Search

Balancing network traffic among base stations poses a primary challenge for mobile operators because of the escalating demand for enhanced data speeds in large-scale 5G radio applications. Within cellular networks, traffic flow prediction constitutes a pivotal issue in numerous applications, such as resource allocation, load balancing, and network slicing. In this paper, traffic prediction based load balancing framework with reinforcement learning is proposed to optimize neighbor cell relational parameters that can better balance traffic within a defined geographical cluster. Spatial–temporal-event cross attention graph convolution neural network (STECA-GCN) is put forward to predict the precise traffic flow. The model takes event dimension features into account, while also incorporating direct cross-fusion among diverse features. Concurrently, we have developed a strategy based on deep reinforcement learning to facilitate dynamic load balancing decisions. Simulation results show that our proposed load balancing framework can improve overall system performance. In particular, the combination of loading rate and energy efficiency can achieve a 12% improvement. The load balancing of the base station can better deal with social emergencies. [Display omitted] • Cross-fusion of different features and adding event domain features can enhance the precision of traffic forecasting. • Incorporating traffic prediction prior to the implementation of load balancing facilitates proactive resource planning. • Clustering to obtain load balancing cells and deep reinforcement learning for dynamic load balancing. • Simulation findings demonstrate that the methodologies yield enhancements in loading rates and energy efficiency. [ABSTRACT FROM AUTHOR]

Meta-heuristics are a set of intelligent algorithms and techniques that have been used to solve various complex problems in several domains in particular in cellular networks and telecommunications. The complex problem tackled by a meta-heuristic approach should be modeled mathematically as an optimization problem where the aim is to optimize a certain objective function. Then, an iterative process is launched to search for high quality solutions i.e. those optimizing the objective function. In this paper, we are interested in the fifth generation of cellular networks. We start with highlighting some main concepts of the 5G mobile networks. Then we discuss important problems in 5G and show how these problems can be solved by using meta-heuristics approaches. [ABSTRACT FROM AUTHOR]

Two-dimensional (2D) materials remain highly interesting for assembling three-dimensional (3D) structures, amongst others, in the form of macroscopic hydrogels. Herein, we present a novel approach for inducing chemical inter-sheet crosslinks via an ethylenediamine mediated reaction between Ti 3 C 2 T x and graphene oxide in order to obtain a reduced graphene oxide-MXene (rGO-MXene) hydrogel. The composite hydrogels are hydrophilic with a stiffness of ~20 kPa. They also possess a unique inter-connected porous architecture, which led to a hitherto unprecedented ability of human cells across three different types, epithelial adenocarcinoma, neuroblastoma and fibroblasts, to form inter-connected three-dimensional networks. The attachments of the cells to the rGO-MXene hydrogels were superior to those of the sole rGO-control gels. This phenomenon stems from the strong affinity of cellular protrusions (neurites, lamellipodia and filopodia) to grow and connect along architectural network paths within the rGO-MXene hydrogel, which could lead to advanced control over macroscopic formations of cellular networks for technologically relevant bioengineering applications, including tissue engineering and personalized diagnostic networks-on-chip. Conventional hydrogels are made of interconnected polymeric fibres. Unlike conventional case, we used hydrothermal and chemical approach to form interconnected porous hydrogels made of two-dimensional flakes from graphene oxide and metal carbide from a new family of MXenes (Ti 3 C 2 T x). This way, we formed three-dimensional porous hydrogels with unique porous architecture of well-suited chemical surfaces and stiffness. Cells from three different types cultured on these scaffolds formed extended three-dimensional networks – a feature of extended cellular proliferation and pre-requisite for formation of organoids. Considering the studied 2D materials typically constitute materials exhibiting enhanced supercapacitor performances, our study points towards better understanding of design of tissue engineering materials for the future bioengineering fields including personalized diagnostic networks-on-chip, such as artificial heart actuators. Image, graphical abstract [ABSTRACT FROM AUTHOR]

In mobile cellular design, one important quality-of-service metric is the blocking probability. Using computer simulation for studying blocking probability is quite time-consuming, whereas existing teletraffic-based methods such as the Information Exchange Surrogate Approximation (IESA) only give a rough estimate of blocking probability. Another common approach, direct blocking probability evaluation using neural networks (NN), performs poorly when extrapolating to network conditions outside of the training set. This paper addresses the shortcomings of existing teletraffic and NN-based approaches by combining both approaches, creating what we call IESA-NN. In IESA-NN, an NN is used to estimate a tuning parameter, which is in turn used to estimate the blocking probability via a modified IESA approach. In other words, the teletraffic approach IESA still forms the core of IESA-NN, with NN techniques used to improve the accuracy of the approach via the tuning parameter. Simulation results show that IESA-NN performs better than previous approaches based on NN or teletraffic theory alone. In particular, even when the NN cannot produce a good value for the tuning parameter, for example when extrapolating to network conditions not experienced in the training set, the final IESA-NN estimate is generally still accurate as the estimate is primarily determined by the underlying teletraffic theory, with the NN determining the tuning parameter playing a supplementary role. The combination of the IESA framework with NN in a secondary role makes IESA-NN quite robust. • We propose an improved method for efficient cellular network performance evaluation. • Combining teletraffic theory with neural networks boosts accuracy and robustness. • The neural network part improves accuracy over a pure teletraffic approach. • The teletraffic part aids robustness when extrapolating to new parameter ranges. [ABSTRACT FROM AUTHOR]

Cellular networks in a broad variety of materials influence many materials properties—a particularly important subject when it comes to microstructural coarsening of these networks. Hence, changes in the networks are of intense scientific and technological interest, where all topological changes occur in form of topological transitions. In two dimensions, there are three types of transitions, namely grain disappearance events, neighbour switching events, and edge disappearance events. Each event changes not only the morphology of a grain but also the local topology around this grain. The present work is the first investigation aimed at the question whether such topological transitions describe a topological random walk for individual grains or if they are a pure geometric necessity for structural space filling. [ABSTRACT FROM AUTHOR]

Abstract This paper addresses the Co-Channel Interference (CCI) reduction in Relay Assisted (R-A) cellular systems using Beamforming (BF) techniques. Analytical treatments are conducted. The network performance improvements through reducing the CCI are evaluated using three different configurations of applying BF. These configurations represent Relay Station (RS) do BF only, Base Station (BS) do BF only and both RS and BS do BF. Additionally, the considered BF techniques denote the horizontal, vertical, and Three Dimensional (3D) BF techniques. Therefore, each configuration consists of three different scenarios. Accordingly, nine different scenarios are studied. A comparison of these scenarios is introduced to enhance the network Quality of Service (QoS). Moreover, closed-form expressions for worst-cases Cell Edge User's (CEU's) Signal to Interference Ratio (SIR), Cell Center User's (CCU's) SIR and inner radius are implemented. Furthermore, various performance evaluation metrics are used to compare the different scenarios. The results reveal, that the performance of vertical BF is close to that of the 3D BF in low Path-loss (PL) exponent range. Therefore, applying vertical BF is preferable from the network cost and power consumption perspectives. Furthermore, it is observed, that the configuration of RS do BF is superior to other configurations when horizontal or vertical BF technique is employed. Additionally, the configuration of both RS and BS do BF outperforms the other configurations when 3D BF is applied. However, as unexpected it performs worse than them when the other BF techniques are applied. The work outcomes attain much higher CEU's SIR improvement. Therefore, the coverage probability is increased. Thus, more users can be served by the network. Accordingly, the total network cost is reduced. So, this treatment not only improves the network performance, but also it reduces the total network cost. [ABSTRACT FROM AUTHOR]

The optimisation of the user tracking process is one of the most challenging tasks in today’s advanced cellular networks. In this paper, we propose a new low-complexity adaptive cellular genetic algorithm to solve this problem. The proposed approach uses a torus-like structured population of candidate solutions and regulates interactions inside it by using a bi-dimensional neighbourhood. It also automatically adapts the algorithm’s parameters and regenerates the algorithm’s population using two algorithmically-light operators. In order to draw reliable conclusions and perform an encompassing assessment, extensive experiments have been conducted on 25 differently-sized realistic networks. The proposed approach has been compared against 26 state-of-the-art algorithms previously designed to solve the mobility management problem, and a thorough statistical analysis of results has been performed. The obtained results have shown that our proposal is more efficient and algorithmically less complex than most of the state-of-the-art solvers. [ABSTRACT FROM AUTHOR]

Ever since the advent of wireless communications, there has been a tremendous growth in data traffic and service demand. Both of the above quantities are expected to explosively dominate wireless communication networks, as we move on to the future 5G wireless communication systems. This paper involves the so-called hit probability related to data caching, a technique that mainly alleviates backbone network congestion and reduces latency, by storing frequently accessed data in mobile users' cache (mobility-aware caching) and leaves the least popular data for recovery from base stations. The hit probability is defined in the literature as the probability of specific file request by a user together with the successful delivery of the data packet to the user/network node that made the request. Considering three distributions, the uniform, the well-established Zipf-like distribution and the normal distribution, we allow a varying number of cached filles and observe the curves representing the hit probabilities and perform comparison. We provide interpretation of the related to optimality results i.e. greatest achievable hit probability. In a pico-cell of a cellular network of minimum radius of 50 m and a maximum radius of 200 m, we derive the transmission power level and verify that it complies to the typical transmission power of a pico-cell. A final remark involves the Compressed Sensing sparsity concept, where considering that the possibility that a file is cached with probability p, and not cached with probability 1 −  p , we examine the «sparsest» and «densest» scenario with respect to the number of cached files n opposed to the total N files in the aggregate users' cache, plotting the equivalent total probability. A final conclusion sets the issues of future work. [ABSTRACT FROM AUTHOR]

We study the problem of broadcasting scalable video coded (SVC) streams in cellular networks, where all user equipments (UEs) require the same video content and cooperate with each other. To take the advantage of channel diversity gains, the base station (BS) uses network coding to generate linear combinations of video packets for broadcasting in the downlink. Once receiving sufficient number of the combinations, a UE can relay packets to others via device-to-device (D2D) connections. The optimal downlink and D2D transmission arrangement problem is formulated as a mixed integer non-linear programming (MINLP) problem, which becomes difficult to solve when the number of UEs increases. Then we convert the MINLP problem to a quasi-convex optimization problem using a continuous step function, and a primal-dual decomposition approach is used to solve it in a distributed way. In addition, we consider the influence of the transmission energy consumption to the optimal solution. Simulation results show that the proposed approach achieves near-optimal performance. [ABSTRACT FROM AUTHOR]

With the advent of fifth-generation 5G networks, mobile communication data rates are steadily rising. The existing base stations (BSs) must reduce the loads with minimal cost and effort. With traffic demands constantly rising, available spectrum resources must be utilized effectively. One of the most exciting developments in 5G networks, particularly cellular networks, is the potential for devices to communicate directly with one another through a technology called device-to-device communication (D2D). With the transmission split between D2D users on one side and cellular users and the BS on the other, it will be effective in the rapidly expanding capacity and offload traffic from the BS. With the dynamic spectrum access in mind, this article proposes using cognitive radio direct-to-device (CRD2D) communication in 5G networks to make use of the unused spectrum. Throughput and latency are examined, for a carrier sense multiple access (CSMA) based medium access control (MAC) protocol that uses a common control channel (CCC) for device users to negotiate the data channel and to address contention among device users. Device users can take advantage of cognitive radio to access multiple data channels simultaneously in a shared interference zone. Since this property has not been utilized, in prior works, we use it to measure the possible delay and throughput. Cognitive radio capability applied to D2D communication and the allocation of a common control channel for device users significantly increases aggregated network throughput by more than 60% compared to individual D2D throughput without causing any harmful interference to cellular users. The wait time can also be scale back using this method. [ABSTRACT FROM AUTHOR]

While cellular interfaces are known to be the main power consumers in smartphones, our measurements reveal that surprisingly, due to cellular tail effect, a substantial ratio of energy drain comes from the low-frequency, low-data-rate background traffic. To reduce cellular tail energy use, existing solutions either require changing application behavior or assume the availability of low-level control of cellular interface (e.g., fast dormancy). We propose a collaborative cellular tail energy reduction approach for background traffic, which opportunistically discovers neighbors using low-power Bluetooth radio and shares their cellular bandwidth. Furthermore, we define a rigorous fairness notion by adapting the generalized processor sharing concept. Our sharing scheduling algorithm uses this notion to achieve substantial energy saving while ensuring fairness for participating phones and is also robust to whitewash attacks. Our evaluation demonstrates up to 90 % saving for background traffic energy consumption in urban settings. [ABSTRACT FROM AUTHOR]

Abstract: Full duplex wireless communication is one of the enabling technologies of the fifth generation (5G) mobile telecommunication networks. It boosts up the bandwidth by enabling simultaneous data transmission and reception on a single channel. In this paper, we design a suitable medium access control (MAC) protocol for 5G networks to realize the benefit of full duplex communication. We also develop an analytical model to evaluate the performance of our proposed MAC protocol. [ABSTRACT FROM AUTHOR]

Fractional frequency reuse (FFR) can not only coordinate inter-cell interference (ICI), but also improve communication quality of cell-edge users, whose key idea is to make a tradeoff between frequency utilization efficiency improvement and ICI suppression. In terms of the fact that conventional spectrum auction neglects the inter-cell and intra-cell interference and wireless spectrum has become scarce resources in cognitive radio networks, in this paper, FFR technology is introduced into the field of spectrum auction and a group reuse spectrum auction mechanism for FFR (GRSAF) is proposed in cognitive cellular systems to achieve higher spectrum allocation and usage efficiency. A Lagrangian relaxation (LR) algorithm is developed to solve the optimal sum utility maximization spectrum allocation problem. Simulation results show that the GRSAF mechanism can significantly improve the sum utility, spectrum reusability as well as satisfaction degree of buyers compared with other two existing auction mechanisms. [ABSTRACT FROM AUTHOR]

Shannon’s information communication theory tells much about the reliable message transmission and has a wide scope of application in communication technologies. The aim of this work is to present the implementation of the information communication theory in the cellular recognition or molecular interaction event models to quantify the message transmission capacities of molecular binding patterns and complexes. It has implications in molecular evolution such that the pattern formation by varied combinations of a possible number of binding events does not necessitate the presence of different types of receptor–ligand complexes. Signals through the same and different types of receptor–ligand complexes seem to have equal information amounts. This is suggesting the possible role of pattern formation in differentiation of distinct conditions, maybe even changing local concentration gradients or so, through sensing the patterns of relevance. Further, recognition of the patterns that are formed up of the same binding partners would be the step preceding the recognition of the patterns with discrete binding partners. All these considerations are valid for cellular networks, wherein the communicating cells are the sources of binding target molecules and are thus imposing diffusion dependent concentration gradients and variations in the probabilities of the binding events. [ABSTRACT FROM AUTHOR]

The success of personal mobile communication technologies has led an emerging expansion of the telecommunication infrastructure but also to an explosion to mobile broadband data traffic as more and more people completely rely on their mobile devices, either for work or entertainment. The continuously interaction of their mobile devices with the mobile network infrastructure creates digital traces that can be easily logged by the network operators. These digital traces can be further used, apart from billing and resource management, for large-scale population monitoring using mobile traffic analysis. They could be integrated into intelligent systems that could help at detecting exceptional events such as riots, protests or even at disaster preventions with minimal costs and improve people safety and security, or even save lives. In this paper we study the use of fully anonymized and highly aggregate cellular network data, like Call Detail Records (CDRs) to analyze the telecommunication traffic and connect people, locations and events. The results show that by analyzing the CDR data exceptional spatio-temporal patterns of mobile data can be correlated to real-world events. For example, high user network activity was mapped to religious festivals, such as Ramadan, Le Grand Magal de Touba and the Tivaouane Maouloud festival. During the Ramadan period it was noticed that the communication pattern doubled during the night with a slow start during the morning and along the day. Furthermore, a peak increase in the number of voice calls and voice calls duration in the area of Kafoutine was mapped to the Casamance Conflict in the area which resulted in four deaths. Thus, these observations could be further used to develop an intelligent system that detects exceptional events in real-time from CDRs data monitoring. Such system could be used in intelligent transportation management, urban planning, emergency situations, network resource allocation and performance optimization, etc. [ABSTRACT FROM AUTHOR]

The need for seamless mobility within the heterogeneous environment of cellular networks imposed the need for finding different vertical handover (VHO) mechanisms to select the best network. The selection process is based on different factors, such as: cost, battery status of Mobile Terminal (MT), the capacity of each network link, available bandwidth (ABW), received signal strength (RSS), etc. However, the major problem here is to find the most effective parameters for VHO and their priorities for these decision mechanisms. Besides, it would be useful to know the values of these parameters for data mining (DM). For this purpose, we collected real log data server of two mobile telecom companies in Lebanon, Touch and Alfa for Global System for Mobile Communications (GSM) and Universal Mobile Telecommunications System (UMTS) networks. After preprocessing and discretizing the data, frequent patterns (FP) were extracted to summarize the log data files. The summarized data was then analyzed by using descriptive and visualization techniques in order to find the most effective parameters for handover (HO) process. Three effective parameters were obtained: the Received Signal Strength (RxLev/RSCP), the Available Bandwidth (ABW) and the Received Signal Quality (RxQual/EcNo). Results showed that they cooperatively work together to accomplish the same task. This paper provide an effective solution to identify the most valuable factors for vertical handover mechanism in telecommunication area by using frequent pattern mining. [ABSTRACT FROM AUTHOR]

This paper examines how novel cellular system architectures and intelligent spectrum management techniques can be used to play a key role in accommodating the exponentially increasing demand for mobile data capacity in the near future. A significant challenge faced by the artificial intelligence methods applied to such flexible wireless communication systems is their dynamic nature, e.g. network topologies that change over time. This paper proposes an intelligent case-based Q -learning method for dynamic spectrum access (DSA) which improves and stabilises the performance of cognitive cellular systems with dynamic topologies. The proposed approach is the combination of classical distributed Q -learning and a novel implementation of case-based reasoning which aims to facilitate a number of learning processes running in parallel. Large scale simulations of a stadium small cell network show that the proposed case-based Q- learning approach achieves a consistent improvement in the system quality of service (QoS) under dynamic and asymmetric network topology and traffic load conditions. Simulations of a secondary spectrum sharing scenario show that the cognitive cellular system that employs the proposed case-based Q- learning DSA scheme is able to accommodate a 28-fold increase in the total primary and secondary system throughput, but with no need for additional spectrum and with no degradation in the primary user QoS. [ABSTRACT FROM AUTHOR]

The Flower Pollination Algorithm (FPA) is a recently proposed continuous metaheuristic that was claimed to give promising results. However, its potential in binary problems has been vaguely investigated. The use of mapping techniques to adapt metaheuristics to handle binary optimisation problems is a widely-used approach, but these techniques are still fuzzy and misunderstood, since no work thoroughly studied them for a given problem or algorithm. This paper conducts a consistent and systematic study to assess the efficiency of the FPA and the common mapping techniques. This is done through proposing four Binary variants of the FPA (BFPA) that have been got by applying the principal mapping techniques existing in the literature. As benchmark problem; an NP-hard binary one in advanced cellular networks, the Antenna Positioning Problem (APP), is used. In order to assess the scalability, efficiency and robustness of the proposed BFPAs, the experiments have been carried out on realistic, synthetic and random data with different dimensions, and several statistical tests have been carried. Two of the top-ranked algorithms designed to solve the APP; the Population-Based Incremental Learning (PBIL) and the Differential Evolution algorithm (DE), are taken as a comparison basis. The results showed that the normalisation and angle modulation are the best mapping techniques. The experiments also showed that the BFPAs have some shortcomings but, they could outperform the PBIL in 4 out of 13 instances and the DE in 6 out of 13 instances and no statistical difference was found in the remaining instances. Besides, the BFPAs outperformed or gave competitive technical results compared to the PBIL and DE in all problem instances. [ABSTRACT FROM AUTHOR]

This study investigated the possibility of integrating a renewable energy system with an existing energy source (electricity grid) to supply mobile base stations in the on-grid sites of Malaysia and minimise the annual Operational expenditure (OPEX). Based on the available renewable energy resources in Malaysia, three options for this goal were examined: (i) photovoltaic/electric grid, (ii) wind energy/electric grid, and (iii) photovoltaic/wind energy/electric grid. System simulations were performed with the software HOMER, using wind speed, solar irradiance, load demand, component costs and technical specifications as well as various minimum renewable fraction (MRF) values. Three key aspects were analysed: (i) energy yields, (ii) economics, and (iii) greenhouse gas (GHG) emissions. The findings herein demonstrate that the hybrid photovoltaic/wind energy/electric grid power system delivered the highest energy to the load of the renewable energy system (48.91%), which reduces both the operating costs and pollution rate. Whereas, cost of the project is large compared with the photovoltaic/electric grid power system. However, large benefits for mobile operators in terms of OPEX reduction can be achieved. The average annual OPEX savings of the hybrid wind energy system was the lowest at 30%, whereas that of the hybrid solar system was 35% and that of the hybrid photovoltaic/wind energy/electric grid was as high as 39%. [ABSTRACT FROM AUTHOR]

Nowadays, despite the ever increasing need of people for staying “connected” at any time and everywhere, in many areas of the world data connection is extremely expensive or even absent. The Global System for Mobile Communication (GSM) network virtually covers all the populated areas of the world and on average, the entire world population have a handheld device capable of accessing at least the GSM services. Therefore, it makes sense to consider the Short Message Service (SMS) as the most popular wireless data service for such devices. In this work, we exploit the SMS as mechanism for data transfer, especially in scenarios where there is no other network coverage than GSM, such as in rural areas and developing regions. In particular, we propose a framework, based on the SMS as transport facility, which enables secure end-to-end data communication in a ubiquitous and pervasive manner. Moreover, we investigated how, by using compression techniques, the overall processing and transmission efforts needed for secure data communication can be effectively reduced, with the obvious consequences also in terms of energy consumption on the involved devices. Finally, we successfully tested the effectiveness of the proposed framework within the context of a proof of concept implementation. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a novel approach for power allocation in cellular networks. In our model, we use sigmoidal-like utility functions to represent different users’ modulation schemes. Each utility function is a representation of the probability of successfully transmitted packets per unit of power consumed by a user, when using a certain modulation scheme. We consider power allocation with utility proportional fairness policy, where the fairness among users is in utility percentage i.e. percentage of successfully transmitted packets of the corresponding modulation scheme. We formulate our power allocation optimization problem as a product of utilities of all users and prove that it is convex and therefore the optimal solution is tractable. We present a distributed algorithm to allocate base station powers optimally with priority given to users running lower modulation schemes while ensuring non-zero power allocation to users running higher modulation schemes. Our algorithm prevents fluctuation in the power allocation process and is capable of traffic and modulation dependent pricing policy. This can be used to flatten traffic and decrease the service price for users. We also compare our results with a benchmark algorithm and show that our algorithm performs better in allocating powers fairly to all users without dropping any user in order to maximize performance. [ABSTRACT FROM AUTHOR]

This paper investigates the resource allocation problem in non-orthogonal multiple-access (NOMA) cellular networks underlaid with OMA-based device-to-device (D2D) communication. This network architecture enjoys the intrinsic features of NOMA and D2D communications; namely, spectral efficiency, massive connectivity, and low-latency. Despite these indispensable features, the combination of NOMA and D2D communications exacerbates the resource allocation problem in cellular networks due to the tight coupling among their constraints and conflict over access to shared resources. The aim of our work is to maximize the downlink network sum-rate, while meeting the minimum rate requirements of the cellular tier and underlay D2D communication, and incorporating interference management as well as other practical constraints. To this end, many-to-many matching and difference-of-convex programming are employed to develop a holistic sub-channels and power allocation algorithmic solution. In addition to analyzing the properties of the proposed solution, its performance is benchmarked against an existing solution and the traditional OMA-based algorithm. The proposed solution demonstrates superiority in terms of network sum-rate, users' connectivity, minimum rate satisfaction, fairness, and interference management, while maintaining acceptable computational complexity. [ABSTRACT FROM AUTHOR]

Abstract: The secondary use of vacant television channels (TV white spaces) and the reallocation of the digital dividend to provide wireless broadband services are in the final stages of implementation in some countries. Originally seen as a once in a generation opportunity to better allocate UHF spectrum, further digital dividends are now underway as regulators and industry strive to meet exponential increases in demand for mobile data services. Concurrent developments suggest that TV white spaces may be rapidly exploited by global networks with billions of supported devices. The potential for sub-optimal outcomes is identified if the prospect of further digital dividends is not taken into account as technical and regulatory arrangements are put in place to allow productive use of TV white spaces. The importance of considering the potential interaction between further digital dividends and the use of TV white spaces is discussed and technical and regulatory approaches to support optimal outcomes are identified. [Copyright &y& Elsevier]

Abstract: This research is to study the air-interface signal problems over GSM cellular network. Using TEMS investigation GSM, several air-interface signal problems are detected at Sukhumvit-Naklue Road, Pattaya-Beach Road No.1, Pattaya Alleyways No.1-4, and Central Pattaya Avenue. In this paper, technical causes are examined and corrective approaches are also recommended. In particular, those problems can be clearly eliminated using corrective approaches. [Copyright &y& Elsevier]

Abstract: In this paper, we address the issue of cellular OFDMA network dimensioning. Network design consists of evaluating cell coverage and capacity and may involve many parameters related to environment, system configuration, and quality of service (QoS) requirements. In order to quickly study the impact of each of these parameters, analytical formulas are needed. The key function for network dimensioning is the Signal to Interference Ratio (SIR) distribution. We thus analyze in an original way the traditional issue of deriving outage probabilities in OFDMA cellular networks. Our study takes into account the joint effect of path-loss, shadowing, and fast fading effects. Starting from the Mean Instantaneous Capacity (MIC), we derive the effective SIR distribution as a function of the number of sub-carriers per sub-channel. Our formula, based on a fluid model approach, is easily computable and can be obtained for a mobile station (MS) located at any distance from its serving base station (BS). We validate our approach by comparing all results to Monte Carlo simulations performed in a hexagonal network, and we show how our analytical study can be used to analyze outage capacity, coverage holes, and network densification. The proposed framework is a powerful tool to study performances of cellular OFDMA networks (e.g. WiMAX, LTE). [Copyright &y& Elsevier]

The cellular networks that regulate humoral immune responses have been a focus of research over the past three decades. Studies have shown that inhibition of immune responses can be attributed to both suppressor T cells and B cells. More recently, T follicular helper (Tfh) cells have been identified as a target of immune regulation. Tfh cells are a subset of highly activated T helper cells specialized for providing cognate help to B cells during germinal center reactions. In this review, we describe emerging evidence for cellular networks that alter Tfh cell phenotype and function and regulate antibody production during the germinal center reaction. We discuss how these new findings influence our understanding of Tfh cells. [ABSTRACT FROM AUTHOR]

Abstract: Given a graph and a demand function , a proper -[]coloring is a mapping such that for every vertex and for any two adjacent vertices and . The least integer for which a proper -[]coloring exists, , is called multichromatic number of . Finding multichromatic number of induced subgraphs of the triangular lattice (called hexagonal graphs) has applications in cellular networks. Weighted clique number of a graph , , is the maximum weight of a clique in , where the weight of a clique is the total demand of its vertices. McDiarmid and Reed (2000)  conjectured that for triangle-free hexagonal graphs, where is some absolute constant. In this article, we provide an algorithm to find a 7-[3]coloring of triangle-free hexagonal graphs (that is, when for all ), which implies that . Our result constitutes a shorter alternative to the inductive proof of Havet (2001)  and improves the short proof of Sudeep and Vishwanathan (2005) , who proved the existence of a 14-[6]coloring. (It has to be noted, however, that our proof makes use of the 4-color theorem.) All steps of our algorithm take time linear in , except for the 4-coloring of an auxiliary planar graph. The new techniques may shed some light on the conjecture of McDiarmid and Reed (2000) . [Copyright &y& Elsevier]

Abstract: A two-tier model is used in cellular networks to improve the Quality of Service (QoS), namely to reduce the blocking probability of new calls and the forced termination probability of ongoing calls. One tier, the microcells, is used for slow or stationary users, and the other, the macrocell, is used for high speed users. In Code-Division Multiple-Access (CDMA) cellular systems, soft handoffs are supported, which provides ways for further QoS improvement. In this paper, we introduce such a way; namely, a channel borrowing scheme used in conjunction with a First-In-First-Out (FIFO) queue in the macrocell tier. A multidimensional Markov chain to model the resulting system is established, and an iterative technique to find the steady-state probability distribution is utilized. This distribution is then used to find the performance measures of interest: new call blocking probability, and forced termination probability. [Copyright &y& Elsevier]

Abstract: Collision avoidance support systems (CASS) are nowadays one of the main fields of interest in the area of road transportation. Among the different approaches, those systems based on vehicle cooperation to avoid collisions present the most promising perspectives. Works available in the current literature have in common that the performance of such solutions strongly relies on the operation of two on-board subsystems: navigation and communications. However, the performance of these two subsystems is usually underestimated when the whole solution is evaluated. Collision avoidance support applications can be considered among the most critical vehicular services, and this is the reason why this paper focuses on the performance issues of these two subsystems. Main issues regarding navigation and communication performance are discussed along the paper, and a study of the literature in the field is completed with the evaluation of different system prototypes. Communication and navigation tests in real environments yield further conclusions discussed in the paper. [Copyright &y& Elsevier]

Abstract: We consider the problem of synthesizing decentralized transmit power control for finite-gain stable cellular code division multiple access (CDMA) networks subject to saturation constraints on the mobile transmit powers. We show that the passivity theorem and an extension of the Zames–Falb multipliers can be used to synthesize the required distributed decentralized nonlinear dynamic controllers, to be implemented at the base station and at the mobile users, including a multi-input–multi-output (MIMO) anti-windup controller that can be implemented on the mobile hand-sets. [Copyright &y& Elsevier]

Abstract: In the frequency assignment problem we are given a graph representing a wireless network and a sequence of requests, where each request is associated with a vertex. Each request has two more attributes: its arrival and departure times, and it is considered active from the time of arrival to the time of departure. We want to assign frequencies to all requests so that at each time step any two active requests associated with the same or adjacent vertices use different frequencies. The objective is to minimize the number of frequencies used. We focus exclusively on the special case of the problem when the underlying graph is a linear network (path). For this case, we consider both the offline and online versions of the problem, and we present three results. First, in the incremental online case, where the requests arrive over time, but never depart, we give an algorithm with an optimal (asymptotic) competitive ratio . Second, in the general online case, where the requests arrive and depart over time, we improve the current lower bound on the (asymptotic) competitive ratio to . Third, we prove that the offline version of this problem is -complete. [Copyright &y& Elsevier]

Abstract: Under acute perturbations from the outside, cells can trigger self-defensive mechanisms to fight against genome stress. To investigate the cellular response to continuous ion radiation (IR), a dynamic model for p53 stress response networks at the cellular level is proposed. The model can successfully be used to simulate the dynamic processes of double-strand breaks (DSBs) generation and their repair, switch-like ataxia telangiectasia mutated (ATM) activation, oscillations occurring in the p53-MDM2 feedback loop, as well as toxins elimination triggered by p53 stress response networks. Especially, the model can predict the plausible outcomes of cellular response under different IR dose regimes. [Copyright &y& Elsevier]

Cellular networks are one of today's most popular means of communication. This fact has made the mobile phone industry subject to a huge scientific and economic competition, where the quality of service is key. Such a quality is measured on the basis of reliability, speed and accuracy when delivering a service to a user no matter his location or behaviour are. This fact has placed the users' tracking process among the most difficult and determining issues in cellular network design. In this paper, we present an adaptive bi-phased evolutionary algorithm based on the takeover time to solve this problem. The proposal is thoroughly assessed by tackling twenty-five real-world instances of different sizes. Twenty-eight of the state-of-the-art techniques devised to address the users' mobility problem have been taken as the comparison basis, and several statistical tests have been also conducted. Experiments have demonstrated that our solver outperforms most of the top-ranked algorithms. • Adaptive metaheuristics to solve the mobile user tracking problem in cellular networks. • Adaptation is dynamic and based on the future behaviour of the algorithm. • Uses a mathematical model to forecast the future behaviour of the algorithm. • Tests over 25 realistic networks and comparison against 28 top-ranked algorithms. • Experiments showed that the proposed approach is more efficient. [ABSTRACT FROM AUTHOR]

Abstract: Computational virtuality is introduced as a key distinguishing feature of genuinely computational systems. Evidence is provided that the basic cellular machinery possesses virtuality. Accordingly, one can step beyond the commonplace metaphor of computation as applied to molecular biology, and come to view the cell as a genuine computing system. The human nervous system is analyzed in the same light, setting an agenda for research on virtuality in recurrent neural networks, whose outcomes in the way of theoretical results and simulation of biological neural systems may heuristically guide neuroscientists in the search for virtual computing in the brain. [Copyright &y& Elsevier]

Abstract: This paper presents an analytical model for cellular networks supporting voice, video and data traffic. Self-similar and bursty nature of the incoming traffic causes correlation in inter-arrival times of the incoming traffic. Therefore, arrival of calls is modeled with Markovian arrival process as it allows for the correlation. Call holding times, cell residence times and retrial times are modeled as phase-type distributions. We consider that the cells in a cellular network are statistically homogeneous, so it is enough to investigate a single cell for the performance analysis of the entire networks. With appropriate assumptions, the stochastic process that describes the state of a cell is a Quasi-birth–death (QBD) process. We derive explicit expressions for the infinitesimal generator matrix of this QBD process. Also, expressions for performance measures are obtained. Further, complexity involved in computing the steady-state probabilities is discussed. Finally, queueing examples are provided that can be obtained as particular cases of the proposed analytical model. [Copyright &y& Elsevier]

Abstract: Cellular learning automata is a combination of cellular automata and learning automata. The synchronous version of cellular learning automata in which all learning automata in different cells are activated synchronously, has found many applications. In some applications a type of cellular learning automata in which learning automata in different cells are activated asynchronously (asynchronous cellular learning automata) is needed. In this paper, we introduce asynchronous cellular learning automata and study its steady state behavior. Then an application of this new model to cellular networks has been presented. [Copyright &y& Elsevier]

Abstract: Substantial works have recently been reported on the mobility management in single-hop wireless networks (e.g. cellular networks and WLAN hotspots), while there has been an increased interest in multi-hop communications. This has made mobility management in heterogeneous multi-hop wireless networks (HMWNs) really interesting so that both single-hop and multi-hop communication paradigms can be integrated. One of the main research challenges for 4G wireless systems is the identification of a mobility management technique that could integrate different wireless technologies such as WLANs, WMANs and WWANs, operating in infrastructure (single-hop) and infrastructureless (ad hoc or multi-hop) modes. In this article we envision a futuristic HMWN where heterogeneous networks, operating in single-hop and multi-hop modes are integrated to provide increased capacity and enhanced coverage for the users. We summarize various existing mobility management solutions and discuss why these schemes are not adequate for HMWNs, as well as highlighting our view of mobility management issues in HMWNs. [Copyright &y& Elsevier]

Abstract: Handoff and cabling cost management plays a key role in the design of cellular telecommunications networks. The efficient assignment of cells to switches in this type of networks is an NP-complete problem which cannot be solved efficiently unless P=NP. This paper presents a hybrid Hopfield network-genetic algorithm approach to the cell-to-switches assignment problem, in which a Hopfield network manages the problem''s constraints, and a genetic algorithm searches for high quality solutions with the minimum possible cost in terms of handoff and cable displayed. We show, by means of computational experiments, the good performance of our approach to this problem. [Copyright &y& Elsevier]

Abstract: In this paper, we extend known relationships between Cayley digraphs and their subgraphs and coset graphs with respect to subgroups to obtain a number of general results on homomorphism between them. Intuitively, our results correspond to synthesizing alternative, more economical, interconnection networks by reducing the number of dimensions and/or link density of existing networks via mapping and pruning. We discuss applications of these results to well-known and useful interconnection networks such as hexagonal and honeycomb meshes, including the derivation of provably correct shortest-path routing algorithms for such networks. [Copyright &y& Elsevier]

Abstract: Song et al. [Self-similarity of complex networks, Nature 433 (2005) 392–395] have recently used a version of the box-counting method, called the node-covering method, to quantify the self-similar properties of 43 cellular networks: the minimal number of boxes of size needed to cover all the nodes of a cellular network was found to scale as the power-law with a fractal dimension . We implement an alternative box-counting method in terms of the minimum number of edge-covering boxes which is well-suited to cellular networks, where the search over different covering sets is performed with the simulated annealing algorithm. The method also takes into account a possible discrete scale symmetry to optimize the sampling rate and minimize possible biases in the estimation of the fractal dimension. With this methodology, we find that scales with respect to as a power-law with for the 43 cellular networks previously analyzed by Song et al. [Self-similarity of complex networks, Nature 433 (2005) 392–395]. Bootstrap tests suggest that the analyzed cellular networks may have a significant log-periodicity qualifying a discrete hierarchy with a scaling ratio close to 2. [Copyright &y& Elsevier]

Abstract: Cellular telephony systems, where locations of mobile users are unknown at some times, are becoming more common. In such systems, mobile users are roaming in a zone and a user reports its location only if it leaves the zone entirely. The conference call search (CCS) problem deals with tracking a set of mobile users in order to establish a call. To find a single roaming user, the system may need to search each cell where the user may be located. The goal is to identify the location of all users, within bounded time, satisfying some additional constraints on the search scheme. We consider cellular systems with cells and mobile users (cellular phones). The uncertain location of users is given by probability distribution vectors. Whenever the system needs to find the users, it conducts a search operation lasting at most rounds. A request for a single search step specifies a user and a cell. In this search step, the cell is asked whether the given user is located there. In each round the system may perform an arbitrary number of such requests. An integer number bounds the number of distinct requests per cell in every round. The bound results from quality of service considerations, whereas the bound results from the wireless bandwidth allocated for signaling being scarce. Every search step consumes expensive wireless links, which motivates search techniques minimizing the expected number of requests thus reducing the total search costs. We distinguish between oblivious, semi-adaptive and adaptive search protocols. An oblivious search protocol decides on all requests in advance, and stops only when all users are found. A semi-adaptive search protocol decides on all the requests in advance, but it stops searching for a user once it is found. An adaptive search protocol stops searching for a user once it has been found (and its search strategy may depend on the subsets of users that were found in each previous round). We establish the difference between those three search models. We show that for oblivious “single query per cell” systems (), and a tight environment (), it is NP-hard to compute an optimal solution (the case was proven to be NP-hard already by Bar-Noy and Naor) and we develop a PTAS for these cases (for fixed values of ). However, we show that semi-adaptive systems allow polynomial time algorithms. This last result also shows that the case and is polynomially solvable also for adaptive search systems, answering an open question of Bar-Noy and Naor. [Copyright &y& Elsevier]

Abstract: Capacity improvment in cellular networks is highly dependent on the effectiveness of power control. A power control procedure is needed to compensate for the fluctuation of a mobile''s transmitting power received at a base station and to increase the capacity of the mobile communication system via decreasing intra- and inter-cellular interference. Here we consider fuzzy set theory based delayed adaptive step-size closed loop power control scheme(s). In this scheme transmitters adjust their power step sizes according to the received multiphased power control signals (delayed commands) from base stations. Code division multiple access (CDMA) system standards (cdmaOne, CDMA2000 and ETSI UMTS/UTRAN) limit the number of bits to two for the length of the control command in time slots. Hence, the number of commands is limited to four per time slot (in practise to two: up and down fixed amount, the rest are zero and unused values) when a sign and magnitude binary word format is used. In the developed algorithm, the number of commands is enlarged to 16 per two sequential time slots (four bits) without an increase in the standardized control bit rate by transmitting control commands in two sequential phases (time slots). First two bits of the command are transmitted in the current time slot and a receiver stores them and waits for the next time slot, which includes the last two bits of the control signal. The receiver interprets control command after receiving all 4bits. Therefore, the control frequency is decreased (delayed control) to half of the original but respectively the dynamic scale is increased to 4 times larger (in practise 7 times: 7 values up and 7 down, 1 value for zero and 1 unused) for the sign and magnitude binary coding. A single transmitter''s control results with the developed controller in a frequency selective fading channel in a CDMA network with interfering nodes and Gaussian noise are compared to the predefined step size power control scheme, which is a de facto standard the power control in cellular networks. [Copyright &y& Elsevier]

Extracting a comprehensive overview from the huge amount of information arising from whole-genome analyses is a significant challenge. This review critically surveys the state of the art methods that are used to connect information from functional genomic studies to biological function. Cluster analysis methods for inferring the correlation between genes are discussed, as are the methods for integrating gene expression information with existing information on biological pathways and the methods that combine cluster analysis with biological information to reconstruct novel biological networks. [Copyright &y& Elsevier]

Abstract: Cells interact/communicate among themselves to form structures that perform specialised functions. Here, we review the different types of multicellular organisation observed in living systems whose constituent cells exhibit collective behaviour that may or may not be identical to the single cell dynamics. We present a simple one-dimensional lattice model of a ring of cells, as observed in real tissues, where each cell incorporates a model biochemical reaction having realistic regulatory processes. We study the dynamics exhibited by this coupled-cell system when the constituent pathway in the cells is at different dynamic regimes, or cells have heterogeneous dynamics. Our results show that the synchronised dynamical behaviour of the coupled-cell system can be both similar or different than its constituent cells depending on their intrinsic dynamics. The collective behaviour is robust even when the constituent single cell dynamics is unpredictable under noise. [Copyright &y& Elsevier]

Abstract: Systems biology approaches for modeling cellular signaling networks affected by chemical exposures should soon produce integrated methodologies capable of predicting dose–response relationships for developmental toxicants and for other toxic responses. This paper outlines an emerging strategy for systems biology approaches in dose–response modeling. Genome-wide functional screens, bioinformatic tools, and network mapping technologies together can provide directed graph representations of the cellular signaling networks. The graphical representations can be converted into mathematical models that permit predicting the shapes of dose–response curves for altered cell signaling by test compounds during development. Systems biology approaches require interdisciplinary teams with expertise in reproduction, cell biology, signal transduction, mathematical/biomedical modeling, and risk assessment. In addition to outlining a systems approach for dose–response research, this paper discusses initial stages of application of this strategy to examine inhibition of steroidogenesis in testes by phthalate esters. [Copyright &y& Elsevier]

We consider the problem of channel assignment in cellular networks with arbitrary reuse distance. We show upper and lower bounds for the competitive ratio of a previously proposed and widely studied version of dynamic channel assignment, which we refer to as the greedy algorithm. We study two versions of this algorithm: one that performs reassignment of channels, and one that never reassigns channels to calls. For reuse distance 2, we show tight bounds on the competitive ratio of both versions of the algorithm. For reuse distance 3, we show non-trivial lower bounds for both versions of the algorithm. [Copyright &y& Elsevier]

The most general form of the Aboav–Weaire empirical topological law of random cellular networks is derived from conditions on local averages in two dimensions. We assume the average number of edges in a local cluster depends on the number of actual edges and its moments together with the probability distribution function. Based on this constitutive assumption we show that the Aboav–Weaire law depends only on the first and second moments of the distribution function. We show that the Aboav–Weaire law is a direct consequence of the existence of the well-known microscopic topological transformations. We study the effect of the constitutive equation’s coefficients on the Aboav–Weaire law. The properties near to the equilibrium are also investigated to explain the role of the actual parameters of the network. [Copyright &y& Elsevier]

• Analysis of the current and potential convergence between power grids and mobile communications in multiple, different power grid evolution scenarios created by using a formal scenario planning process. • Power grids and communications can be expected to become more tightly integrated. • Mobile communications and cloud computing are key enablers in the most transformative consumer-centric and grid-management-centric power grid scenarios. • Beyond-5G features are required both for the evolutionary and the most transformative scenarios. • Both the power grid and the communications industries deal with networked infrastructures. Thus, in the future, similarities could also be expected in the business model evolution of these two industries. This paper focuses on the evolution of the Finnish power grid until 2035 and the role of mobile communications networks in this evolution. It outlines alternative futures (i.e. scenarios) and identifies the role of mobile communications networks in these scenarios. The paper uses an established scenario planning process and a group of experts to determine three scenarios for the evolution of services offered to customers in a future electricity system and four scenarios describing the evolution of grid management. Finally, the role of mobile communications (cellular networks) is analyzed in each of the scenarios. Results show that mobile networks can serve as a key enabler in those scenarios where smart grid evolution would be the most transformative. [ABSTRACT FROM AUTHOR]

The demand for a ubiquitous and accurate indoor localization service is continuously growing. Cellular-based systems are a good candidate to provide such ubiquitous service due to their wide availability worldwide. One of the main barriers to the accuracy of such services is the large number of models of cell phones, which results in variations of the measured received signal strength (RSS), even at the same location and time. In this paper, we propose OmniCells++ , a deep learning-based system that leverages cellular measurements from one or more training devices to provide consistent performance across unseen tracking phones. Specifically, OmniCells++ uses a novel approach to multi-task learning based on LSTM encoder–decoder models that allows it to learn a rich and device-invariant RSS representation without any assumptions about the source or target devices. OmniCells++ also incorporates different modules to boost the system's accuracy with RSS relative difference-based features and improve the deep model's generalization and robustness. Evaluation of OmniCells++ in two realistic testbeds using different Android phones with different form factors and cellular radio hardware shows that OmniCells++ can achieve a consistent median localization accuracy when tested on different phones. This is better than the state-of-the-art indoor cellular-based systems by at least 148%. [ABSTRACT FROM AUTHOR]