full cooperative spatial multiplexing transmission.

Interference Coordination for 5G New Radio

The arrival of the 5G NR provides a unique opportunity for introducing new inter-cell interference coordination (ICIC) mechanisms. The objective is twofold: to better exploit the benefits of ICIC in coherence with the rest of radio resource management (RRM) principles in 5G, and to support new services and deployment scenarios. We propose several enhanced techniques. In the uplink, inter-cell coordination of the pilot sequence configuration mitigates the inter-cell interference problem of such pilots, which is especially severe for cell-edge users. In the downlink, coordinated small cell DTX aims at network interference control and energy consumption reduction, whereas intercell rank coordination can unleash the potential of advanced receivers with minimal control overhead. Besides, on-demand power boosting and coordinated muting can be tailored to meet URLLC requirements. The simulation results quantify the performance benefits of the different techniques under heterogeneous key performance indicators (KPIs). We also discuss the standardization effort required for having each of these techniques included in the 5G NR specifications.

Resource-aware relay selection for inter-cell interference avoidance in 5G heterogeneous network for Internet of Things systems

The fifth-generation (5G) heterogeneous networks (HetNets) are gaining attention to be a key enabler that provides promising infrastructure for the massive proliferation of Internet of Things (IoT) devices and their services. However, one of the key challenges that the IoT terminals face is the inter-cell interference (ICI) problem since the 5G HetNets are generally deployed based on a co-channel model that overlays numerous pico eNodeBs (eNBs) on top of macro eNBs grid on the same frequency band. In order to overcome the ICI problem, we propose a relay-assisted communication approach by which the data of interfered IoT terminal (iIT) in the ICI area is relayed, via a device-to-device connection, to its neighboring IoT terminals which has good signal to and from the network. The key component in this proposed scheme is the relay selection algorithm which aims at maximizing the network resource availability at the highest priority, as well as device data rate. Firstly, resource availability maximization (RAmax) function determines an eNB that has maximum resource availability among all neighboring eNBs of the iIT to be a gateway node for the relay connection to the network (referred to as reNB). Among the IoT terminals associated with the reNB, a relay IoT terminal (called rIT) linking iIT and reNB is selected by a condition of maximum channel quality to the reNB. Simulation results show that our proposed algorithm increases total network throughput and the number of simultaneously served ITs by 44% and 20%, respectively.

A Low Complexity Precoding Algorithm Based on Parallel Conjugate Gradient for Massive MIMO Systems

Linear precoding algorithms with low complexity in massive multi-in multi-out system have always been a hot research topic to solve the problem of inter-cell interference. In this paper, we proposed a conjugate gradient-based regularized zero-forcing (CG-RZF) precoding algorithm, with which the base station can directly obtain the transmitted signal after RZF precoding and avoid directly solving the inverse matrix in RZF. Moreover, an RZF precoding algorithm based on a parallel conjugate gradient (Parallel-CG-RZF) is also proposed, which can optimize initial values and iterative process of the aforementioned CG-RZF precoding algorithm. The simulation results have shown that the proposed CG-RZF and the optimized Parallel-CG-RZF precoding algorithm can significantly improve the performance of bit error rate with fast convergence speed compared with other precoding algorithms and can reduce the number of global communications. Meanwhile, the calculation complexity of the proposed CG-RZF and Parallel-CG-RZF precoding algorithm is much lower than the optimized Chebyshev iteration algorithm.

Comparative Analysis of Intercell Interference Mitigation Techniques in LTE-A Network

The performance of long term evolution-advance (LTE-A) depends on different factors such as spectral efficiency, throughput and signal interference to noise ratio (SINR). Interference causes the performance of a network to be grassed to very low level, it directly affects the parameters such as noise interference, receiving diversity and system receiving gain so to mitigate the interference in LTE-A network is very important. Interference occurs in two forms, intra-cell interference and inter-cell interference. Intra-cell interference is removed by orthogonal frequency division multiple access, but the problem of inter-cell interference still exists due to reception of signals from two adjacent base stations at same frequency on user equipment, so coordination is applied between the cells to reduce the interference between the cells. This paper focuses on coordination between the base stations using dynamic cooperative Base Station selection (DCBS). In this paper, SINR, system capacity, minimum and maximum rates of the system are analyzed when coordination is applied between the cells. Three different scenarios are discussed in this paper, which includes coordinated multipoint transmission and reception (COMP), non-COMP and DCBS and then the results of these scenarios are compared.

Joint ABS and user grouping allocation for HetNet with picocell deployment in downlink

In order to resolve the co-channel inter-cell interference problem in heterogeneous networks (HetNet), the feature of almost blank subframes (ABS) in the time domain of the enhanced inter-cell interference coordination (eICIC) is utilized. In this paper, an ABS configuration design is developed on downlink in HetNet and the associated resource allocation problem for maximizing the system performance with fairness among user equipments (UEs) is considered. Compared to conventional problems, the resource assignment problems include the configuration of ABS pattern and the resource allocation for macro UEs and pico UEs, which aims to maximize the downlink throughput and balance the traffic offloading in intra-frequency HetNet deployments. First, this paper introduces an ABS pattern design by using the channel condition, which is developed in terms of the time domain resource. Subframes are categorized as protected or normal subframes for reducing interference impact to pico UEs. Based on the configuration of the ABS pattern, we develop a grouping strategy to determine which pico UEs use either protected or normal subframes. Besides, the assignment of resource blocks with respect to the resource in the frequency domain is developed along with the fairness among UEs. The proposed joint allocation scheme takes the system throughput and the fairness into account, and has better performance than the existing schemes. Simulation results also reveal that the performance of the proposed joint allocation scheme approximates the optimal solution with the full search scheme.

Optimal Contract Design for Joint User Association and Intercell Interference Mitigation in Heterogeneous LTE-A Networks With Asymmetric Information

We study the problem of joint user association and intercell interference (ICI) mitigation in heterogeneous long-term evolution advanced (LTE-A) networks, presuming the absence of the precise global channel state information (CSI). We confront this problem from a contract-theoretic perspective and model the considered network as a labor market where the LTE evolved NodeBs (eNBs) are regarded as the employers offering a contract to the employees (cellular users). We explore a scenario where the wireless channels are ordered into different types according to their link gains and the cost of power consumption. It is assumed that each user knows the type of its channel but is not aware of the types of the channels belonging to other users. Hence, the channel type is regarded as the private information which is known only by the corresponding user. Under the presence of such asymmetric information, the eNBs formulate the optimal contract given by a set of the contract items (the combinations of user association, allocated spectrum, and power) and pass these items to the users, who then select the best contract items according to their channel types. The performance of a proposed contract-based resource allocation mechanism has been evaluated using the OPNET-based simulations. It has been demonstrated that the efficiency of a contract-based mechanism with asymmetric information is close to the optimal method (where the network resources are allocated based on the precise CSI). It has also been shown that the contract-based method outperforms the other relevant resource allocation techniques in terms of the total network service rate and signal-to-noise ratio.

Dynamic Frequency Reuse: A Method for Interference Mitigation in OFDMA Based LTE-A Networks

Spectrum scarcity is one of the most discussed restraining aspects in wireless communication system. To solve this issue Frequency Reuse (FR) concept is introduced. It is a promising development to fulfil the requirement of Long Term Evolution Advanced (LET-A). With the introduction of FR comes the problem of Inter Cell Interference as the neighboring eNodeBs (eNB) which uses the same frequency band that will act as an interference source. In this paper, a Dynamic Frequency Reuse (DFR) method is anticipated. Continuous optimization of resource allocation of each cell is considered in this method. The important focus of the paper is to expand the capacity of the users placed in cell edge areas by reducing out of cell interference. Simulation has been done to prove that the proposed scheme leads to efficient resource management.

Centralized versus decentralized multi-cell resource and power allocation for multiuser OFDMA networks

The exponential growth in the usage of mobile networks along with the increasing number of User Equipments (UEs) are exacerbating the scarcity of frequency resources. Dense frequency reuse on the downlink of multiuser Orthogonal Frequency Division Multiple Access networks leads to severe Inter-Cell Interference (ICI) problems. Resource and power allocation techniques are required to alleviate the harmful impact of ICI. Contrarily to the existing techniques that consider single-cell resource and power allocation problem without taking ICI into account, we formulate a centralized downlink multi-cell joint resource and power allocation problem. The objective is to maximize system throughput while guaranteeing throughput fairness between UEs. We demonstrate that the joint problem is separable into two independent problems: a resource allocation problem and a power allocation problem. Lagrange duality theory is used to solve the centralized power allocation problem. We also tackle the resource and power allocation problem differently by addressing it in a decentralized manner. We propose a non-cooperative downlink power allocation approach based on game theory. The players are the base stations, and each base station seeks to maximize its own utility function. We investigate the convergence of our proposed centralized and decentralized approaches, and we compare their performance with that of state-of-the-art approaches.

Turbo Receiver With Dual-Loop Dual-List Update for Inter-Cell Interference Mitigation in Heterogeneous Networks

Inter-cell interference (ICI) may considerably degrade the detection performance of receivers in heterogeneous networks (HetNets). To increase the spectrum efficiency per area, the cell ranges of small cells may be expanded, making the ICI problem more severe. Furthermore, to pursue higher data rate, spatial multiplexing is often applied, incurring inter-antenna interference (IAI). This paper presents a turbo receiver with a dual-loop dual-list update (TRDDU) structure that efficiently detects data signal deteriorated by both ICI and IAI. The proposed lists maintained several likely data vectors and interference vectors, facilitating the receiver to more efficiently determine the most-likely solution. In addition, a dual-loop update algorithm was proposed to enhance the iteration efficiency. Moreover, two design techniques were proposed to reduce the detection complexity. Simulation results showed that the error rate performance of TRDDU is close to that of a receiver in the ICI-free scenario. The complexity needed by TRDDU is only 3.5% that of the receiver that considers all possible interference vectors. In addition, the TRDDU complexity is only approximately 1.56 times that of a successive-interference-cancellation-based receiver. Finally, an over-the-air experiment was conducted to validate the effectiveness of the proposed TRDDU, and the results demonstrated the feasibility of this receiver in the field.

Row-by-Row Coding Schemes for Inter-Cell Interference in Flash Memory

Inter-cell interference (ICI) is a significant cause of errors in flash memories. In single-level cell (SLC) flash memory, ICI arises when 1 0 1 patterns are programmed either in the horizontal or vertical directions. Since data pages are written sequentially in horizontal wordlines, one can mitigate the effects of horizontal ICI by applying conventional constrained codes that forbid the 1 0 1 pattern. This approach does not address the problem of vertical ICI, however. In this paper, a row-by-row coding technique that eliminates vertical 1 0 1 patterns while preserving the sequential wordline programming order is presented. This scheme, though efficient, necessarily suffers a rate loss of almost 20%. We therefore propose another coding scheme, combining a weak constraint on vertical 1 0 1 patterns with a systematic error-correcting code, that can mitigate vertical ICI errors while achieving a higher overall coding rate, provided that the vertical ICI error probability is sufficiently small. Some extensions for multi-level cell (MLC) flash memory are discussed as well.

A Framework to Evaluate Fairness in Fractional Frequency Reuse Based Cellular Networks

The focus in Mobile communication networks has been addressed to high data rate networks that offer high quality of service. Long Term Evolution Advanced (LTE-A) technology has been the first to completely fulfill 4G requirements. However, performance gains remain limited due to severe interference levels. For this reason, the Inter-Cell Interference (ICI) problem is one of the main challenges in LTE-A systems. In order to deal with this ICI problem, in this paper we propose a novel framework to analyze the fairness of several scheduling techniques when Fractional Frequency Reuse (FFR) schemes are used. We evaluate the system performance of a typical FFR-based LTE-A scenario. Performance results show the optimum values of the Signal to Interference plus Noise Ratio and partition bandwidth for frequency reuse that maximizes the spectral efficiency. Fairness evaluation has been done in terms of the Gini index, showing a trade-off between spectral efficiency and fairness among users. In that sense, the proposed Truncated-Equal Transmission Rate scheduling policy is able to adjust this trade-off by means of a parameter \(\varepsilon\).

Inter-cell Interference Mitigation through Flexible Resource Reuse, LP-OFDM and Coordination techniques for LTE Advanced in Dense Urban Area

&lt;p&gt;&lt;em&gt;The inter-cell interference problem is a key issue in LTE Advanced system especially in dense urban environments. This paper present a new inter-cell interference reduction technique for LTE Advanced downlink system in dense urban area based on a new coordination algorithm with the use of linear precoding OFDM, coordination between cells and power management techniques. The objective of our new technique is to improve cell edge and centre capacity in LTE Advanced downlink system. For this purpose, we prove with real time simulations using Matlab that the S.F.R and P.F.R scheme with our algorithm is a good candidate to enhance the average cell capacity and edge user experience, without sacrificing the average cell throughput.&lt;/em&gt;&lt;br /&gt;&lt;strong&gt;&lt;/strong&gt;&lt;/p&gt;