Neighboring Base Stations Research Articles

Downlink Signal-to-Interference Ratio and Spectral Efficiency of MIMO Cellular Networks Using Truncated Lognormal Approximation

This work focuses on analytical performance evaluation of a multiple-input multiple-output (MIMO) multicellular radio access network, while taking into account distance-dependent path loss, lognormal-distributed shadowing, and Rayleigh-distributed multipath fading. We propose a truncated moment-matching method for approximating the distribution of the sum of independent lognormal random variables in order to model the statistical behavior of the downlink signal-to-interference ratio (SIR) experienced by user equipment at a particular location in the presence of cochannel interference. The proposed method offers a good match with the simulated results in terms of the downlink SIR as well as mean and outage spectral efficiency for various MIMO schemes such as transmit and receive diversity, closed- and open-loop spatial diversity, and closed-loop multiuser MIMO. We compare the semianalytical results with that obtained from Monte Carlo simulations and quantify the relative error in terms of statistical metrics such as Kullback–Leibler divergence and Kolmogorov–Smirnov distance. In contrast to the existing works, the proposed model is useful for a wide range of shadowing standard deviation (4–12 dB) and activity of neighboring base stations (0.4–1). Moreover, the presented method is shown to achieve a comparable accuracy with the state of the art in spite of being less time consuming.

A Novel Intelligent Cluster-Head (ICH) to Mitigate the Handover Problem of Clustering in VANETs

The huge development in the number of Vehicle factories have resulted in many people having lost their life due to accident, which has made vehicular Ad-hoc networks (VANETs) hot topic to enable improved communication between vehicles aimed at reducing the loss of life. The main challenge in this area is vehicle mobility, which has direct effect on network stability. Thus, most previous studies that discussed clustering focused on cluster formation, cluster-head selection and the stability of cluster to reduce the impact of mobility in the network, with little attention given to the clusters when passing from base-station to neighbor base-station. Therefore, this study focused on handover problem that occurs after cluster formation and cluster-head election during cluster passing from base station to base station, known as overlapping area. As the cluster in an overlapping area receives two signals from different base stations, the signal arriving at the cluster becomes weak due to interference between two frequencies resulting in loss of cluster information in the overlapping area. In this study, proposed a novel method named Intelligent Cluster-Head (ICH), which is a controller on two clusters that are used to change uplink between clusters to solve the handover problem in the overlapping area. The proposed method was evaluated with VMaSC-1hop method. The proposed method achieved percentage of packet loss up to 0.8%, percentage of packet delivery ratio (PDR) 99%, percentage of number of disconnected links 0.12% and percentage of network efficiency 99% in the cells edge.

FINDER: A D2D based critical communications framework for disaster management in 5G

Public Safety Network communications technologies are at crossroads with next-generation networks to render better solutions and applications that can manage disaster efficiently. The fifth generation (5G) network is poised to have a guaranteed network connection, even in the case of partial dysfunction of cellular infrastructure due to disaster. In this paper, we have designed a framework named FINDER (Finding Isolated Nodes using D2D for Emergency Response) to locate-and-reconnect the isolated Mobile Nodes (MNs) in the disaster zone, so that the damage to assets and loss of life can be minimized. If the cellular link is non-existent over a disaster, the MNs under the impaired Base Station (BS) switch to the Device-to-Device (D2D) communications mode, and a critical D2D network is formed. The MNs in the disaster zone can reach an active network through a neighboring BS or a Wi-Fi access point. A multi-hop D2D communications based on hybrid Ant Colony Optimization is adopted to increase the energy efficiency of individual nodes and the overall network lifetime. Further, dynamic clustering curtails the numbers of active participating nodes, and data aggregation shrinks the number of packets in the network. Assistance from the Software-Defined Networking (SDN) controller at the BS benefits to have an intelligent and reliable connectivity to the MNs in the disaster zone. Our proposal FINDER is implemented using MATLAB, and the simulation results show that our framework extends the network lifetime with improved message delivery probability.

Directional Cell Search Delay Analysis for Cellular Networks With Static Users

Cell search is the process for a user to detect its neighboring base stations (BSs) and make a cell selection decision. Due to the importance of beamforming in 5G cellular networks including both the millimeter wave and sub-6 GHz networks, there is a need for a better understanding of the directional cell search delay performance. A cellular network with fixed BS and user locations is considered, so as to take into account the strong temporal correlations that exist for the SINR experienced by each BS and user in this context. For Poisson cellular networks with Rayleigh fading channels, a closed-form expression for the spatially averaged mean cell search delay of all users is derived. This mean cell search delay for a noise-limited network is proved to be infinite whenever the non-line-of-sight path loss exponent is larger than two. For interference-limited networks, a phase transition for the mean cell search delay is shown to exist in terms of the number of BS beams $M$ : the mean cell search delay is infinite when $M$ is smaller than a threshold and finite otherwise. Beam-sweeping is also demonstrated to be effective in decreasing the cell search delay, especially for cell edge users.

Downlink Resource Allocation Under Time-Varying Interference: Fairness and Throughput Optimality

We address the problem of downlink resource allocation in the presence of time-varying interference. We consider a scenario where users served by a base station face interference from a neighboring base station. We model the interference from the neighboring base station as an ON/OFF renewal process, that arises due to its idle and busy cycles. The users feedback their downlink signal to interference plus noise ratio (SINR) values to their base station, but these values are outdated. In this setting, we characterize how the resource allocation layer can optimally exploit the reported SINR values, which could be unreliable due to time-varying interference. In particular, we propose resource allocation policies in two well-known paradigms. First, we address the problem of $\alpha $ –fair scheduling, and propose a policy that ensures asymptotic convergence to the optimal $\alpha $ –fair throughput. Second, we propose a throughput optimal resource allocation policy, i.e., a policy that can stably support the largest possible set of traffic rates under the interference scenario considered. Estimating the outage probability from the outdated SINR values plays an important role in both scheduling paradigms, and we accomplish this using tool from renewal theory.

Interference management using direct sequence spread spectrum (DSSS) technique in LTE-Wi-Fi network

In this paper, an enhance DSSS technique was proposed which considers both serving and its neighbouring base stations in the network. New coefficients, chip rate coefficient ( a ) and radius fraction coefficient ( b ) were applied in DSSS technique in order to improve the SINR value. First, SINR MUE and SINR WUE for the standard DSSS were simulated. Then, by using the obtained analysis, the enhance DSSS technique was proposed. As the results, the SINR at MUE using a -coefficient gives better SINR than standard around 4%~5% improvement. On the other hand, the SINR at WUE using a -coefficient also gives better SINR than standard around 9%~10% improvement. Other than that, by applying both a -coefficient and b -coefficient into the proposed DSSS based on modified interference power, the improvement for SINR MUE increases to 11%~13%. For SINR WUE, the percentage spikes to 74%~84%.

Renewable Energy Assisted Traffic Aware Cellular Base Station Energy Cooperation

With global concern for climate change, and for cutting down the energy cost, especially in off grid areas, use of renewable energy has been gaining widespread attention in many areas including cellular communication. The base station (BS) has emerged as a strong candidate for the integration of renewable energy sources (RES), particularly solar and wind. The incorporation of renewable energy opens many possibilities for energy conservation through strategies such as energy cooperation between BSs during the off-peak hours, when the energy harvested from renewable energy sources may become surplus. In this paper, we present the case for cellular BSs enabled with renewable energy sources (RES) to have an arrangement in which the BS provide surplus energy to a neighboring BS, thus minimizing the use of conventional energy. A realistic objective is developed for northern region of Pakistan, which entails modeling of solar panels and wind-turbine according to the average solar irradiation and wind speed of the region. We also model the dynamic load of the BS, which depicts temporal fluctuations with traffic variations. Based on these models we initiate an energy cooperation scheme between the BS in which an energy cost minimization framework is mathematically modeled and solved through the interior point method algorithm. Results are obtained for different times of the year for different number of base stations showing respective energy cost savings.

Base Station Ordering for Emergency Call Localization in Ultra-Dense Cellular Networks

This paper proposes the base station ordering localization technique (BoLT) for emergency call localization in cellular networks. Exploiting the foreseen ultra-densification of the next-generation (5G and beyond) cellular networks, we utilize higher order Voronoi tessellations to provide ubiquitous localization services that are in compliance to the public safety standards in cellular networks. The proposed localization algorithm runs at the base stations (BSs) and requires minimal operation from agents (i.e., mobile users). Particularly, BoLT requires each agent to feedback a neighbor cell list that contains the order of neighboring BSs based on the received signal power in the pilots sent from these BSs. Moreover, this paper utilizes stochastic geometry to develop a tractable mathematical model to assess the performance of BoLT in a general network setting. The goal of this paper is to answer the following two fundamental questions: 1) how many BSs should be ordered and reported by the agent to achieve a desirable localization accuracy? and 2) what is the localization error probability given that the pilot signals are subject to shadowing? Assuming that the BSs are deployed according to a Poisson point process, we answer these two questions via characterizing the tradeoff between the area of location region and the localization error probability in terms of the number of BSs ordered by the agent. The results show that reporting the order of six neighboring BSs is sufficient to localize the agent within 10% of the cell area. Increasing the number of reported BSs to ten confines the location region to 1% of the cell area. This would translate to the range of a few meters to decimeters in the foreseen ultra-dense 5G networks.

Pilot Decontamination Using Coordinated Wiener Predictor in Massive-MIMO System

The massive multiple-input-multiple-output (MIMO) technology relies on many antennas at base stations to offer high throughput to meet 5G network requirements. However, each base station requires accurate channel state information during channel estimation. Pilot contamination is one of the significant challenges that limit higher order MIMO deployment because it causes channel estimation error. In this paper, a Wiener predictor (WP) using the temporal-based prediction technique was first proposed and then extended as the coordinated WP (CoWP). The WP method is based on prediction using information that has been stored and processed at the base station from a modified subframe, whereas the extended CoWP method requires neighboring base station coordination to assign collection and prediction with other base stations. Results showed a reduction in channel estimation error due to pilot contamination after the Wiener-based prediction and coordinated base station techniques were used. The proposed CoWP technique can increase the performance of channel estimation error by up to 25 and 30 dB relative to the performance of other research technique and conventional MMSE channel estimation. This paper indicates that the pilot contamination effect can be minimized by exploiting the temporal dimension, and this approach increases the number of MIMO order for future 5G base stations, which currently limited due to pilot contamination.

Parameter Setting of Load Forecasting Model for Adjacent Base Stations of Mobile Communication Based on Particle Swarm Optimization

In order to study the parameter setting of load forecasting model of mobile communication adjacent base station, the particle swarm optimization algorithm is used to make intelligent optimization of the parameter values in the support vector regression model, so as to obtain a prediction model with better parameters. Through the verification of base station load prediction scheme assisted by the nearest neighbor base station, we establish the support vector regression model only using the base station itself historical information that introducing adjacent base station historical information, and compare the performance of the two parts. It is proved that the base station assisted load prediction scheme with assisted adjacent base stations can achieve better performance.

MOCA: Multiobjective Cell Association for Device-to-Device Communications

It is widely accepted that device-to-device (D2D) communication is envisaged to become the key enabler of direct localized communication between mobile nodes in future wireless networks. However, little attention has been paid to an important aspect that can potentially affect both the performance of D2D and cellular transmissions, which is that of the D2D cell association. In this paper, a multiobjective cell association (MOCA) optimization framework for orchestrating a large number of D2D links in a multicell network is introduced. To this end, and without loss of generality, a differentiated Fractional Frequency Reuse (FFR) scheme is considered as the interference-limiting method, especially for cell-edge users, and we assume the provision of different resource pools for D2D and cellular users, which can vary according to their location. Under this assumption, we develop a set of integer linear programming optimization formulations for D2D links, part of which fall within the coverage area of different neighboring base stations. The main purpose is to achieve improved network traffic balancing via an efficient cell association scheme. Furthermore, we provide an iterative randomized resource allocation algorithm ( i-RRA ), which roots its logic on the differentiated FFR model in order to increase the overall network throughput. A wide set of numerical investigations demonstrate the benefits offered by MOCA, as well as the throughput gains that can be achieved through i-RRA , compared to existing solutions.

Evaluation of energy efficiency of fifth generation mobile systems

There has been active research worldwide to develop the next generation, i.e., fifth generation, wireless network. Next generation mobile communication networks are broadening their spectrum to higher frequency bands (above 6 GHz) to support a high data rate up to multigigabits per second. This work examines how to substantially improve energy efficiency for next fifth generation mobile communication systems. It is depicted how by limited exchange of information between neighboring base stations it is possible to maintain quality of service, over a range of traffic loads, while enabling inactive base stations to sleep. Performance of distributed energy efficient topology management schemes are compared against the system without topology management. Performance evaluation is examined using both analytical and simulation based models. Extensive numerical results show that the schemes deliver a significant energy reduction in energy consumption in the mobile network systems.

Aligned Reverse Frame Structure for Interference Mitigation in Dynamic TDD Systems

The dynamic time division duplex (TDD) system has been proposed as a way to meet today's asymmetrically and dynamically changing traffic demand. However, this approach causes cross-link interference, because neighboring base stations and user elements transmit in opposite directions. In this paper, we investigate and analyze the characteristics of cross-link interference in dynamic TDD systems. Based on this observation, we propose an aligned reverse frame structure to utilize and cancel the cross-link interference. Mathematical analysis and numerical results verify that the proposed scheme achieves performance enhancement in terms of capacity compared with conventional dynamic TDD systems.

QoS priority‐based coordinated scheduling and hybrid spectrum access for femtocells in dense cooperative 5G cellular networks

AbstractA third‐generation partnership project long‐term evolution system uses the concept of a 2‐tier heterogeneous network, where low‐power and short‐range femtocells are laid under macrocells to fulfill the quality of service (QoS) requirements of users and to boost overall network throughput. However, cochannel deployment gives rise to the problem of cross‐tier interference that significantly deteriorates the performance of the cellular network. The coordinated multipoint (CoMP) transmission scheme is proposed as a promising solution to alleviate cross‐tier interference by doing cooperation among the neighbor base stations. In this paper, we propose a QoS priority‐based coordinated scheduling and hybrid spectrum access (QoS‐CSaHSA) scheme for downlink CoMP transmission in 2‐tier networks. The proposed QoS‐CSaHSA scheme dynamically reduces the femtocells' power requirements by considering the neighbor cell interference, and it also balances the macrocell load by switching the femtocells to HA mode. Moreover, it can reduce unnecessary muting of the base stations because it only enables the coordinated scheduling CoMP when there is no other possibility to reduce the cross‐tier interference. System‐level simulation results prove the validity of the proposed QoS‐CSaHSA scheme in a heterogeneous network environment. Compared with the existing schemes that operate the femtocells in a closed‐subscriber group without considering users' QoS requirements, the proposed scheme almost doubles the cell‐edge user throughput and reduces the packet loss rate and call‐blocking probability.

An Efficient Energy Saving Scheme for Base Stations in 5G Networks with Separated Data and Control Planes Using Particle Swarm Optimization

Reducing energy consumption of mobile communication networks has gained significant attentions since it takes a major part of the total energy consumption of information and communication technology (ICT). In this paper, we consider 5G networks with heterogeneous macro cells and small cells, where data and control planes are separated. We consider two types of data traffic, i.e., low rate data traffic and high rate data traffic. In basic separation architecture, a macro cell base station (MBS) manages control signals, while a small cell base station (SBS) manages both low rate data traffic and high rate data traffic. In the considered modified separation architecture, an MBS manages control signals and low rate data traffic, while an SBS manages high rate data traffic. Then, an efficient energy saving scheme for base stations (BSs) is proposed, where the state of a BS is determined depending on the number of user equipments (UEs) that request high rate data traffic and the number of UEs that exist under the overlapping areas commonly covered by the considered BS and the neighbor BSs. We formulate an optimization problem for the proposed energy saving scheme and obtain the solution using particle swarm optimization (PSO). Numerical results show that the proposed energy saving scheme in the modified separated network architecture has better energy efficiency compared to the conventional energy saving schemes in both basic and modified separated network architectures. Also, the proposed energy saving scheme has lower aggregate delay.

REDISTRIBUTION OF BASE STATIONS LOAD IN MOBILE COMMUNICATION NETWORKS

The subject matter of the article is the processes of load distribution in mobile communication networks. The object of research is the handover. The goal is to develop a method for redistributing the load between neighboring areas for mobile nodes. The considered base stations are supposed to have the signal-to-noise ratios that are equal or close. The methods t hat are used: methods of system analysis, methods of digital signal processing. The following results are obtained. The method that allows mobile nodes, whose signal-to-noise ratios are equal or close, to switch to a less loaded base station. This method allows the base station to launch the handover process enabling more even distribution of the load from mobile nodes among neighboring base stations in wireless and mobile networks. In the suggested modification of the method, the function assessing the bandwidth of the uplink channel is added to the base stations, as well a threshold value for using its bandwidth. Thus, when the current value of bandwidth reaches the threshold, the base station starts sending out a message to all mobile nodes and verifies free neighboring areas for switching over mobile nodes. If there are adjacent areas with a lower load, the base station notifies all potential candidates about the necessity of their switching over. The handover process is launched when the available bandwidth of the base station decreases below a certain threshold. Therefore, it is possible to optimize the operation of the WiMAX network with respect to the criterion of the total bandwidth capacity of the base stations. Besides, the results of the comparative analysis of the handover process in networks based on the WiMAX technology that are obtained using the OpNet simulation environment are presented. Conclusions. The suggested approach can be used to improve the basic software of mobile communication networks. When moving a node from one area to another one in access servers, the node allocation tables are adjusted according to the developed method. Also, the suggested method enables improving and balancing the load of the base stations of mobile communication networks. The obtained results enables maintaining the required level of service quality in mobile communication networks.

Joint Power Optimization for Device-to-Device Communication in Cellular Networks With Interference Control

For device-to-device (D2D) communication under laid in a cellular network with uplink resource sharing, both cellular and D2D pairs may cause significant inter-cell interference (ICI) at a neighboring base station (BS). In this paper, under optimal BS receive beamforming, we jointly optimize the power of a cellular user (CU) and a D2D pair for their sum rate maximization, while satisfying minimum SINR requirements and worst-case ICI limit in multiple neighboring cells. We solve this non-convex joint optimization problem in two steps. First, the necessary and sufficient condition for the D2D admissibility under given constraints is obtained. Finally, we consider joint power control of the CU and D2D transmitters. We propose a power control algorithm to maximize the sum rate. Depending on the severity of ICI that D2D and CU may cause, we categorize the feasible solution region into five cases, each of which may further include several scenarios based on minimum SINR requirements. The proposed algorithm is optimal when ICI to a single neighboring cell is considered. For multiple neighboring cells, we provide an upper bound on the performance loss by the proposed algorithm and conditions for its optimality. We further extend our consideration to the scenario of multiple CUs and D2D pairs, and formulate the joint power control and CU-D2D matching problem. We show how our proposed solution for one CU and one D2D pair can be utilized to solve this general joint optimization problem. Simulation demonstrates the effectiveness of our power control algorithm and the nearly optimal performance of the proposed approach in the setting of multiple CUs and D2D pairs.

Analysis of Handover Failures in Heterogeneous Networks With Fading

The handover process is one of the most critical functions in a cellular network and is in charge of maintaining seamless connectivity of user equipments across multiple cells. The handover process is driven by signal measurements from the neighboring base stations (BSs), and it is adversely affected by the time and frequency selectivity of the radio propagation channel. In this paper, we introduce a new model for analyzing handover performance in heterogeneous networks (HetNets) as a function of vehicular user velocity, cell size, and mobility management parameters. In order to investigate the impact of shadowing and fading on handover performance, we extract relevant statistics obtained from a Third-Generation Partnership Project (3GPP)-compliant HetNet simulator, and subsequently, we integrate these statistics into our analytical model to analyze both handover failure and ping-pong probabilities under fluctuating channel conditions. Computer simulations validate the analytical findings, which show that fading can significantly degrade the handover performance in HetNets with vehicular users.

A Novel Approach for RSS-based Fingerprinting Location System in GSM

Received signal strength (RSS)-based fingerprinting location systems have attracted much attention in recent years. No additional hardware is required for it implementation to existing networks. However, by analyzing the realistic measurements from GSM, we find that not only the RSS but also the neighboring base stations heard at some reference point will change over time. But the relative order of neighboring base stations (NBS) sorted according to their RSS are more stable. In this paper, we present a confidence coefficient of base station based on a gridding approach to get a relative accurate NBS during the offline phase, and proposed a novel algorithm with Longest Common Subsequence Matching Degree (LCSMD) of base station vector (BSV), which uses the relative order of NBS sorted according to their RSS. To evaluate our proposed method, we collect the realistic data from GSM network. Results show that the method based on LCSMD improves the positioning accuracy compared to the original method.

Learning Based Content Caching and Sharing for Wireless Networks

Content caching at base stations (BSs) is a promising technique for future wireless networks by reducing network traffic and alleviating server bottleneck. However, in practice, the content popularity distribution may change with spatio-temporal variation but be unknown for BSs, which is an intractable obstacle for efficient caching strategy design. In this paper, considering unknown popularity distribution, we explore the content caching problem by jointly optimizing the content caching in cooperative BSs, content sharing among BSs, and cost of content retrieving. We tackle the problem from a multi-armed bandit learning perspective, where the learning of the popularity distribution is incorporated with the content caching and sharing process. Specifically, we first propose a centralized algorithm by employing a semidefinite relaxation approach, and we prove that this centralized algorithm learns efficient caching by deriving a sub-linear learning regret bound. To further reduce computational complexity, we propose a distributed algorithm based on alternating direction method of multipliers, where each BS only solves their own problems by exchanging local information with neighbor BSs. Extensive simulation results show the effectiveness of the proposed algorithms in terms of learning content popularity distributions of individual BSs, offloading traffic from the content server, and reducing cost of content retrieving.