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In this article, a joint user pairing and secure resource allocation scheme for cognitive radio inspired nonorthogonal multiple access (CR-NOMA) femtocells in the presence of a jammer base station (JBS) is proposed. In the considered CR-NOMA-based femtocells, femto base stations (FBSs) serve their femto mobile station (FMS) by sharing the resource block (RB) with macromobile stations (MMSs), while the JBS in each femtocell secures the data rate of a weak user from the eavesdropping capability of the strong FMS. The strong FMS intercepts the data rate of the weak FMS using a successive interference cancellation technique to decode their own data as per the NOMA principle. The weak FMS protects its data from the strong eavesdroppers through the JBS. The JBS generates artificial noise to confuse the strong eavesdroppers. The problem of the joint user pairing and resource allocation is formulated as an optimization problem, whose main goal is to maximize the secure sum rate of the FMS while guaranteeing the secure data rate of the weak FMS and MMS. For RB allocation, CR at the FBS senses the best RB for its FMS using the Greedy approach. To optimize the power of the FBS and JBS, a successive convex approximation scheme with a low complexity is applied. Simulation results show that our proposed scheme provides an improvement in the secure sum rate of the FMS in comparison to the conventional NOMA and preexisting orthogonal multiple access schemes.

The paper is motivated by the urgent need, imposed by the COVID-19 pandemic, for trustworthy access to secure communication systems with the highest achievable availability and minimum latency. In this regard, we focus on an ultra-dense wireless network consisting of Femto Access Points (FAPs) and Unmanned Aerial Vehicles (UAVs), known as caching nodes, where there are more than one possible caching node to handle user's request. To efficiently cope with the dynamic topology of wireless networks and time-varying behavior of ground users, our focus is to develop an efficient connection scheduling framework, where ground users are autonomously trained to determine the optimal caching node, i.e., UAV or FAP. Our aim is to minimize users' access delay by maintaining a trade-off between the energy consumption of UAVs and the occurrence of handovers. To achieve these objectives, we formulate a multi-objective optimization problem and propose the Convolutional Neural Network (CNN) and Q-Network-based Connection Scheduling (CQN-CS) framework. More specifically, to solve the constructed multi-objective connection scheduling problem, a deep Q-Network model is developed as an efficient Reinforcement Learning (RL) approach to train ground users to handle their requests in an optimal and trustworthy fashion within the coupled UAV-based femtocaching network. The effectiveness of the proposed CQN-CS framework is evaluated in terms of the cache-hit ratio, user's access delay, energy consumption of UAVs, handover, lifetime of the network, and cumulative rewards. Based on the simulation results, the proposed CQN-CS framework illustrates significant performance improvements in companion to Q-learning and Deep Q-Network (DQN) schemes across all the aforementioned aspects.

In the rapid development of wireless communications, femtocells provide tremendous improvement in coverage and quality of service for users. Macro-femto based networks are envisioned to be the de-f...

In this paper, we propose, an energy-efficient resource allocation scheme for simultaneous wireless information and power transfer (SWIPT)-Non-orthogonal multiple access (NOMA) based femtocell users with imperfect channel state information. SWIPT enhances the transmission power of Femto users and NOMA improves the spectral efficiency. Therefore, SWIPT and NOMA at Femto base station are integrated to improve the energy efficiency and spectral efficiency of femtocells. The formulated resource allocation problem is divided into subchannel allocation and power control. The preference list of Femto users and macro users is developed on the basis of their energy harvested from the Femto base station and macro base station, respectively. Then, to optimize the power of a Femto base station, a successive convex approximation low complexity technique at each Femto base station is used. Also, Dinkelbach method is used to convert the non-liner fractional problem into a subtractive problem and Lagrangian duality is used for power computation of Femto base station. Finally, the simulation results demonstrate that our proposed scheme provides 0.2% and 31.25% higher energy-efficiency in comparison to the existing EH-NOMA and EH-OFDMA schemes.

This paper presents the development and integration of a power control algorithm into the User Association Algorithm with Optimal Bandwidth Allocation (UAAOBA) to form a Hybrid Algorithm for User Association and Resource Allocation (HAUARA). The power control algorithm updates the transmit power of the Base Stations (BSs) towards a minimum transmit power that satisfies the minimum data rate requirement (1 Gbps) of the User Equipment UEs. The power update is achieved using the Newton Rhapson’s method and it adapts the transmit powers of the BSs to the number of their connected UEs. The developed HAUARA provides an optimal solution for user associations, bandwidth allocation, and transmit powers to UEs concurrently. This maximizes the network energy efficiency by coordinating the load fairness of the network while guaranteeing the quality of service requirement of the UEs. The network energy efficiency performance of the developed HAUARA is compared with that of the UAAOBA. The results show that the developed algorithm has network energy efficiency improvement of 12.36%, 10.58%, and 13.44% with respect to UAAOBA for increase number of macro BS antennas, pico BSs, and femto BSs, respectively. Also, the network load balancing performance of the developed HAUARA is compared with that of the UAAOBA. The results show that the developed algorithm has network load balancing improvement of 12.62%, 10.04%, and 10.34% with respect to UAAOBA for increase number of macro BS antennas, pico BSs, and femto BSs, respectively. This implies that the developed algorithm outperforms the UAAOBA in terms of network energy efficiency and load balancing.

With the ubiquitous demand for wireless communications, researchers have studied heterogeneous networks (HetNets) for years. Often the HetNets include a macrocell base station (MBS), several sets of macrocell users (MUs), a large number of femtocell base stations (FBSs), and femtocell users (secondary users), where the femtocells help the macrocell system relay the uplink or downlink traffic between the MUs and the MBS. In this article, we propose a novel joint information and energy cooperation method, with the aim of enhancing the spectrum and energy efficiency (EE) for cognitive HetNets. Specifically, the MUs and the femtocells harvest wireless energy from the radio frequency signal transmitted by MBS. By using the harvested energy, femtocells obtain the transmission opportunity to forward the signals of their serving users. We theoretically derive the theoretical expressions of the outage probabilities of the primary link as well as the secondary link. Then, we focus on investigating how to maximize EE by jointly considering time allocation and power control. Furthermore, we formulate the EE maximization problem, which contains the fractional form objective function and the linear inequality constraints and hence is nonconvex. To resolve this, we integrate the Dinkelbach method with convex optimization to derive the tractable and optimal solution. The numerical results demonstrate the simulations well match our theoretical analysis. Moreover, the results validate the feasibility of the proposed method for high-quality transmission without incurring extra energy consumption.

The development of wireless technology has penetrated in femtocell communication systems, where this communication system is very flexible to develop. However, with many networks running simultaneously, which is called a heterogeneous network, a combination of macrocell and femtocell networks, interference between networks is unavoidable. To resolve this interference, it can be done with adaptive power control techniques by the user. Adaptive power control can be achieved through the use of Game Theory and also known as Power Control Game (PCG). By determining the appropriate utility function, the optimal power is obtained when using the power update iteration process. The results show that in the Proposed method when it reaches a convergent condition, both femto users and macro users are able to reach SINR that exceeds the target SINR of 5.496 for femto users and 10.04 for macro users. Meanwhile, the Distributed Power Control (DPC) method is only able to achieve the SINR user value which is the same as the target SINR, which is 5 and 10 for femto users and macro users, respectively. The Proposed method produces a higher SINR value for the user than the DPC method so that in terms of achieving the target SINR, it is possible to conclude that the Proposed approach is superior to the DPC.

A case study of designing advanced telecommunication computing architecture (ATCA) framework using femtocells. A small cell is smaller than the expected base station, explicitly intended to broaden the information capacity, speed, and proficiency of a cell arrange. These low force radio access hubs can be sent inside or outside, and utilize authorized, shared, or unlicensed range. The femtocell gateway architecture is designed for a small range such as 10 m to a few kilometers. Small cells can be utilized to give in-building and open-air remote help. Mobile operators use them to expand their service coverage and additionally increment network limits. Small cells are downsized, low force, lightweight remote access base stations that are found regularly inside homes, workplaces, and shopping centers.

Femtocell deployment is an important strategy when it comes to improvement of QoS metrics in areas of poor cell coverage like indoors in an LTE environment. This, however, is accompanied by bottlenecks in resource allocation and trade-offs in accuracy for interference management in the heterogeneous two-tier network of macro and femtocell environment. To that end, we propose two schemes using radial division of cells that allocate sub-bands to both femtocell users and macrocell users which in turn, mitigates co-channel interference. Simulation results show that our proposed schemes, commonly named as radial sub-band allocation (RSA-1 and RSA-2) improve performance as measured by signal to interference and noise ratio, sum throughput, outage probability, and channel reuse efficiency while maintaining a balance in computational complexity with existing schemes like F-ALOHA. Further experimentation revealed that the proposed version also works exceedingly well in ultra-dense environments.

The diverse architectural evolution and intensive data explosion in the forthcoming 5G will have severe impacts on providing seamless and robust mobility management. In this paper, P-persistent energy-aware handover (HO) decision strategies with mobility robustness are proposed both for intra-handover cases while a femto user equipment (FUE) roams into another femto access point (FAP) and for cross-tier handover cases while a macro user equipment (MUE)/FUE roams into/out of the FAP in a dynamic cell sizing involving macro-femto two-tier networks. To approximate the densely deployed small-cells, a unique RF fingerprint (RFF)-based localization is employed to enable efficient small-cell detection by an RFF matching mechanism. The prediction of the HO trigger is jointly determined by a P-persistent decision mechanism that formulates the specific HO behaviors when an MUE/FUE roams into (HO-in) and out of (HO-out) a femtocell in terms of the correlated coverage variance and UE trajectory features, whereas the target selection follows a utility function in consideration of the UE traveling time and the achievable throughput. The closed-form stationary probabilities of the proposed VHO/HHO decisions are analyzed by a Semi-Markov-based framework. In addition, an adjustable sensing mechanism with dynamic intervals is proposed when UE is located far from the RFF matching region, which can have a positive influence on reducing unnecessary UE energy consumption. Numerical results are presented for the decision accuracy analyses (too early, too late, and ping-pong HOs), energy-efficiency, and resource utilization of the two-tier system. The comprehensive evaluations indicate that the proposed scheme can enhance the mobility robustness and enable an optimal trade-off between the energy efficiency (EE) and system capacity while eliminating the architectural impacts caused by the dynamic topology and the dense deployment for the next-generation macro-femto two-tier networks.

The paper discusses femtocell identification aspects in mobile networks such as long-term evolution (LTE) and LTE-advanced. Femtocells, or femto access points (FAPs), are new-class of base stations in addition to existing macro, microcells. Unlike these cells, femtocells implement automatic configuration principles. One of the main parameters in the automatic configuration process is among others an physical cell identifier. By considering two FAP deployment models, we discuss collision and confusion issues, which affect the proper physical cell id allocation. The first model represents a random deployment of FAPs within a (rural) macrocell area, whereas the second one, called dense urban model, constitutes placement of FAPs in a built-up area. The given study serves for the better understanding of interrelations between differently placed FAPs in term of collision and confusion events, and the obtained results can be used as a basis when designing an algorithm for automated assignment of physical cell identifier.

One promising approach to expand the coverage and enhance the performance of cellular networks is to employ multitier cellular networks. In this paper, an uplink two-tier communication network is studied, in which macrousers, femtousers, and femto access points are geometrically located inside the coverage area of a macro base station according to a Poisson point process. Each femtocell is assumed to have a fixed backhaul constraint that puts a limit on the maximum number of femto and macrousers it can service. Under this backhaul constraint, the network adopts a special open-access policy in which each macrouser is either assigned to its closest femto access point or to the macro base station. The choice is made based on the ratio between the distance of the macrouser from the macro base station and its distance from its closest femto access point. Under this model, upper and lower bounds on the outage probabilities experienced by users serviced by femto access points are derived as functions of the distance between the macro base station and the femto access point serving them. Similarly, upper and lower bounds on the outage probabilities of the users serviced by the macro base station are obtained. The bounds in both cases are confirmed via simulation results.

The deployment of heterogeneous networks (HetNets) is one of the promising approaches to meet the 5G requirements. The traditional user association approach is inefficient for HetNets due to the high transmission power of macro base stations (BSs) and the low transmission power of small cell BSs, i.e., pico and femto BSs. This approach causes macro BSs to be overloaded whereas small cell BSs are lightly loaded. To address this load imbalance in 5G HetNets, 3GPP introduced the concept of cell range expansion (CRE) where the coverage area of small cell BSs is artificially increased by adding a bias value to the power received from small cells. Although the biasing approach can better balance the load among tiers, users at the expansion area suffer from severe interference coming from neighbouring macro BSs. This work utilizes coordinated multi-point transmission (CoMP) to reduce interference. User-centric clustering where a user can be served by a number of BSs is implemented. The results have sown that user-centric CoMP can significantly improve the SINR levels of all users and cell-edge users as well.

In this paper, we initially dealt with the issue of spectrum allocation among macro (or “licensed”) and Femto (or “unlicensed”) users in an Orthogonal Frequency Devision Multiple Access (OFDMA) based dual-layer femtocell networks. This research contribution will lead to basic coin in the design of next generation (5G) wireless networks. This manuscript exemplifies the trade off issue of energy efficiency (EE) and spectral efficiency (SE) with both cooperative and non-cooperative architecture in cognitive femtocell networks. The pivotal concepts for each technology are described, along with their potential impact on 5G and the research challenges that remain. Further, the trade-off between EE and SE is reposed with respect to the state of the art. The obtained insightful observations from the trade-off analysis of EE ans SE can lead to provide design guideline for 5G wireless Networks.

Vehicular communication has emerged as a powerful tool for providing a safe and comfortable driving experience for users. Long Term Evolution (LTE) supports and enhances the quality of vehicular communication due to its properties such as, high data rate, spatial reuse, and low delay. However, high mobility of vehicles introduces a wide variety of security threats, including Denial-of-Service (DoS) attacks. In this paper, we propose an effective solution for real-time detection and localization of DoS attacks in an LTE-based vehicular network with mobile network components (e.g., vehicles, femto access points, etc.). We consider malicious data transmission by vehicles in two ways - using real identification (unintentional) and using fake identification. Our attack detection technique is based on data packet counter and average packet delivery ratio which helps to efficiently detect attack faster than traditional approaches. We use triangulation method for localizing the attacker, and analyze average packet delay incurred by vehicles by modelling the system as an M/M/m queue. Simulation results demonstrate that our proposed technique significantly outperforms state-of-the-art techniques.

In cellular networks, majority of calls and data services occur in indoor areas. In some areas, macrocell does not give adequate indoor network coverage, and thus, many households and businesses experience a poor indoor coverage problem. As a result, in those areas voice and data service quality are very poor and users do not get satisfactory services. To overcome this problem, in many indoor areas, users can use small Cell network known as Femto Base Transceiver Station (BTS) or Home Node B (HNB). Femto BTS gives strong network coverage in indoor areas and it can offload traffic from macrocell layer and improve macrocell capacity. Outdoor users connect to the macro cells and when they enter into their homes, they connect to their femtocell. However, there are some problems for deploying femto BTS in indoor areas. When femto BTS are placed in indoor areas, some macro BTS signal are transmitted from outdoor to indoor and Femto BTS signal also spreads to outside areas. This unwanted signal creates interference. To overcome these problems, interference management is very important. When a user moves from one place to another, successful handover is needed. In this work, we proposed interference management scheme by using power control. To improve mobility management services in indoor environment, we also proposed a handover (HO) procedure from one femto cell to another femto cell. MATLAB is used to implement these techniques. The results prove improved interference management and solve the challenges of higher demand of indoor network coverage and mobility management for femto cells in indoor environments.

The last decades have been characterized by an exponential increase in digital services. The demand is foreseen to further increase in the next years, and mobile networks will have to mandatorily supply connections to enable digital services with very different requirements, from ultra high speed to ultra low latency. The deployment and the coexistence of cells of different size, from femto to macro, will be one of the key elements for providing such pervasive wireless connection: the ultra dense networks (UDN) paradigm. How to associate users and base stations is one of the most investigated research topics. Many criteria can be drawn, from minimization of power consumption to optimization of throughput. In this paper we propose a new utility to optimize two of the most important features of future mobile connection: security and energy consumption. By using our utility it is possible to jointly select the base station to be activated in a UDN, and associate users to the base stations with the aim of maximizing the secure throughput by spending the minimum energy. Moreover, we propose a heuristic that allows to achieve performance very close to the optimal one with reduced complexity. Effectiveness of the proposed approach is proved by means of comparison with benchmark approaches.

Recently, as a consequence of the COVID-19 pandemic, dependence on telecommunication for remote learning/working and telemedicine has significantly increased. In this context, preserving high Quality of Service (QoS) and maintaining low latency communication are of paramount importance. In cellular networks, incorporation of Unmanned Aerial Vehicles (UAVs) can result in enhanced connectivity for outdoor users due to the high probability of establishing Line of Sight (LoS) links. The UAV’s limited battery life and its signal attenuation in indoor areas, however, make it inefficient to manage users’ requests in indoor environments. Referred to as the Cluster-centric and Coded UAV-aided Femtocaching (CCUF) framework, the network’s coverage in both indoor and outdoor environments increases by considering a two-phase clustering framework for Femto Access Points (FAPs)’ formation and UAVs’ deployment. Our first objective is to increase the content diversity. In this context, we propose a coded content placement in a cluster-centric cellular network, which is integrated with the Coordinated Multi-Point (CoMP) approach to mitigate the inter-cell interference in edge areas. Then, we compute, experimentally, the number of coded contents to be stored in each caching node to increase the cache-hit-ratio, Signal-to-Interference-plus-Noise Ratio (SINR), and cache diversity and decrease the users’ access delay and cache redundancy for different content popularity profiles. Capitalizing on clustering, our second objective is to assign the best caching node to indoor/outdoor users for managing their requests. In this regard, we define the movement speed of ground users as the decision metric of the transmission scheme for serving outdoor users’ requests to avoid frequent handovers between FAPs and increase the battery life of UAVs. Simulation results illustrate that the proposed CCUF implementation increases the cache-hit-ratio, SINR, and cache diversity and decrease the users’ access delay, cache redundancy and UAVs’ energy consumption.

The number of devices connected to Internet of Things (IoT) and massive machine-type communication (mMTC) networks is expected to increase exponentially in the next generation of wireless communication systems, resulting in a new type of “massive” random access network. However, most of the work in this emerging field considers the single-hop setting with direct communication between the users and a fully-equipped base station. In contrast, this work explores the massive random access problem in a two-hop relay setting where users access the network through a femto- or pico-cell relay which itself only has a limited amount of bandwidth/power. We present two low-complexity relaying schemes designed to minimize power consumption and discuss their tradeoffs using numerical simulations.

The increasing demand for varied wireless applications urges the development of an efficient resource allocation mechanism that provides required rate satisfaction and interference mitigation. Femtocell deployment provides capacity and coverage improvement and service quality to indoor users. However, overlay deployment of femtocells makes resource and interference management a bit challenging. Thus, a review on the resource allocation strategies for heterogeneous macro–femto networks is conducted. A self-organized resource allocation (SO-RA) scheme was implemented to mitigate co-layer interference in the downlink transmission for a macro–femto networks. An analysis on the SO-RA scheme was conducted, considering the cross-layer interference between macrocell and femtocell. A modification to the system was proposed to mitigate the cross-layer interference by adjusting the transmit power of femto base station. The resulting modified scheme and the SO-RA scheme were compared with existing schemes like reuse-1 and simple macro network for various system parameters. The modified SO-RA scheme achieves the best performance among all the four schemes. It results in improved throughput, fairness performance, and interference mitigation compared with the SO-RA scheme.

Fifth generation (5G) is a forthcoming mobile network technology, which is most likely to be initiated in India by 2020 through different top mobile operators. In 5G technology, the mobile consumers will be given extreme importance compared to other features. In this work, an effort is made to analyze the different existing generations of mobile wireless technology in terms of effective energy consumption by the mobile. Even though fifth-generation technology for smart phone network has improved the speed of transmission significantly, in addition it put forward a few drawbacks. Among them, conserving the energy is one of the most significant features in fifth generation. The role of small cells in energy-efficient management is studied and based on the functions they are classified to reduce the energy utilization and increase the energy efficiency. As the cellular technology is growing fast, energy utilization is a major concern. In this paper, we discuss novel architecture of different types of small cells in 5G mobile networks used in effective energy consumption. In the proposed work, among various forms of small cells, we discuss the role of femto cells, particularly in energy consumption.

Femto Access Points (FAP) and Device-to-Device (D2D) communications have recently been considered as potential candidates for 5G network densification and cell-edge performance. Mobility and handover management is a major issue in heterogeneous networks (HetNet) offering different access technologies. Recently, many Fuzzy and Multi-Attribute Decision Making (MADM) handover decision algorithms have been proposed to ensure Quality of Service (QoS), reduce the number of handovers and handover blocking probability of mobile users. However, network discovery is still an issue as it increases the total handover delay and drains the battery of the user equipment (UE). In addition, the UE may undergo high interference with other co-channel users after the handover is executed, thus limiting the overall network performance. Currently, the emerging Software Defined Networking (SDN) has been proposed in which one centralized controller can assist in the handover discovery, handover decision, and co-channel interference coordination. SDN-based handover algorithms ensure QoS, Quality of Experience (QoE), reduce delay and interference. In this paper, we will integrate the Fuzzy logic into the SDN to assist in FAPs and D2D discovery, and the decision of candidate networks based on the networks’ QoS parameters. Then, the UE will make the final handover decision by selecting the best network based on the predicted QoE using TOPSIS and AHP algorithms. Frequency reuse and appropriate power control are also applied in order to increase network capacity and reduce interference. Performance results show that the proposed SDN-based Fuzzy MADM handover scheme reduces unnecessary handovers, blocking probability and total handover delay. In addition, throughput is increased as the number of users increases.

Due to numerous base stations (BSs) being randomly deployed in ultra-dense networks (UDNs), the co-tier interference and cross-tier interference become more and more serious. We propose an interference management scheme based on joint clustering, subchannel allocation and successive cancellation among users for UDN taking all types of interference into consideration. To reduce the co-tier interference, we design a clustering algorithm based on interference graph to divide femto base stations (FBSs) and femto user equipments (FUEs) into FBS clusters and FUE groups respectively. Then a subchannel allocation algorithm is presented for FBS clusters to avoid the cross-tier interference. Moreover, a successive interference cancellation (SIC) detection algorithm is used to abate the interference among users in the same FUE group. Our analysis and simulations show that the proposed scheme outperforms other schemes in terms of system capacity and spectral efficiency in several scenarios. The results also verify that the proposed scheme can not only effectively mitigate the interference, but also have advantages in meeting the requirements of users and improving the network performance.

Cooperative communication is one of the emerging technologies that promise significantly higher reliability and spectral efficiency in wireless networks. It is a new form of diversity that allows users or nodes to share resources to create collaboration via distributed transmission and processing of messages. As candidate multiple access for future radio access, Non orthogonal multiple access (NOMA) over orthogonal multiple access (OMA) are adopted as downlink access scheme for future 5th generation mobile communication. In this paper, we compare user throughput when using orthogonal multiple access (OMA) and NOMA in macro femto network. We show through computer simulation the effect of imperfect interference cancellation on user throughput. We assist the performance of user selection when using fixed power allocation. Finally, we propose NOMA with COMP scenario whose performance improvement lead for user and cell throughput.

We address a resource allocation problem for joint caching and broadcast transmission in small cell networks with time-varying statistical properties. Each small base station (SBS) selects some files to store in its capacity-limited cache, given no prior information about the random and dynamic parameters such as file popularity, channel quality, and network traffic. Moreover, at consecutive rounds, a file is selected from the cache to broadcast. We define the utility of the SBS in terms of the number of successful file receptions per power consumption. The problem is formulated as to place the cache, and afterward select a file from the cache together with a transmission power for every broadcast round. The goal is to maximize the accumulated utility over the horizon. Therefore, we decompose the initial problem into two sub- problems: (i) cache placement, and (ii) joint file- and transmit power selection. The former problem boils down to a stochastic knapsack problem with stationary items' value, whereas the latter is cast as a multi-armed bandit problem with mortal arms. We develop a solution to each problem and evaluate the proposed solutions by theoretical and numerical analysis.

This research work explores small cell densification as a key technique for next generation wireless network (NGWN). Small cell densification comprises space (i.e, dense deployment of femtocells) and spectrum (i.e., utilization of frequency band at large). The usage of femtocells not only improves the spectral efficiency (SE) of the Heterogeneous two-tier networks against conventional approach, but also it alleviates outage probability and enhances the achievable capacity. We yield an analytical framework to establish the density of the femto base station (FBS) to a monotonically increasing or decreasing function of distance or radius, respectively. This ensures the enhanced performance in spectrum sharing Orthogonal Frequency Division Multiple Access (OFDMA) femtocell network models. We also illustrate the influence of active Femto users (i.e., users in femtocells, and they are usually low mobility and located closer to the cell center with less fading), cluster size (i.e., a group of adjacent macrocells which use all of the systems frequency assignments) via simulation results.

LTE-A (Long Term Evolution Advanced) as a transition from the GSM (global system for mobile) to LTE-A. Where LTE-A provides higher bandwidth than GSM and its compatibility to the modern mobile communication system. The objective of the paper is to examine the importance of the femto cell component of the existing LTE-A technology with the current femto cellular technology by adding a femto cell that gives us better signal strength in the indoor environment. It has become a common approach in the current cellular networks to improve capacity and coverage. As a result there is a continued demand for capacity in ultra dense areas, thus by increased coverage it has gained the importance in small cell research to minimize the impact of the living world. Femto cells for improving the performance of indoor users in LTE-A heterogeneous network provides an overall description of LTE-A technology during the exploit of femto cells to improve the indoor signal strength.

Dual-Connectivity architecture allows each user’s equipment (UE) to simultaneously communicate with two kinds of serving base stations (BSs) via two different radio-interfaces. Dual-Connectivity paradigm emerges as a promising solution to boost system capacity in fifth-generation heterogeneous network (HetNet), deploying multiple kinds of BSs, such as Femto BSs (FBSs), Pico BSs (PBSs) and Macro BSs (MBSs). In this paper, a comprehensive study of Dual-Connectivity in the downlink HetNet is analyzed via the framework of stochastic geometry, where the deployments of the BSs are modeled as mutually independent homogeneous Poisson point processes. In the conventional Dual-Connectivity, only the combination of MBS and SBS is available to access. In this paper, we consider that each UE can be simultaneously associated with any two types of BSs. The analysis is divided into two parts. We first derive the association probabilities of different combinations for Dual-Connectivity and then evaluate the average downlink throughput with the help of the association probabilities and the distance distributions to the serving BS. Moreover, we analyze the impact of the relative density of FBSs (or PBSs) on the association probabilities of different cases. Also, we compare the average downlink throughput of our considered Dual-Connectivity with those of conventional Dual-Connectivity and single association. Numerical results prove the validity of the theoretical analyses and demonstrate that our considered Dual-Connectivity owns superior performance on the throughput in HetNet, especially in the dense deployed SBS HetNet.

Future devices are likely to have the capability to harvest energy from radio-frequency (RF) signals. In this paper, we consider such energy harvesting (EH) devices operating in a two-tier orthogonal frequency-division multiple access-based heterogeneous network. Critically, we investigate how such EH devices can be supported alongside non-RF harvesting or legacy devices. Our aim is to minimize the downlink sum transmit power of both femto and macro base stations and ensure that legacy and EH devices receive a given data rate and amount of energy, respectively. Critically, we study sub-carrier and power allocation to both types of devices and investigate novel questions related to interference, which reduces network capacity but improves the amount of harvested energy by EH devices. To study these questions, we formulate a mixed-integer non-linear program (MINLP) and propose three linear approximations to the MINLP where devices are either assigned one or multiple sub-carriers. Numerical results show that EH devices will not affect network capacity if they can harvest sufficient energy from data transmissions to legacy devices. In addition, if multiple sub-carriers can be assigned to devices, our results show that the sum transmit power decreases by approximately 15% as compared with assigning a single sub-carrier to these devices.

Recently, femtocells are widely deployed to offload the traffic from the macrocell. Since conventional location management schemes of femto/macrocell networks do not consider mobility pattern of the mobile node (MN), unnecessary location updates can occur. Specifically, when an MN moves along the contour of the femtocell coverage, the MN frequently executes location update procedures, which causes significant location update cost. To address this problem, we propose a mobility-aware location management (MALM) scheme, where the MN conducts location update only at specific femtocells in which it is expected that the MN stays for a long time. To optimize MALM, a Markov decision process (MDP) problem is formulated and the optimal policy is determined. Evaluation results demonstrate that MALM with the optimal policy can reduce the number of location updates while providing sufficient offloading gain.

Femtocells have been discovered as the solution to coverage and capacity challenges experienced by mobile users in indoor environments, where data and voice services are mostly employed. During communication, path losses are mostly experienced because of base station distances and walls separating the communicating devices, which ultimately affects coverage and quality of service adversely. This study proposes an efficient channel allocation scheme (ECA) and compared with light channel (LCA), stern channel (SCA) and open channel allocation (OCA) schemes to ascertain the most optimal. These schemes assign frequencies such that interference is diminished significantly after femtocells, femto-users, and macro-users have been deployed randomly within the macro-cell coverage area. Results show higher capacities for macro-femto edge users (105 Mbps) compared to macro-femto center users (11 Mbps) with the proposed algorithm (ECA) emerging as the most optimal in both cases. Deployment of 30 macro-femto edge users records a failure probability of 0.11 for the proposed scheme, 0.17 for OCA, 0.19 for LCA, and 0.29 for SCA which is much lower compared to center users. It was observed that 50% of the edge users recorded downlink interference of 0.8 dBm for proposed, 1.3 dBm for OCA, 1.6 dBm for LCA, and 1.7 dBm for SCA which is much reduced compared to center users.

The hierarchical coexistence of femtocells and macrocells is a promising approach for heterogeneous networks (HetNets), dealing mainly with indoor coverage issues and providing high data rates in cellular networks. As for any HetNet, mobility management with handoff issues on top, should be studied prior to hindering the successful deployment of these networks. The current study introduces a new handoff algorithm in hierarchical macro/femtocell HetNets based on the combination of quality of service metrics for efficient network selection including: received signal strength, co-channel interference level, and outage probability of each of femtocell and macrocell networks. The proposed algorithm first collects the measured three mentioned metrics based on mobile station (MS) location, then applies a dynamic weighting system to three-metric sets according to the significance of each metric to obtain one utility for each of femtocell and macrocell networks. The obtained utility is then used as a measure for determining handoff necessity. In order to evaluate the performance of the proposed approach, the paper then introduces analytical model of cell assignment probability for an MS moving from the serving macrocell base station to the target femtocell base station in a two-tier cellular network. The analytical and simulation results indicate the efficiency of the proposed handoff algorithm in comparison with the existing algorithms in terms of cell assignment probability, throughput, number of handoffs, and ping-pong rate.

A cognitive femtocell is a new small cell based on a smart home base station to solve the spectrum-scarcity problem. Recently, dedicated resource allocation for cognitive femtocell to mitigate co-channel interference is extensively researched. However, the cognitive femtocell may suffer from the lack of frequency resource for its users due to high data traffic load of the macrocell. We propose a novel resource allocation and power control mechanism using spatial frequency reuse and spectrum sensing, which enables femto users in the cognitive femtocell to obtain more feasible resource. We analyze and evaluate the performance gain of the proposed scheme. Although data traffic load of the macrocell increases, the capacity of the cognitive femtocell can be maintained appropriately by the proposed resource allocation and power control scheme and it is shown that the performance is improved compared to that of the conventional scheme.

In the femto–macro coexisted heterogeneous network, the uplink transmission of femtocell user equipment (FUE) interferes with the macrocell base station (MBS) and deteriorates the capacity of macrocell user equipments (MUEs). To mitigate the cross-tier interference, a power control mechanism is proposed to adjust transmission power of FUE. The approach of this paper is to derive the minimum transmission power to achieve the required modulation and coding scheme and the maximum transmission power without violating the maximal tolerable interference of MBS, respectively. By selecting the minimum one among the two derived transmission power and the maximum allowable transmission power of an FUE as the transmission power of each FUE, the cross-tier interference from FUEs to MBS are alleviated. Simulation results show that when femtocells and macrocell are operated in the co-channel allocation approach, the average capacity of MUEs by using the proposed power control mechanism can be increased by 53.4% as compared to that without power control when 40 femtocells are deployed. The cost for the improvement is a reduction in the average FUE capacity by 7.3%. When the hybrid channel allocation approach is employed, the average capacity of MUEs can be further increased by 21.3%. Hence, the proposed power control mechanism is an efficient solution to mitigate the cross-tier interference and improve the average capacity of MUE with an acceptable reduction in the capacity of FUEs for the femto–macro coexisted heterogeneous network.

To address the explosively growing demand for mobile data services in the 5th generation (5G) mobile communication system, it is important to develop efficient content caching and distribution techniques, aiming at significantly reducing redundant data transmissions and improving content delivery efficiency. In heterogeneous cellular network (HetNet), which has been deemed as a promising architectural technique for 5G, caching some popular content items at femto base-stations (FBSs) and even at user equipment (UE) can be exploited to alleviate the burden of backhaul and to reduce the costly transmissions from the macro base-stations to UEs. In this paper, we develop the optimal cooperative content caching and delivery policy, for which FBSs and UEs are all engaged in local content caching. We formulate the cooperative content caching problem as an integer-linear programming problem, and use hierarchical primal-dual decomposition method to decouple the problem into two level optimization problems, which are solved by using the subgradient method. Furthermore, we design the optimal content delivery policy, which is formulated as an unbalanced assignment problem and solved by using Hungarian algorithm. Numerical results have shown that the proposed cooperative content caching and delivery policy can significantly improve content delivery performance in comparison with existing caching strategies.

LTE overlay cognitive femtocells system can provide a satisfied throughput for the macro and the femto users. On the other hand, the femto users can assign only the vacated subcarriers from the macro users. This assignment results in a reduced throughput for the femto users. Moreover, their throughput can have a zero value when the macro users operate on all subcarriers. In this paper, an underlay cognitive femtocells operation is proposed. The femtocells can share the subcarriers with the existing macrocells in such a way that their transmission cannot affect the macro users’ performance. The macro users’ positions can be determined, during their uplink transmission, using the received signal strength at the femto users. Then, the femtocells adapt their emitted power to guarantee a satisfied macro users’ performance. The performance of the proposed LTE underlay cognitive femtocells system is mathematically analyzed, simulated, and compared with the previous one which applies overlay cognitive femtocells. It can be observed that, the femto users’ throughput is existent and has a high value in comparison with the previous LTE overlay cognitive femtocells system. Furthermore, the proposed system has a higher macro and femto users’ throughput.

Femtocell deployment, which is a promising approach to the coverage and capacity improvement of indoor communications, suffers from cross-tier interference. Therefore to make the femtocell technology practical this issue needs to be addressed appropriately. One serious type of cross-tier interference occurs in downlink communication, in which a macrocell user is located far from its macro base station. In this setup, the communication of the adjacent femto access points with their users makes the macrocell user experience a low SINR. This paper considers this scenario and shows how cognitive-enabled femto access points can cope with cross-tier interference. More precisely, we compute the outage probability of macro users in a two-tier network when femto access points use the energy detection-based spectrum sensing technique to find the unoccupied frequency subband. To improve the outage probability of macro users, we also study the effectiveness of cooperation among neighbor femto access points. In all cases, the analytical expressions are validated by computer simulations which confirm the accuracy of the used approximations.

Heterogeneous networks (HetNets) composed of macrocells and small cells are expected to improve the transmission performance of users significantly. Designing efficient resource allocation schemes, specifically, bandwidth allocation and power allocation schemes for HetNets is of particular importance for it may affect user quality of service (QoS) and network performance severely. In this paper, we consider the resource allocation problem of a HetNet composed of a macrocell and a number of femtocells and propose a resource characteristic and user QoS oriented bandwidth and power allocation algorithm for the femto base stations (FBSs) which share spectrum with the macro base station. By taking into account the service requirements of the femto user equipments (FUEs) and the bandwidth resource characteristics of the network, various bandwidth resource allocation schemes are proposed. Particularly, in the case of slightly insufficient bandwidth resource, we propose a bankruptcy game based bandwidth resource allocation algorithm for the FBSs, and solve the bandwidth allocation problem by means of Shapley value method. To stress the tradeoff between data rate and power consumption, we examine the energy efficiency of the FBSs and formulate the power allocation problem as a multi-objective optimization problem with the objectives of maximizing the energy efficiency of all the FBSs. The optimal power allocation strategy can be obtained by solving the optimization problem via ideal point method and generic algorithm. Simulation results demonstrate the efficiency of the proposed algorithm.

Cognitive radios and femtocell networks are gaining much popularity due to the formers ability to carry out unlicensed transmission in licensed bands and the latter’s ability to increase the indoor capacity by bringing the transmitter and receiver closer to each other. The combination of the two provides us with a joint benefit of unlicensed transmission and increased system capacity. However, deployments of such cognitive radio based femtocell networks (CRFN) can pose some severe cross-tier interference towards the primary system. In this paper, we propose a novel spectrum sensing technique based on Uniform Linear array (ULA) combined with Genetic Algorithm to detect not only the presence of a Primary user but also estimate its parameters such as range, frequency, angle of arrival and amplitude. Furthermore, a joint beamforming and null steering technique is proposed to maximize the signal to interference plus noise ratio (SINR) towards the secondary user equipment (SUE) while minimizing the interference towards the primary Base Station (PBS). We are reutilizing the sensed uplink (UL) frequency of the Primary users for the downlink (DL) transmission; the cognitive femtocell base station (CFBS) calculates such weight vector that aims at sending the maximum signal power towards the femto user and null in the direction of PBS.

In this paper, a system of femtocells controlled by a single controller is investigated. In such a scenario, femtocell access points (FAPs) are assumed connected via wired links to a central controller within a certain vicinity (e.g., building, compound, hotel, and campus.). Thus, radio resource management (RRM) and green network operation of LTE femtocell networks are investigated in an integrated wired/wireless system. Consequently, it becomes possible to perform RRM in a centralized and controlled way in order to enhance the quality of service (QoS) performance for the users in the network. Furthermore, energy-efficient operation consisting of switching off redundant FAPs can be implemented. A utility maximization framework is presented, and an RRM algorithm that can be used to maximize various utility functions is proposed. Another algorithm is presented for the scenario of FAP on/off switching to achieve green operation. It consists of selecting the best FAP to switch off, then moving the femto user equipments (FUEs) to other active FAPs without compromising their quality of service (QoS). Simulation results show that the proposed algorithms lead to significant performance gains.

A vehicular network with Road Side Units (RSUs) provides an efficient way to connect vehicles even on the move. However, due to high deployment and maintenance cost of RSUs, it is necessary to use fewer RSUs, such that the total cost is minimized. It is suggested that cellular networks, such as Long-Term Evolution (LTE), are capable of fulfilling the demands posed in vehicular network scenarios. Availability of high bandwidth, large coverage area, and low latency are some of the advantages of cellular networks, which help in overcoming the challenges of high-speed vehicular communication. In this paper, we propose a maiden approach to analyze the performance of a vehicular network with cellular infrastructure as a backbone. For this, we use mobile Femto Access Points (FAPs) as relays in place of RSUs. We model the network using $M/M/m$ queue and compare the delay and throughput performance with traditional IEEE 802.11p vehicular networks. We also formulate an optimization problem and propose a subchannel power control algorithm to handle increased co-channel interference, which emerges due to high mobility of vehicles in the network. Our suggested approach shows improvement in terms of delay, throughput, and energy efficiency. The results are verified using extensive simulations.

As a result of the significant increase of overlapped coverage areas among base stations (BSs), interference coordination in heterogeneous cellular networks (HetCNets) becomes necessary, since interference would degrade network performance and even cause dropped calls. In addition, various types of BSs coexist in HetCNets, and BSs with low power (such as Pico BSs and Femto BSs) are deployed more arbitrarily than those in macrocell BSs (MBSs) so that the traditional anti-interference technologies are not enough in HetCNets. To reduce the interference between MBSs and low-power BSs within the coverage, a novel distributed resource allocation algorithm is proposed. First, an interference graph is established, by which the corresponding orthogonal resources can be assigned to different BSs, and the users can be classified into center and edge users, respectively. After that, users select appropriate resource blocks according to an improved proportional fair algorithm, and BSs distribute transmission power to different resource blocks to enhance network throughput further. Simulation results demonstrate the effectiveness of our proposed scheme in resource allocation and utilization.

Energy harvesting and sleeping strategy are the important methods to deal with the increasing grid power consumption problem. However, power supply solely from energy harvesting modules would be more likely to cause energy outage of base station (BS), and the load of sleeping BS would lead to coverage hole problem, which directly affect user’s quality of service (QoS). In this paper, to achieve the trade-off between grid power consumption and user’s QoS for each tier, optimal joint of ON/OFF mode of a BS and power source switching strategies are designed for two-tier femtocell networks, which are powered by the cooperation of the harvested energy and grid power. Then, exploiting stochastic geometry and random walk theory, BS availability and availability region are characterized with the proposed strategies. Moreover, the relationships among BS availability, battery capacity of grid power and cut-off energy level are exploited to verify the proposed strategies. By numerical simulations, we find that when energy storage capacity achieves a certain value, the effect of grid power battery capacity on availability almost vanishes especially in femto tier. So these redundant grid power can be saved when the stored energy in battery meets current traffic requirement.

In fifth-generation (5G) wireless networks, heterogeneous networks (HetNets) are used to improve capacity and users' densification. However, to rapidly deploy a large number of femto base stations (BSs) in a cost-efficient manner, they should be connected to the core network through residential broadband links. As such, different femto BSs may have different backhaul capacities, which should be taken into consideration when macro BSs offload traffic to femto BSs. Furthermore, users offloaded to femto BSs can be severely interfered by the macro BSs if macro and femto BSs transmit at the same time in the downlink. This interference can be avoided by proper transmission time scheduling. In view of the problem, this paper proposes a novel scheme to jointly perform traffic offloading and time fraction allocation (TOTFA) to ensure proportional fairness in throughput among the users. The proposed scheme, called TOTFA maximizes the weighted sum of the logarithm of user throughput, subject to constraints imposed by the backhaul capacity. Simulation results show that TOTFA can improve aggregated throughput up to 100% compared with a baseline scheme when the backhaul link capacity is 1.25 Mb/s. Over a range of different backhaul capacities, the average throughput improvement is 45%.

Employing femtocell technology noticeably improves both the indoor coverage and the overall cellular network's capacity. In the downlink scenario, when macrocell users (MUs) are far from the macro base station (MBS) and close to the femto access points (FAPs), the transmitted signals of FAPs to their users cause severe interference on MUs. One solution to overcome this issue is serving MUs by neighbouring FAPs. Generally femtocells are selfish and have no desire to allocate their resources to MUs. In this study, a framework to motivate femtocells to share their free resources with MUs is proposed. In this framework, the femtocells are assumed to belong to a specific unit. The unit encourages and manages the femtocells to share their resources, and in exchange receives a monetary utility from the MBS, and as a result improves the performance of the network. A computationally-efficient algorithm is proposed, which approximates the complete search algorithm, and their solutions coincide with each other in many cases. After FAPs assignment, the authors try to allocate the optimal power to MUs served by each femtocell to further improve their coverage probability through a bargaining game. The simulation results verify the performance of the proposed model and confirm the coverage improvement obtained in the network.

Nowadays, the popularity of smart phones creates huge capacity requirements for networks during mass events where thousands of people coexist in specific areas. At such events, large numbers of people use their smartphones to share pictures and download information. This behavior creates traffic profiles that differ from those typically observed in legacy -less populated- networks where lower uplink traffic volumes are generated. Thus, novel network planning and radio resource management mechanisms have to be considered for such dense network conditions, one of which is macrocell offloading. In this context, reducing the cell size has always been the best way to increase the network capacity of LTE. Femtocells are used to enable offloading data-traffic from macrocell network to increase the capacity. In this paper, to achieve efficient user offloading from macro to femtocells, we propose an offloading algorithm based on a perceived rate threshold in combination with uplink power control for hybrid femtocells also considering resource block partitioning. The proposed algorithm enhances the network capacity so that more mobile users can satisfy their minimum Quality of Service (QoS) requirements, thus the overall performance of dense cellular networks increases. The proposed offloading mechanism is assessed in terms of the achieved total throughput and outage probability figures. Simulation results demonstrate the potential increase of the number of supported users per macrocell in joint macro and hybrid femtocell deployments.

In this paper, an auction-based spectrum leasing for hybrid access in macro-femto network with location sensing is proposed to maximize the utilities of MBS and FAPs. The macrocell base station (MBS) owns all available spectrum resource and leases its spectrum to femtocell access points (FAPs) in order to get revenue. MBS offloads the macro UEs (MUEs) which are closer to the FAPs to improve the energy efficiency of the system. Auction mechanism is introduced to analyze the spectrum renting problem. We assume each FAP bids while the MBS acts as the auctioneer. The FAPs decide their bids independently of each other. Then MBS collects the bids of FAPs and determines the optimal allocation strategy. The MBS leases the spectrum to FAPs in order to get revenue, but it compensates FAPs for serving the additional MUEs. Simulation results validate the validity of this spectrum leasing scheme.

Femtocell technology has been gaining popularity as an inexpensive means of enhancing cellular coverage and capacity. However, under co-channel deployment&mdash, expected to be commonplace due to high spectrum costs&mdash, femtocells may incur harmful interference to existing macrocells, and vice versa. To alleviate this problem, This paper proposes a new architecture called HandOver-driven Femtocell Interference Management (HO-FIM) that offloads macrocells by handing macrocell users over to &ldquo, hybrid-access&rdquo, femtocells that allow the access of both subscribed and unsubscribed users. This use of handovers adds a new degree-of-freedom for solving the interference problem, thus overcoming the capacity limit of the existing approaches that exploit radio resource coordination only. A new challenge associated with this approach is how to minimize handovers while reaching a desired system condition due to the inevitable service interruptions that accompany handovers. This paper proposes to overcome this challenge by triggering handovers only when needed and, once triggered, to find an optimal sequence to reach a target system condition with minimal handovers. This paper designs a greedy per-user control algorithm that has a fine control granularity and thus enables convergence to an optimal solution. The in-depth evaluation of the paper shows that HO-FIM improves the service quality of both macro- and femtocell users, in an example simulation scenario, HO-FIM is shown to improve the signal-to-interference and noise ratios (SINRs) of macro- and femtocell users by up to 23.3 and 2.9 dB, respectively, on average, compared to the case of no handovers.