Femtocell Base Stations Research Articles

An Improved Interference Mitigation Scheme for Femtocell Networks

Femtocell networks have gained significant attention in recent years due to their ability to improve indoor wireless coverage and capacity. However, they are susceptible to interference from neighboring cells, which significantly degrade their performance and quality of service to the end-user. The study introduced an adaptive power control technique that causes the power level of the femtocell base station to adjust dynamically to reduce the interference caused by adjacent femtocell networks, thereby adjusting the system bandwidth, carrier frequency, path loss and femtocell Base Station (BS) transmission power based on the request made by the users. The interference mitigation scheme was optimized by tuning the parameters of the power control algorithm, such as the transmit power levels and the interference thresholds. The algorithm was simulated with MATLAB simulation tools. Throughput, Signal to Interference Noise Ratio (SINR), coverage enhancement and user satisfaction were used as measurement metrics for the model using descriptive statistics. The results showed that the average performance obtained for the throughput increased by 25.88% from 3.40 X 1010 (bps) to 4.28 X 1010 (bps), and the SINR increased by 35.29% from 1.70 X 109 dB to 2.30 X109 dB for the benchmarked power control and improved power control techniques respectively. Coverage enhancement and user satisfaction were nearly 0, which indicates that the technique was of average performance. This study concluded that the new scheme enhances wider coverage to reach more users and mitigate interference while maintaining a higher level of femtocell user satisfaction.

Performance Analysis of UL-DL Decoupled Access in Two-Tier Cellular Heterogeneous Networks

With the advent of the 5th generation mobile communication technology (5G) era, cellular networks are evolving towards highly heterogeneous and ultra-dense network structures, posing challenges for achieving high communication rates. Existing coupled access methods can no longer meet user demands. As a promising solution to this issue, decoupled uplink-downlink access has gained significant attention. This paper investigates the performance of decoupled uplink-downlink access in a two-tier cellular network model. We obtain the analytical expressions of association probabilities, distance distribution, and spectral efficiency of base stations (BSs) when femto-cell BSs are selected for uplink access and macro-cell BSs are selected for downlink access by a user device. Our findings provide insights into the selection of access patterns and decoupled methods for better efficiency and quality of service. Furthermore, our model and approach can guide the design and deployment of next-generation networks to enhance performance.

Energy Efficient Clustering and Resource Allocation Strategy for Ultra-Dense Networks: A Machine Learning Framework

The ultra-dense network structure of 5G with dense femto-cells deployment, is identified as a prospective way out for the problem of growing demand for cellular services. However, optimum resource allocation among dense and random deployed femto-cell base stations (FBSs) is a challenging task since there are severe interferences. To overcome these interferences and to obtain efficient resource allocation, a two-stage cluster-based resource allocation scheme has been proposed. In the first step, an efficient dynamic clustering algorithm based on unsupervised learning is proposed which group the FBSs in an optimal number of clusters while balancing the traffic load in each cluster. Afterward, we focus on the green resource allocation problem by using a cooperative methodology. A cloud-based multi-agent reinforcement learning algorithm has been proposed in a decentralized way. The cloud server provides fast-flexible access, large storage space, and turns down operational expenditure. Further, the reinforcement model exploits a brief representation of Q-value to resolve the problem of large stateaction space, diminish the computational complexity and hasten the convergence. The proposed scheme is evaluated in real time experimental setup. The experimental results and the numerical results verify that the proposed scheme significantly improves energy efficiency with a QoS guarantee.

Secure Information Transmission for B5G HetNets: A Robust Game Approach

This article investigates the robust secure transmission problem in two-tier B5G heterogeneous networks with multiple noncollusive eavesdroppers and users, where two types of imperfect channel state information (CSI) scenarios, i.e., instantaneous and statistic CSI scenarios, are considered. Given the two-sidedness of co-channel interference in physical-layer security and the selfishness of femtocell base stations (FBSs), an imperfect-CSI-based noncooperative game framework is proposed to maximize the profits of the macro base station (MBS) and FBSs, while guaranteeing user’s Quality-of-Service (QoS) requirement in terms of outage probability. Specifically, based on the involved two CSI scenarios, the original game where the MBS and FBSs act as players is elaborated as two robust game problems. To address channel uncertainties in the objective function, the worst-case and the mean value of the channel gains are used separately. Besides, the remaining channel uncertainties embodied in the intractable outage probability constraints are treated in a unified way, i.e., the extended Bernstein approximation. The existence and uniqueness of the Nash equilibrium (NE) are analyzed, and the sufficient condition on the uniqueness of the NE is derived. Then, two robust iterative algorithms are given to approach the robust game equilibrium. Finally, numerical results are presented to verify the theoretical analysis and show the robustness and effectiveness of the proposed algorithms.

Optimizing the operator’s economy in multi-tier cellular networks with underlaid D2D communications

In this paper, we consider a three-tier cellular network, consisting of a Macrocell base station, several Femtocell base stations, cellular users, and Device-to-Device (D2D) users. Each user is attached to the Macrocell or one of the Femtocells while D2D users communicate directly. The Macrocell divides the spectrum into several subchannels. The Femtocell users are allowed to communicate over the common spectrum which is allocated to one of the Macrocell users. We consider the scenario in which the Femtocells do not interfere each other while the Macrocell users experience interference from Femtocells and vice versa. Likewise, the Macrocell users would suffer from the interferences caused by underlaid Femtocells and D2D communications in the same spectrum. The average outage probability over the shared sub-channel is investigated assuming the effect of D2D users, and the closed form expressions are obtained in an interference limited scheme. Then, the object function is defined to minimize the operator’s cost function for establishing Femtocell network. The problem is generally non-convex and hence, it is solved through separation to subproblems to derive the near-optimal solutions for the intensity of Femtocells and power allocation. The analytical results are verified by the simulation results, which show that although the D2D and Femtocells improve the network performance by handling the data traffic, increasing the D2D users’ transmission power and the intensity of physical distribution of Femtocells increase the network cost function.

Stackelberg game approach for resource allocation in device-to-device communication with heterogeneous networks

Device-to-device communication is an enabling technology for direct connection between two or more devices/users without the intermediation of a base station (BS). In heterogeneous device-to-device networks, technology such as femtocell suggests advantages such as improving coverage area, spectral efficiency, and increased capacity. However, several challenging issues like interference, resource allocation, and power control strategies need to be addressed in the macrocell–femtocell-D2D heterogeneous network. This research presents a solution for resource allocation in D2D networks by proposing a Stackelberg game approach to increase network performance and throughput. The proposed study examines a framework for a two-leader multiple-followers Stackelberg game in which the leaders are macrocell base station (MBS) and femtocell base station (FBS), and the numerous followers are D2D pairings. Based on their mobility in the cell zone, D2D users are divided into three types Each leader and follower are designed with a different utility function. The paper is focused to minimize the interference in the system and maximize the system throughput. The game is solved to a Stackelberg equilibrium and ensures D2D communication continues with optimal transmit power. The assignment of resources among various contending users using the Hungarian algorithm. The proposed model is validated through simulations in MATLAB. The results show that the proposed model reduced the interference in the network and increased the throughput of the system in terms of price, transmit power and D2D rate.

Performance analysis of 5G heterogeneous networks under the impact of aggregate interference over Nakagami‐m fading channels

AbstractHeterogeneous networks (HetNets), which consist of ultra‐dense femtocell networks underlaid by traditional homogenous macrocell networks, are a promising option for the exceedingly high data rate demands of upcoming 5G communications. The densely deployed femtocells in cochannel mode cause severe interference because of the short distances between cochannel cells, which is the main challenge for femtocell deployment in HetNets. The HetNets are modeled based on stochastic geometry, which is assumed to distribute the interfering nodes as a point process. Specifically, in this article, a homogeneous Poisson point process is used to model the random distribution of macrocell users and femtocell base stations. Based on the complementary cumulative distribution function of the received signal to interference ratio at the macrocell base stations and femtocells, closed‐form expressions are derived for the outage probability. Further, closed‐form expressions are derived for the network throughput and energy efficiency of femtocells. Finally, theoretical and simulation results are discussed for the derived expressions under different system parameters.

Bargaining solutions in heterogeneous networks: A reinforcement learning‐based approach

To enhance the performance and the coverage area of the next-generation heterogeneous wireless networks (HetNets), smaller cells such as femtocells are deployed. A reasonable resource allocation strategy is crucial for the operation of such systems. In this work, the Nash bargaining solution (NBS), Kalai–Smorodinsky bargaining solution (KSBS), and a proposed bargaining solution, which is the combination of NBS and KSBS, are studied to ensure the efficiency and fairness in the transmission rate allocation among femtocells. The mentioned bargaining solutions are optimised subject to the rate constraints due to the Han–Kobayashi (HK) rate splitting scheme, and a maximum tolerable interference caused by femtocell base stations (FBSs) at the macrocell user equipment. Two methods are used to address the bargaining solutions' optimisations. First, the conventional optimisation-based method is used for the situations where the channel gains are known, then a reinforcement learning-based algorithm for a real environment is proposed without being aware of the channel gains. To accelerate the speed of the learning process and to initialise the values of quality functions, the hotbooting technique is used. The bargaining solutions are compared by fairness and efficiency criteria in both methods. Numerical simulations show that the proposed reinforcement learning-based algorithm achieves the same performance derived from the conventional optimisation method. First, this paper studies the two well-known Nash and Kalai–Smorodinsky bargaining solutions as the good tools to establish fairness in rate allocation problem among femtocells in a HetNet. Then a new bargaining solution is proposed as the combination of the two bargaining solutions. The fairness and the efficiency of the allocated rates to femtocells as the output of optimisation problems of bargaining solutions are compared via Jain index criterion (as the fairness metric) and inverse price of anarchy criterion (as the efficiency metric). Moreover, the femtocell base stations are allowed to use Han–Kobayashi signalling scheme to send their signals in private and common messages which results in the best-known achievable rate region. Two methods are used to solve the optimisation problems: the conventional optimisation method and the reinforcement learning-based method (to formulate a real-world model with the unknown channel gains). It is shown that the proposed bargaining solution (in both methods) results in fairer rates than Nash and Kalai–Smorodinsky bargaining solutions while all of them are efficient.

Robust Resource Allocation for Two-Tier HetNets: An Interference-Efficiency Perspective

The heterogeneous network (HetNet) is a promising network for beyond 5G to improve network capacity and spectral efficiency by developing low-power small cells within macro networks. Therefore, appropriate resource allocation schemes should be designed to balance between data rates and the cross-tier interference among different cells. To improve system robustness and also reduce the harmful interference to macrocell users (MUs), in this paper, we maximize the total interference efficiency (IE) (i.e., the ratio of the sum data rates of femtocell users (FUs) to the total cross-tier interference from femtocell base stations (FBSs) to MUs) with imperfect channel state information in a two-tier orthogonal frequency division multiple access based HetNet by jointly optimizing the transmit power of the FBS and the subcarrier allocation factor. Meanwhile, the outage rate constraint of each FU, the outage interference constraint of each MU, the maximum transmit power constraint of the FBS, and the subcarrier assignment constraint are considered simultaneously. The considered problem belongs to a mixed-integer non-linear programming problem and thus is NP-hard. The original problem with uncertain parameters is transformed into a deterministic and convex one solved by using the quadratic transformation approach, the variable relaxation approach, and Lagrange dual theory. The feasible region analysis and robust sensitivity are provided. Simulation results demonstrate that the proposed scheme has a lower interference to the MU and higher IE by comparing it with the traditional schemes.

A study and Description of the Femtocells Wireless Communication Networks

In this paper the femtocell base station called as Femtocell Access Point (FAP) was descriped and studied. The femtocell (FAP) is fully user deployed and hence reduces the infrastructure, maintenance and operational cost of the operator while at the same time providing good Quality of Service (QoS) to the end user and high network capacity gains. The surest way to increase the system capacity and data rates can be achieved efficiently in a wireless system by getting the transmitter and receiver closer to each other. In a network with nomadic users, this inevitably involves deploying more infrastructure, typically in the form of microcells, hotspots, distributed antennas, or relays. Femtocells deployed in the macrocell significantly improve the indoor coverage and provide better user experience.
 In this paper the four indoor propagation path loss models with simulated data for different scenarios at 2 GHz are presented In additions the Simulation were carried out in two different scenarios LOS and NLOS for max 50m femtocell and max 100m macrocell network. The simulation results was implemented using Matlab code software.

Power and Radio Resource Management in Femtocell Networks for Interference Mitigation.

The growth of mobile traffic volume has been exploded because of the rapid improvement of mobile devices and their applications. Heterogeneous networks (HetNets) can be an attractive solution in order to adopt the exponential growth of wireless data. Femtocell networks are accommodated within the concept of HetNets. The implementation of femtocell networks has been considered as an innovative approach that can improve the network’s capacity. However, dense implementation and installation of femtocells would introduce interference, which reduces the network’s performance. Interference occurs when two adjacent femtocells are operated with the same radio resources. In this work, a scheme, which comprises two stages, is proposed. The first step is to distribute radio resources among femtocells, where each femtocell can identify the source of the interference. A constructed table is generated in order to measure the level of interference for each femtocell. Accordingly, the level of interference for each sub-channel can be recognized by all femtocells. The second stage includes a mechanism that helps femtocell base stations adjust their transmission power autonomously to alleviate the interference. It enforces a cost function, which should be realized by each femtocell. The cost function is calculated based on the production of undesirable interference impact, which is introduced by each femtocell. Hence, the transmission power is adjusted autonomously, where undesirable interference can be monitored and alleviated. The proposed scheme is evaluated through a MATLAB simulation and compared with other approaches. The simulation results show an improvement in the network’s capacity. Furthermore, the unfavorable impact of the interference can be managed and alleviated.

A NOMA Scheme Using Oblique Projection for HetNet Uplink Under Perfect and Imperfect CSIR

The emerging non-orthogonal multiple access (NOMA) technique for fifth-generation (5G) heterogeneous network (HetNet) yields performance improvement specifically by boosting the network capacity and spectral efficiency. This paper proposes a new NOMA scheme for the uplink HetNet using oblique projection (OP) under perfect and imperfect channel state information at the receiver (CSIR). In this scheme, the OP operation performed at the femtocell base station (FBS) recovers the desired NOMA users’ signal from the composite received signal. Unlike the existing successive interference cancellation (SIC) based NOMA schemes, the proposed scheme does not demand any power control or user clustering techniques for decoding NOMA users’ data at the receiver side. Further, it does not need information exchange between users for decoding and hence the computational complexity and the signaling overhead of the system gets reduced significantly. To evaluate the performance of the proposed scheme under perfect CSIR analytically, we derive the closed-form expression for the probability of error and outage probability at the FBS receiver. We also derive the diversity order, sum-rate, and perform the computational complexity analysis of the NOMA-HetNet system employing the proposed scheme. Simulation results illustrate that the derived analytical results accurately describe the proposed NOMA scheme. We compare the performance of the proposed technique with a prevailing SIC based NOMA scheme and establish its superiority. Performance of the proposed NOMA scheme under imperfect CSIR is also studied and established that the scheme works well under this scenario also.

Energy-efficient relay selection and power allocation for multi-source multicast network-coded D2D communications

Device-to-device (D2D) communication improves spectrum efficiency (SE) and increases system capacity. Heterogeneous networks comprise macrocell and several small cells, such as picocells and femtocells, where femtocells are more efficient. In cooperative communications, one or several additional nodes help to send data from source to destination to improve the quality of service (QoS). Network coding (NC) in cooperative networks can extend data rate and coverage area of D2D communication. The purpose of this article is to minimize power consumption of transmitting nodes during network-coded cooperative D2D transmission to reduce the interference on co-channel transmissions. In this study, we consider cooperative multicast D2D communication with NC, where femtocell base stations (FBSs) are used as relay. We propose a method based on energy efficiency (EE) maximization for relay selection and power allocation for multi-source network-coded cooperative D2D communication in heterogeneous cellular networks. We present a solution to the proposed method and evaluate its performance. The results show that the introduced method significantly improves the SE and EE compared to the coordinated multi-point (CoMP) transmission, multi-source direct D2D communication (D-D2D), and other works.

Q-Learning-Based Adaptive Power Control in Wireless RF Energy Harvesting Heterogeneous Networks

This article investigates adaptive power control in wireless radio frequency energy harvesting (EH) femtocell heterogeneous networks (HetNets), where some EH devices desire to harvest energy from the signals transmitted from both macro base stations (BSs), and femtocell BSs. An optimization problem is formulated to maximize the sum capacity of femtocells while satisfying the EH requirements of energy users, and information quality of service (QoS) requirements of macrocell users by adaptively controlling the transmit power of femtocell HetNets, where nonlinear EH model is adopted. Due to the discrete variables of transmit power, the formulated optimization problem is with combinatorial computational complexity, and cannot be solved with known solution methods. Thus, a Q-learning-based algorithm is presented, and a segmented reward function based on the distance factor, and the penalty parameter is designed. Simulation results show the effectiveness of the proposed Q-learning-based algorithm, and the presented segmented reward function. It is also demonstrated that by using the nonlinear EH model can effectively avoid the deviation brought by the traditional ideal linear EH model. Additionally, it shows that the convergence time of our proposed scheme grows linearly w.r.t. the number of femtocell BSs, and the number of selectable transmit power levels of femtocell BSs roughly.

Genetic algorithm for biobjective optimization of indoor LTE femtocell deployment

SummaryThe optimization of indoor femtocell base stations (FBS) placement is a highly complex problem in which multiple performance figures can be considered. In this paper, we propose a biobjective optimization approach based on non‐dominated sorting genetic algorithm II (NSGA‐II) to solve the indoor FBS deployment problem in residential scenarios where a single cell is deployed within the coverage of a single dominant interfering external macro base station (MBS). The optimization problem is formulated with the objective of jointly minimizing outage probability and maximizing normalized downlink average throughput. Several conditions are simultaneously considered under the framework of Monte Carlo simulations, such as the effect of co‐channel interference in uplink and downlink, buildings with arbitrary layouts, realistic transmission schemes and antenna radiation patterns, random user distributions, and a well‐established empirical path loss model. The proposed algorithm, which determines the location and orientation of the FBS's antenna that provides a suitable compromise between the two objective functions, is evaluated in this paper. First, two different experiments are proposed to investigate the algorithm convergence; then, statistical analyses are formulated to characterize the relation between the values achieved for both objective functions; finally, the computational load is evaluated. Results indicate the convergence of the proposed method towards the real Pareto front and a significant reduction of the computational time with respect to a reference method based on exhaustive search, while pointing at new criteria for the selection of the objective functions.

Using LTE-Sim in New Hanover Decision Algorithm for 2-Tier Macrocell-Femtocell LTE Network

Deployment of mini macrocell base stations can also be referred to as femtocells improve quality of service of indoor and outdoor users. Nevertheless, mobility management remains a key issue with regards to their deployment. This paper is leaned towards this issue, with in-depth focus on the most important aspect of mobility management - handover. In handover management, making a handover decision in the LTE two-tier macrocell femtocell network is a crucial research area. Decision algorithms in this research, are classified and comparatively analyzed according to received signal strength, user equipment speed, cost function and interference. However, it was observed that most of the discussed decision algorithms fail to consider cell selection with hybrid access policy in a single macrocell multiple femtocell scenario, another observation was a majority of these algorithms lack the incorporation of user equipment residence parameter. Not including this parameter boosts the number of unnecessary handover occurrence. To deal with these issues, a sophisticated handover decision algorithm is proposed. The proposed algorithm considers the user’s velocity, received signal strength, residence time as well as the femtocell base station’s access policy. Simulation results have shown that the proposed algorithm reduces the number of unnecessary handovers when compared to conventional received signal strength based handover decision algorithm.

Relay selection for multi-source network-coded D2D multicast communications in heterogeneous networks

Multicast service is considered as a useful transmission mode for future mobile social services to deliver the traffic to multiple mobile users simultaneously. Device-to-device (D2D) multicast communication enables multiple proximate users to share the contents of their common interests directly. This paper aims to present a relay selection scheme for multi-source network-coded D2D multicast communication underlying heterogeneous cellular network which consists of macrocells and femtocells. We propose two methods for selecting efficient relays from the set of femtocell base stations (FBSs). The first method, named destination-blind relay selection, identifies those idle FBSs that can correctly decode all source messages. Since all identified relays may not be necessary, this method reduces the average transmission rate. Hence, in the second method named destination-aware relay selection, we find the minimum number of required relays by maximizing the spectral efficiency to make sure that all destinations can correctly decode all source messages. In contrast to the first method, the second method requires information about destinations. We present efficient solutions for the proposed methods and obtain their performance in terms of outage probability and spectral efficiency. We also derive analytical expressions for the outage probability to verify simulation results. It is shown that the introduced methods improve the spectral efficiency compared to the direct D2D multicast, random relay selection, and coordinated multi-point transmission. Further, the presented methods achieve lower outage probability than direct D2D multicast and random relay selection methods. The proposed methods reduce the average outage probability about 17 times and increase the average spectral efficiency about 16 times in comparison with direct multi-source D2D multicast, which indicate their efficiency.

Multi-Tier Caching and Resource Sharing for Video Streaming in 5G Ultra-Dense Networks

In this letter, we formulate a multi-tier caching and resource sharing (CRS) optimization problem for a high video streaming performance in 5G ultra-dense networks. Particularly, in user tier, the optimal sets of spectrum owning users (SUs) with available downlink resources, caching users (CUs) with cached video versions, and normal users (NUs) requesting the video versions are tripartite for video streaming over device-to-device (D2D) communications. In femto tier, the optimal caching strategy is found to indicate which video versions and where to cache them in the femtocell base station (FBSs). By cooperating with the video versions cached in macro tier, i.e., macro base station (MBS), the mobile users (MUs) can receive the video versions from D2D communications, FBSs, and MBS flexibly. The objective of the CRS solution is to maximize the video playback quality, while saving the caching storage of FBSs and satisfying a given throughput required by MUs and a given target signal to interference plus noise ratio of SUs.

Rate Maximization for Hybrid Access Femtocell Networks With Outage Constraints Based on Pricing Incentive Mechanism

Wireless services are developing rapidly and user requirements also are becoming more demanding. Femtocell networks have great potential in many aspects, especially in expanding the capacity and increasing the coverage of traditional cellular networks. However, it is challenging to motivate femtocell base stations (FBSs) to voluntarily adopt a hybrid access strategy to provide services and access to macrocell users (MUEs). In order to maximize the transmission rate of users, we propose an incentive mechanism in two-tier femtocell networks including a macrocell and multiple femtocells that share the spectrum. In the proposed mechanism, the macrocell base station (MBS) attempts to provide femtocells with a reward by pricing the transmission rates of the accessed MUEs, which are guaranteed by the FBSs. A Stackelberg game is developed to maximize the utility of the MBS and FBSs, and to guarantee the quality of service (QoS) of different users. An uncertain channel gain is formulated in the optimization problem and the uncertainty is restricted by a probabilistic constraint. Furthermore, a power control and nonuniform price bargaining algorithm is proposed to satisfy practical operation and obtain an optimal solution. Finally, numerical results validate the effectiveness of the proposed algorithm in terms of transmission rate improvement and outage reduction.

Precoding-Aided Spatial Modulation Assisted Joint Two-Tier Downlink Reception

In this paper, we consider a two-tier downlink scenario, where femtocell users are interested in receiving both macrocell and femtocell information simultaneously at a single frequency (joint two-tier downlink reception). Unlike in conventional handsets, which use orthogonal schemes for accommodating two-tier downlink reception, we propose two non-orthogonal schemes based on precoding-aided spatial modulation (PSM) for handling cross-tier downlink interference. In both the proposed schemes, the femtocell information is conveyed as an active antenna index at the user (spatial symbol), while the macrocell information is conveyed as a phase shift keyed (PSK) symbol on the activated antenna. Appropriate precoders are designed at femtocell base station (FBS) and macrocell base station (MBS) to manage the cross-tier interference. We derive average transmit powers at the MBS and all FBSs for both the schemes. We also optimize the transmit powers of both the schemes at a given target signal-to-noise ratio (SNR). Further, we exploit the existing cross-tier interference as a source of artificial interference for enhancing the physical layer security of femtocell users. We derive secrecy rates of the proposed schemes, and corroborate the analytical expressions derived throughout the paper with simulation results.