Search

Nowadays, efficient spectrum usage is one of the most important design principles to take into account in wireless communications due to the exponential growth of mobile devices. In that sense, solutions such as Non-Orthogonal Multiple Access (NOMA) and cognitive radio (CR) have been proposed. In essence, NOMA allows some interference level by using non-orthogonal resource allocation with a tolerable increase in receiver complexity employing successive interference cancellation (SIC). In this work, a novel mathematical model of teletraffic for users performing accessment, simultaneously, by means of Orthogonal Multiple Access (OMA) and NOMA, is developed using a Markovian process that considers bursts of arrivals to model the access schemes. This novel procedure implies a closed-form solution of the proposed system compared to other works where these parameters are estimated assuming the moment generating function obtained with approximation models. The model is validated with a discrete event simulator, considering different scenarios and simulation conditions. The simulation results are in agreement with the mathematical solution proposed. [ABSTRACT FROM AUTHOR]

This paper considers a caching system of a single server and multiple users. We aim to characterize the memory-rate tradeoff for caching with uncoded cache placement, under nonuniform file popularity. Focusing on the modified coded caching scheme (MCCS) recently proposed by Yu, etal., we formulate the cache placement optimization problem for the MCCS to minimize the average delivery rate under nonuniform file popularity, restricting to a class of popularity-first placements. We then present two information-theoretic lower bounds on the average rate for caching with uncoded placement, one for general cache placements and the other restricted to the popularity-first placements. By comparing the average rate of the optimized MCCS with the lower bounds, we prove that the optimized MCCS attains the general lower bound for the two-user case, providing the exact memory-rate tradeoff. Furthermore, it attains the popularity-first-based lower bound for the case of general $K$ users with distinct file requests. In these two cases, our results also reveal that the popularity-first placement is optimal for the MCCS, and zero-padding used in coded delivery incurs no loss of optimality. For the case of $K$ users with redundant file requests, our analysis shows that there may exist a gap between the optimized MCCS and the lower bounds due to zero-padding. We next fully characterize the optimal popularity-first cache placement for the MCCS, which is shown to possess a simple file-grouping structure and can be computed via an efficient algorithm using closed-form expressions. Finally, we extend our study to accommodate nonuniformity in both file popularity and size, where we show that the optimized MCCS attains the lower bound for the two-user case, providing the exact memory-rate tradeoff. Numerical results show that, for general settings, the gap between the optimized MCCS and the lower bound only exists in limited cases and is very small. [ABSTRACT FROM AUTHOR]

The future of the manufacturing industry highly depends on digital systems that transform existing production and monitoring systems into autonomous systems fulfilling stringent requirements in terms of availability, reliability, security, low latency, and positioning with high accuracy. In order to meet such requirements, private 5G networks are considered as a key enabling technology. In this article, we introduce the 5G-CLARITY system that integrates 5GNR, WiFi, and LiFi access networks, and develops novel management enablers to operate 5G-Advanced private networks. We describe three core features of 5G-CLARITY, including a multi-connectivity framework, a high-precision positioning server, and a management system to orchestrate private network slices. These features are evaluated by means of packet-level simulations and an experimental testbed demonstrating the ability of 5G-CLARITY to police access network traffic, to achieve centimeter-level positioning accuracy, and to provision private network slices in less than one minute. [ABSTRACT FROM AUTHOR]

Sixth generation (6G) wireless communication networks are expected to provide ultra-low latency and energy-efficient services for global users. The paradigm of wireless powered mobile edge computing (WP-MEC) provides a feasible framework to real-ize the above purposes by leveraging the advantage of both wireless power transfer and MEC. Howev-er, massive network traffic and control information overburden the centralized server. In this article, we integrate federated learning and deep reinforcement learning with WP-MEC to jointly optimize computing and communication resources. Specif-ically, we design an online learning framework to schedule computation tasks of mobile clients, where the learning model can be distributed over edge servers, and parameter synchronization happens on the cloud. The superiority of the designed frame-work is evaluated and compared with benchmarks in terms of average task completion delay and task completion ratio. Finally, we discuss some research challenges and opportunities for future WP-MEC. [ABSTRACT FROM AUTHOR]

As hordes of data-hungry devices challenge its current capabilities, Wi-Fi strikes back with 802.11be, alias Wi-Fi 7. This brand new amendment promises a (r)evolution of unlicensed wireless connectivity as we know it. To appreciate its foreseen impact, we start by overviewing the latest Wi-Fi-related news, with emphasis on the recently launched Wi-Fi 6E certification program. We then provide an updated digest of 802.11be essential features, vouching for multi-AP coordination as a must-have for critical and latency-sensitive applications. We finally get down to the nitty-gritty of one of its most enticing implementations – coordinated beamforming – for which our standard-compliant simulations confirm near-tenfold reductions in worst case delays. [ABSTRACT FROM AUTHOR]

In present scenario, the high speed data transmission services has pushed limits for wireless communication network capacity, at same time multimedia transmission in real-time needs provision of QoS, therefore the network capacity and small cell coverage has comes with lots of challenges. Improving the channel capacity and coverage area within the available bandwidth is necessary to provide better QoS to users, and improved channel capacity for the FCUs and MCUs in network. In this paper, we are proposing an NQHN approach that incorporate with efficient power allocation, improving the channel capacity by optimized traffic scheduling process in a small cell HetNets scenario. This work efficiently handle the interference with maintaining the user QoS and the implemented power controller uses HeNB power as per the real time based approach for macro-cell and femto-cell. Moreover, we consider the real traffic scenario to check the performance of our proposed approach with respect to existing algorithm. [ABSTRACT FROM AUTHOR]

For intrusion detection, it is increasingly important to detect the suspicious entities and potential threats. In this paper, we introduce the identification technologies of network entities to detect the potential intruders. However, traditional entities identification technologies based on the MAC address, IP address, or other explicit identifiers can be deactivated if the identifier is hidden or tampered. Meanwhile, the existing fingerprinting technology is also restricted by its limited performance and excessive time lapse. In order to realize entities identification in high-speed network environment, PFQ kernel module and Storm are used for high-speed packet capture and online traffic analysis, respectively. On this basis, a novel device fingerprinting technology based on runtime environment analysis is proposed, which employs logistic regression to implement online identification with a sliding window mechanism, reaching a recognition accuracy of 77.03% over a 60-minute period. In order to realize cross-device user identification, Web access records, domain names in DNS responses, and HTTP User-Agent information are extracted to constitute user behavioral fingerprints for online identification with Multinomial Naive Bayes model. When the minimum effective feature dimension is set to 9, it takes only 5 minutes to reach an accuracy of 79.51%. Performance test results show that the proposed methods can support over 10Gbps traffic capture and online analysis, and the system architecture is justified in practice because of its practicability and extensibility. [ABSTRACT FROM AUTHOR]

The heterogeneous network is the foundation of next-generation networks. It aims to explore the existing network resources effectively, and providing better QoS for every kind of traffic flow as far as possible. However, the diversity and dynamic nature of heterogeneous networks will bring a huge burden and big data to the network traffic control. Therefore, how to achieve efficient and intelligent network traffic control becomes the key problem of heterogeneous networks. In this article, an AI-inspired traffic control scheme is proposed. In order to realize fine-grained traffic control in heterogeneous networks, multi-dimensional (i.e., inter-layer, intra-layer, and caching and pushing) network traffic control is introduced. It is worth noting that backpropagation in deep recurrent neural networks is applied in the intra-layer such that an intelligent traffic control scheme can be derived efficiently when facing the huge traffic load in heterogeneous networks. Moreover, DBSCAN is adopted in the inter-layer, which supports efficient classification in the inter-layer. In addition, caching and pushing is adopted to make full use of network resources and provide better QoS. Simulation results demonstrate the effectiveness and practicability of the proposed scheme. [ABSTRACT FROM AUTHOR]

Wireless cameras are widely deployed in smart homes for security guarding, baby monitoring, fall detection, and so on. Those security cameras, which are supposed to protect users, however, may in turn leak a user’s personal privacy. In this paper, we reveal that attackers are able to infer whether users are at home or not, that is, the user presence, by eavesdropping the traffic of wireless cameras from distance. We propose HomeSpy, a system that infers user presence by inspecting the intrinsic pattern of the wireless camera traffic. To infer the user presence, HomeSpy first eavesdrops the wireless traffic around the target house and detects the existence of wireless cameras with a Long Short-Term Memory (LSTM) network. Then, HomeSpy infers the user presence using the bitrate variation of the wireless camera traffic based on a cumulative sum control chart (CUSUM) algorithm. We implement HomeSpy on the Android platform and validate it on 20 cameras. The evaluation results show that HomeSpy can achieve a successful attack rate of 97.2%. [ABSTRACT FROM AUTHOR]

In a multihop wireless network, the traffic at each node and the channel over each link may fluctuate with time. Thus, traditional optimal resource allocation needs to be computed for each moment with instantaneous information of channel states over all links and the traffic rates at all nodes, leading to huge communication overhead and computation cost. To solve this challenge, in this correspondence, we propose to use robust resource allocation, in which the only needed information is the mean and variance of the wireless channels and the traffic rates. In the formulated problem, there are probabilistic constraints, which are difficult to handle. Effective methods are provided that can transform the probabilistic constraints to convex constraints. As the resource allocation does not need instantaneous channel state information or instantaneous traffic rate information, it is robust to channel and traffic variations, with very little communication and computation overhead. [ABSTRACT FROM AUTHOR]

Studies on the current usage of the radio spectrum by several agencies have already revealed that a large fraction of the radio spectrum is inadequately utilized. This basic finding has led to numerous research initiatives. Cognitive radio technology is one of the key candidate technologies to solve the problems of spectrum scarcity and low spectrum utilization. However, random behavior of the primary user (PU) appears to be an enormous challenge. In this paper, a Pre-reservation based spectrum allocation method for cognitive radio network is proposed to apply a PU behavior aware joint spectrum band (SB) selection and allocation scheme. In the first step, the SB is observed in terms of PU usage statistics whereas in the second phase, a network operator (NO) using a spectrum allocation scheme is employed to allocate SBs among secondary users (SUs). We also introduce the concept of reservation and exchange functionality under the priority serving strategy in a time-varying framing process. Simulation results show that the proposed scheme outperforms existing schemes in terms of the spectrum utilization and network revenue. In addition, it helps NO to manage the spectrum on a planned basis with a systematical spectrum reservation management where the NO has the status of time slots. Moreover, SUs have an opportunity to reserve or instantly request a SB that maximizes the SUs satisfaction in terms of quality of experience. [ABSTRACT FROM AUTHOR]

The technological growth combined with the exponential increase of wireless traffic are pushing the wireless community to investigate solutions to maximally exploit the available spectrum. Among the proposed solutions, the operation of Long Term Evolution (LTE) in the unlicensed spectrum (LTE-U) has attracted significant attention. Recently, the 3rd Generation Partnership Project announced specifications that allow LTE to transmit in the unlicensed spectrum using a Listen Before Talk (LBT) procedure, respecting this way the regulator requirements worldwide. However, the proposed standards may cause coexistence issues between LTE and legacy Wi-Fi networks. In this article, it is discussed that a fair coexistence mechanism is needed to guarantee equal channel access opportunities for the co-located networks in a technology-agnostic way, taking into account potential traffic requirements. In order to enable harmonious coexistence and fair spectrum sharing among LTE-U and Wi-Fi, an adaptive LTE-U LBT scheme is presented. This scheme uses a variable LTE transmission opportunity (TXOP) followed by a variable muting period. This way, co-located Wi-Fi networks can exploit the muting period to gain access to the wireless medium. The scheme is studied and evaluated in different compelling scenarios using a simulation platform. The results show that by configuring the LTE-U with the appropriate TXOP and muting period values, the proposed scheme can significantly improve the coexistence among LTE-U and Wi-Fi in a fair manner. Finally, a preliminary algorithm is proposed on how the optimal configuration parameters can be selected towards harmonious and fair coexistence. [ABSTRACT FROM AUTHOR]

In the last few years, traffic over wireless networks has been increasing exponentially due to the impact of IoT. IoT is transforming a wide range of services in different domains of urban life, such as environmental monitoring, home automation, and public transportation. The so-called smart city applications will introduce a set of stringent requirements, such as low latency and high mobility, since services must be allocated and instantiated on demand, simultaneously, close to multiple devices at different locations. Efficient resource provisioning functionalities are needed to address these demanding constraints introduced by smart city applications while minimizing resource costs and maximizing QoS. In this article, the CoT framework is presented, which provides not only data collection and analysis functionalities but also automated resource provisioning mechanisms for future smart city applications. CoT is deployed as a smart city testbed in Antwerp, Belgium, which allows researchers and developers to easily set up and validate IoT experiments. A smart city use case of air quality monitoring through the deployment of air quality sensors in moving cars is presented showing the full applicability of the CoT framework for a flexible and scalable resource provisioning in the smart city ecosystem. [ABSTRACT FROM AUTHOR]

Interference and traffic imbalance hinder improved system performance in heterogeneous ultra-dense networks. Network cooperation has become a promising paradigm with sophisticated techniques that can significantly enhance performance. In this article, a coalition game-theoretic framework is introduced to characterize cooperative behaviors, thus exploring these cooperative benefits and diversity gains. First, we introduce the basis of the coalition games. Then we survey its latest applications, in particular, interference mitigation and traffic offloading. Different from most current applications, we concentrate on cooperative incentive mechanism design since node cooperation always means resource consumption and other costs. Moreover, for the incentive mechanism, cooperative spectrum leasing is introduced. To mitigate interference and balance traffic, we propose two schemes under the presented framework: IASL and TOSL. Simulation results show the improved performance of the cooperative gains using the proposed IASL and TOSL schemes. [ABSTRACT FROM AUTHOR]

Minimizing power consumption in bandwidth limited optical traffic grooming networks is presented as a two-objective optimization problem. Since the main objective is to route a connection, the network throughput is maximized first, and then the minimum power consumption solution is found for this maximized throughput. Both transparent IP over WDM (Tp-IPoWDM) and translucent IP over WDM (Tl-IPoWDM) network may be applied to examine such bi-objective algorithms. Simulations show that the bi-objective algorithms are more energy-efficient than the single objective algorithms where only the throughput is optimized. For a Tp-IPoWDM network, both link based ILP (LB-ILP) and path based ILP (PB-ILP) methods are formulated and solved. Simulation results show that PB-ILP can save more power than LB-ILP because PB-ILP has more path selections when lightpath lengths are limited. For a Tl-IPoWDM network, only PB-ILP is formulated and we show that the Tl-IPoWDM network consumes less energy than the Tp-IPoWDM network, especially under a sparse network topology. For both kinds of networks, it is shown that network energy efficiency can be improved by over-provisioning wavelengths, which gives the network more path choices. [ABSTRACT FROM AUTHOR]

Traffic offloading through small cells has been considered as a promising approach to accommodate tremendous traffic growth in future heterogeneous cellular networks (HCNs). The dense deployment of small cells, however, has led to a growing concern about the excessive carbon- based on-grid energy consumption in HCNs. In this article, we first overview the green-oriented traffic offloading in future HCNs that exploits the recent advanced energy technologies including energy harvesting (EH), local energy sharing (ES) enabled by smart grid, and wireless power transfer (WPT). We then discuss the challenges in resource management when exploiting EH, ES, and WPT to support traffic offloading, and provide possible solutions, especially by using the emerging dual connectivity (DC) in recent 3GPP specifications. Furthermore, we present a case study on the optimal DC-enabled traffic offloading through small cells that are powered by EH, with the objective of minimizing the total on-grid power consumption of all small cells and macrocells. The case study validates the benefit of exploiting the DC feature for traffic scheduling and the harvested energy to reduce the total on-grid power consumption. We finally share our view of some research directions in the green-oriented traffic offloading in HCNs. [ABSTRACT FROM PUBLISHER]

Cloud storage and computing, although it empowers ubiquitous and global information acquisition, analysis, and management, the latency performance and heavy traffic burdens at fronthaul/ hackhaul links have emerged as critical concerns due to the scalability issue, which consequently drives the development of edge content cache and dissemination. Despite ample research on latency and traffic load reduction, an effective design of edge content cache and dissemination from the perspective of energy efficiency is imperative. Noting the fact that wireless service demands are inherently unbalanced over geographic regions, a practical cell planning strategy of operators' basic interests should deploy base stations massively in hot spot areas and sparsely in rural areas. A mobile user is therefore able to acquire desired contents through multiple base stations in a hot spot, while performing autonomous content cache and dissemination with other mobile users in rural areas. Taking this practical constraint into consideration, this article offers energy-optimal edge content cache and dissemination designs for hot spot and rural areas. Exploiting Lyapunov optimization and optimum control theory, we demonstrate analytical foundations and principles of the proposed optimum designs. Engineering insights are also revealed through practical simulation investigations to extend the research frontier of energy-efficient edge content cache and dissemination. [ABSTRACT FROM PUBLISHER]

In this paper, we propose an efficient analytical method for admission control of wireless virtual networks (VNs), with heterogeneous traffic profiles, and various quality-of-experience (QoE) requirements, in the future software-defined radio access networks. We present a novel methodology for the admission control process that includes feedback information to the VN customers to improve their traffic profile accuracy, and consequently, their QoE. We formulate the virtual network admission control problem as a convex optimization problem which allows general multiple association between user equipment and base stations. Consequently, we propose an algorithm for solving this problem. The proposed method is applicable on heterogeneous networks with heterogeneous traffic distributions. We also propose a number of extensions to the problem including mechanisms that consider minimization of the network and service cost, and optimization according to the backhaul limitations. The simulation results show that our proposed methods are accurate and result in significant improvement in network resource utilization and customer satisfaction. [ABSTRACT FROM PUBLISHER]

Non-hierarchical overflow loss systems (NH-OLSs) with mutual overflow have applications in many telecommunications and service systems, e.g., cellular networks, video-on-demand, emergency healthcare, or cloud services. In this paper, we make fundamental contributions in teletraffic modeling for blocking probability evaluation in NH-OLSs. These are based on the development of the well-known decomposition methodology, which decomposes an NH-OLS into independent subsystems and applies a suitable node model to each subsystem. In particular, we provide new both theoretical and numerical results involving both new and existing approximation methods. We show that these results cover a broad range of NH-OLSs, including those with heterogeneous arrival processes, server group size, and/or routing, with both Poisson and non-Poisson arrivals of fresh requests. Our theoretical results include the first scalable asymptotic exactness results for NH-OLSs. Our new approximations include the first computationally efficient and fairly accurate approximation for NH-OLSs with both mutual overflow and non-Poisson input with asymptotic exactness properties. [ABSTRACT FROM PUBLISHER]

Small cell networks (SCNs) have emerged as promising technologies to meet the data traffic demands for the future wireless communications. However, the benefits of SCNs are limited to their hard handovers between base stations (BSs). In addition, the interference is another challenging issue. To solve this problem, this study employs a cooperative transmission mechanism focusing on correlated Rician/Gamma fading channels with zero‐forcing receivers. The analytical expressions for the achievable sum rate, symbol error rate and outage probability are derived, which are applicable to arbitrary Rician factors, correlation coefficients, the number of antennas, and remain tight across entire signal‐to‐noise ratios (SNRs). Asymptotic analyses at the high and low SNR regimes are carried out in order to further reveal the insights of the model parameters on the system performance. Monte‐Carlo simulation results validate the correctness of their derivations. Numerical results indicate that the theoretical expressions provide sufficiently accurate approximation to simulated results. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the resource allocation problem in two-tier heterogenous networks (HetNets) with massive MIMO, where two frequency bands, cellular frequency band and millimeter wave frequency band, are used for wireless backhaul links. To coordinate the interference among small cells (SCs), SCs are grouped into multiple SC clusters (SCCs), where SC users are jointly served by SC base stations (BSs) (SBSs) belonging to the same SCC. To eliminate the multi-user and inter-tier interference, we propose a block diagonalization based precoding scheme at macro-BS and each SCC, where the transmit precoding matrix for users is projected onto the null space of interference channels. Following this, we formulate a power allocation optimization problem to maximize the downlink sum rate of the system subject to per-SCC power and users’ quality of service requirements. Since the formulated problem is nonconvex, we transform it into a convex one by appropriate approximation, and a constrained concave convex procedure based iterative algorithm is proposed to obtain the solution. Furthermore, we prove that the obtained solution converges to the local optimum. Meanwhile, according to the structure of the original formulated problem, we divide it into multiple subproblems and propose an optimal iterative water-filling algorithm. Next, we extend the original problem with per-SBS power constraint, which results in that the precoding of each SCC has to be redesigned. On this basis, we propose an iterative water-filling algorithm to obtain the optimal power allocation and precoding. Numerical results are presented to verify the performance of our proposed algorithms. [ABSTRACT FROM PUBLISHER]

This paper studies the issues on wireless networks virtualization in terms of two important performance metrics, i.e., energy efficiency (EE) and delay. Different from existing works on physical layer, we aim to achieve a good tradeoff between EE and delay in wireless networks virtualization using cross-layer stochastic optimization approach. In particular, we formulate a cross-layer problem using fractional programming and Lyapunov optimization method. The EE and delay tradeoff solution is given explicitly by deriving their analytical bounds that are verified by simulation results. [ABSTRACT FROM PUBLISHER]

This work aims the development of scheduling algorithms to maximize user satisfaction index in the downlink of an Orthogonal Frequency Division Multiple Access network, considering different traffic models of Non-Real Time and Real Time services; and more realistic channel conditions, eg, imperfect Channel State Information. To solve the problem of maximizing the satisfaction with affordable complexity, a cross layer optimization approach uses the utility theory to formulate the problem as a weighted sum rate maximization. Aiming at the maximization of the satisfaction of users of Non-Real Time and Real Time services, 2 scheduling algorithms are proposed: Modified Throughput Satisfaction Maximization and Modified Delay-based Satisfaction Maximization, respectively. The modification of parameters of the shifted log-logistic utility function enables different strategies of distribution of resources. System level simulations indicate the accomplishment of the objective of development of efficient and low complexity scheduling algorithms able to maximize the satisfaction indexes. These strategies can be useful to the network operator who is able to design and operate the network according to a planned user satisfaction profile. [ABSTRACT FROM AUTHOR]

For transmission of packetised media, real‐time communications rely on the real‐time protocol (RTP). RTP traffic, however, is transmitted over datagram‐based transport that allows fast delivery of media. Internet firewalls are typically configured to allow web friendly traffic that uses stream‐based transport instead and, simultaneously as security measure, reject any other type of transport. A mechanism to overcome this limitation is by switching transport such that media frames that would be rejected by firewalls are transmitted on top of stream transport. In this study, a novel mathematical model that links application layer packet loss to bursty network packet loss in the context of fading channels characteristic of wireless communications is presented for both, datagram and stream transport. This model is compared with experimental scenarios applied to state‐of‐the‐art speech codecs in order to obtain quality scores that can be correlated against theoretical loss probabilities. [ABSTRACT FROM AUTHOR]

To support a tremendous amount of traffic demands via wireless access in 2020 and beyond, limited bandwidth of the licensed bands has been a major obstacle to boosting further the capacity of wireless services. To fundamentally break through this predicament, an emerging technology known as heterogeneous carrier communications has been launched into standardization in the form of licensed-assisted access (LAA) to the unlicensed bands. Integrating the heterogeneous cloud radio access networks and carrier aggregation, and although LAA-empowered cellular networks gain wider bandwidth from the unlicensed bands, communications may suffer from intersystem interference. To avoid interference, listen-before-talk has been designated as a mandatory function; however, it leads to significant challenges of the hidden-terminal problem. To address this open issue in LAA, in this paper, we consequently propose a resource-optimal scheme using a minimum amount of replicated radio resources to achieve the most essential latency guarantees for real-time applications. To further support non-real-time applications, a new resource control as well as the mathematical architecture inspired by so-called political communications is proposed to further maximize the throughput of packet delivery. Our scheme not only optimizes resource utilization in time and spatial domains but also suggests optimum energy efficiency and computation efficiency, to successfully deploy cellular networks on the unlicensed bands. [ABSTRACT FROM PUBLISHER]

Bridging between two cognitive personal area networks (CPANs) is a fundamental step toward a reliable and efficient routing protocol. In this paper, we describe a bridging protocol for two-hop cognitive networks that use the transmission tax-based medium access control and propose ways to prioritize bridge traffic over that of ordinary nodes in both CPANs. We develop an analytical model based on probabilistic modeling and queueing theory to evaluate the performance of the bridging protocol. We validate the network performance by analyzing the waiting time of local and nonlocal packets and how the node or bridge transmission is affected by the collision with primary-source activity. Our results provide insights into the impact of various traffic and network parameters on the performance of two-hop bridging. The results indicate that the proposed protocol is effective and efficient when the bridge transfers a moderate amount of traffic. [ABSTRACT FROM PUBLISHER]

With the advances in wireless communication and mobile computing, a future infrastructureless self-organizing traffic information system, where vehicles can form a network for exchanging traffic information among themselves, will soon be realized. In an infrastructureless traffic information system, vehicles will act as mobile sensors and collect the traffic data as they travel. Smartphones are a great choice for traffic sensing devices as they are now equipped with a variety of sensors such as global positioning system (GPS) receivers, accelerometers, gyroscopes, cameras, and microphones. These sensors can be exploited to collect traffic data. Although there are many types of sensors available for traffic sensing, past studies have mainly focused on a GPS receiver. However, a GPS receiver consumes a lot of power; hence, it can significantly shorten the battery life. In this paper, we explore a possibility of using other types of sensors on a smartphone for traffic sensing. In particular, we investigate whether it is possible and how accurate it is to estimate the average speed of a vehicle from the data sensed by an accelerometer. Two estimation methods will be introduced, and their accuracy will be evaluated. [ABSTRACT FROM AUTHOR]

In Wireless communication, to provide good Quality of service (QoS), network operators have to make the effective use of their available resources, which leads to effective network design and network planning. The blocking probability is the dominant parameter used for effective network design and network planning. It is defined as the probability of service being denied to users due to the non-availability of radio resources and is determined from the number of available channels and traffic load in Erlangs. In this paper, the blocking probability of Orthogonal Frequency Division Multiple Access (OFDMA) technique, used in 4G cellular communication system, is investigated for assessing the QoS of the network. The blocking probability of FDMA and TDMA based systems is estimated by using the Erlang-B formula. The blocking probability of OFDMA is estimated using a proposed dynamic algorithm which is based on the Signal to Interference plus Noise Ratio (SINR) of users and other QoS parameters such as the power transmitted by the base station to each sub-carrier and the data rate. The results obtained using the proposed algorithm show that when the traffic of the OFDMA system is increased from 2 to 40 Erlangs, then the blocking probability increases from 0.3378 to 0.7075. The variation in the blocking probability of an OFDMA-based cellular system with different data rates and base station-transmitted power to sub-carriers is also estimated. [ABSTRACT FROM AUTHOR]

Communication networks these days face a relentless increase in traffic load. Multi-gigabitper- second links are becoming widespread, and network devices are under continuous stress, so testing whether they guarantee the specified throughput or delay is a must. Software-based solutions, such as packet-train traffic injection, were adequate for lower speeds, but they have become inaccurate in the current scenario. Hardware-based solutions have proved to be very accurate, but usually at the expense of much higher development and acquisition costs. Fortunately, new affordable FPGA SoC devices, as well as high-level synthesis tools, can very efficiently reduce these costs. In this article we show the advantages of hardware-based solutions in terms of accuracy, comparing the results obtained in an FPGA SoC development platform and in NetFPGA-10G to those of software. Results show that a hardware-based solution is significantly better, especially at 10 Gb/s. By leveraging high-level synthesis and open source platforms, prototypes were quickly developed. Noticeable advantages of our proposal are high accuracy, competitive cost with respect to the software counterpart, which runs in high-end off-the-shelf workstations, and the capability to easily evolve to upcoming 40 Gb/s and 100 Gb/s networks. [ABSTRACT FROM AUTHOR]

A table of contents for the issue is presented.

This paper proposes a Prioritized New Call Threshold Policy for Call Admission Control schemes. It is known that connection reattempts negatively affect the system performance. In currently proposed policy, the system's performance is improved by decreasing the number of connection reattempts. In order to demonstrate that the proposed scheme is better than the traditionally utilized ones in terms of various parameters, the simulations were utilized. It predicts the time that the mobile station will spend in the current cell, mobile station with different remaining time will have different number of channels available for them. More channels are available for the new calls with higher remaining time. Simulations were used in order to show that the proposed scheme outperforms the traditionally employed mechanisms in terms of various parameters. [ABSTRACT FROM AUTHOR]

In this paper, we study the power allocation for two-way amplify-and-forward relay networks with asymmetric traffic requirements in cognitive radio. The proposed power allocation scheme is achieved by minimizing the weaker link's individual outage probability under the sum-power constraint and interference power threshold (IPT) constraints of the primary user (PU). Particularly, for the purpose of accomplishing the power allocation more realistically, the interference to each other between PU and secondary user (SU) and relay is taken into consideration. And the closed-form solution is derived for the optimum power allocation scheme of each case. Numerical results confirm that the proposed scheme improves the system performance compared with the equal power allocation scheme under various traffic requirements. The outage probability of SU communication is limited by the IPT constraints of PU and is affected significantly by the IPT level of PU. Furthermore, regardless of the symmetric or asymmetric traffic requirements, the proposed power allocation scheme is more suitable for cognitive two-way relaying networks. [ABSTRACT FROM AUTHOR]

In recent years, MANETs have received a significant amount of attention due to the growing number of wireless device users. This has resulted in increasing the need to support real-time applications. The real-time applications require QoS assurances in terms of throughput. The major issue that is faced while providing QoS in MANET is the communication over a shared medium in a single channel. In this paper, we propose an Achievable Throughput-based Admission Control Protocol (ATACP) for preventing a channel from becoming overloaded, thereby ensuring guaranteed throughput for the real time traffic. ATACP works in a cross-layer architecture that encompasses the network and the MAC layers. The admission control is carried in each node during the route discovery. The node broadcasts the route request to its neighbors only if its achievable throughput satisfies the required throughput with considering the contention count. The achievable throughput is estimated based on the minimum idle fraction within the carrier sense range, taking into account the packet size of the new flow and the error and collision probabilities. Through extensive simulations in NS2, we show that our proposed scheme outperforms the existing ones in terms of throughput, end-to-end delay and overall performance. [ABSTRACT FROM AUTHOR]

With advances in technology, network operators may need to set up a dynamic spectrum access overlay in heterogeneous networks (HetNets) to increase network coverage, spectrum efficiency, and the capacity of these networks. Uses of TV white space (TVWS) and long term evolution (LTE) are the combination of a new research direction to meet the increasing user demands in the domain of wireless cellular networks. Without the consideration of traffic flow, a network may operate with serious congestion problems that degrade the system performance. Congestion problems can be resolved by either reducing traffic flow or increasing the bandwidth provision. This paper has proposed Distributed dynamic load balancing (DDLB) cellular-based TVWS and LTE technique, such that a cellular-based device can operate on both TVWS and LTE by simply switching its frequency of operation when necessary. The objective of this paper is to resolve the congestion problems in a HetNet through dynamically constructing new clusters to increase the system bandwidth. The simulation results show that the proposed technique solved the bottleneck problem, reduced transmission control overhead and power consumption, and increased the average throughput and load balancing index. [ABSTRACT FROM AUTHOR]

The rapidly growing wave of wireless data service is pushing against the boundary of our communication network's processing power. The pervasive and exponentially increasing data traffic present imminent challenges to all aspects of wireless system design, such as spectrum efficiency, computing capabilities, and fronthaul/backhaul link capacity. In this article, we discuss the challenges and opportunities in the design of scalable wireless systems to embrace the big data era. On one hand, we review the state-of-the-art networking architectures and signal processing techniques adaptable for managing big data traffic in wireless networks. On the other hand, instead of viewing mobile big data as an unwanted burden, we introduce methods to capitalize on the vast data traffic, for building a big-data-aware wireless network with better wireless service quality and new mobile applications. We highlight several promising future research directions for wireless communications in the mobile big data era. [ABSTRACT FROM PUBLISHER]

The introduction of smart electricity meters with cellular radio interfaces has placed an additional load on wireless cellular networks. Currently, these meters are designed for low duty cycle billing and occasional system check, which generates low-rate sporadic traffic. As the number of distributed energy resources increases, household power will become more variable and thus unpredictable from the viewpoint of the distribution system operator (DSO). Therefore, it is expected that in the near future there will be an increase in the number of wide area measurement system (WAMS) devices with phasor measurement unit (PMU)-like capabilities in the distribution grid, thus allowing utilities to monitor the low voltage grid quality while providing information required for tighter grid control. From a communication standpoint, the traffic profile will change drastically toward higher data volumes and higher rates per device. In this paper we characterize the current traffic generated by smart electricity meters, and we discuss the potential traffic requirements resulting from the introduction of enhanced smart meters, i.e. meters with PMUlike capabilities. Our study shows how GSM/ GPRS and LTE cellular system performance behaves with current generation and next generation smart meter traffic, where it is clearly seen that the PMU data will seriously challenge these wireless systems. We conclude by highlighting the possible solutions for upgrading the cellular standards, in order to cope with the upcoming smart metering traffic. [ABSTRACT FROM PUBLISHER]

In this article we discuss the design of a new fronthaul interface for future 5G networks. The major shortcomings of current fronthaul solutions are first analyzed, and then a new fronthaul interface called next-generation fronthaul interface (NGFI) is proposed. The design principles for NGFI are presented, including decoupling the fronthaul bandwidth from the number of antennas, decoupling cell and user equipment processing, and focusing on high-performancegain collaborative technologies. NGFI aims to better support key 5G technologies, in particular cloud RAN, network functions virtualization, and large-scale antenna systems. NGFI claims the advantages of reduced bandwidth as well as improved transmission efficiency by exploiting the tidal wave effect on mobile network traffic. The transmission of NGFI is based on Ethernet to enjoy the benefits of flexibility and reliability. The major impact, challenges, and potential solutions of Ethernet-based fronthaul networks are also analyzed. Jitter, latency, and time and frequency synchronization are the major issues to overcome. [ABSTRACT FROM PUBLISHER]

To realize collaborative transmission in wireless overlay access networks, the question of rate allocation arises as how to divide the traffic flow among heterogeneous networks. Different networks role as game players and they try to transmit the traffic flow by a cooperative method. Power costs and transmission capabilities in heterogeneous networks are different according to terminal position, network load etc, so the grand coalition is not always beneficial and the coalition structure should be adjusted in time. With the power cost introduced in the utility function, the rate allocation is formulated in a coalition formation game framework in the paper. The stable coalition structure is formed with the merge-and-split rule, then the utility is distributed to different players and the transmission rates in different networks are determined. Such a process continues until the end of the traffic transmission. The theoretical and experimental results are presented to validate our proposed method. Compared with the Nash Bargaining Solution and the Shapley value, the coalition structure can be adjusted with the terminal position through the new scheme and then the highest coalition utility can be obtained with low power cost. Moreover, the proposed method turns to be the bargaining game framework if the power cost is not considered. [ABSTRACT FROM AUTHOR]

Delay-Tolerant Networks (DTNs) are characterized by time-varying and partially connected network topology. In such networks, mobility of node may be by virtue of its carrier. Social beings such as humans may act as a carrier of mobile nodes, and therefore mobility pattern of node follows a social-based movement model. Due to intermittent connectivity, end-to-end path between source and destination is rare and therefore message delivery is a challenge in such networks. In this paper, we present a new routing approach, context-aware community-oriented routing (CONCOR) that exploits the community and the context awareness of nodes, for efficient message delivery. Nodes with a common point of interest form a dynamic community. We have identified a set of node's attribute (context) and formulated a utility function to determine its capability to deliver a message. CONCOR is a multihop routing approach exploiting the nodes as message relays (store-carry-forward). Through simulation, we validated the effectiveness of node's attributes in estimation of message delivery probability. The simulations were done for our approach using the social movement-based data set on Opportunistic Network Environment (ONE) simulator. We compared our approach with dynamic social grouping (DSG)-based routing and context-aware routing(CAR) on three metrics viz. message delivery ratio, message traffic ratio and average message delay. We found that the results of our approach outperforms the DSG and CAR on all the three metrics. [ABSTRACT FROM AUTHOR]

Transmission Control Protocol (TCP) performs poorly over wireless networks. Some research indicates that the TCP congestion control mechanism may cause burstiness in the traffic flow. Numerous TCP segments are delivered simultaneously, while an acknowledgement of a retransmission is successfully received. Burstiness leads to a highly contentious network, which markedly increases the probability of packet loss on wireless networks. TCP pacing is a possible solutions for TCP burstiness on multi-hop networks. In this algorithm, TCP segment transmissions are distributed over the whole Round Trip Time. Most pacing protocols attempt to insert a delay interval into the TCP transmissions. However, there is a similar pacing algorithm in IEEE802.11, known as the contention window mechanism. In this paper, we first measure and analyze the way that the contention window size affects TCP throughput in different scenarios. We propose a cross-layer TCP pacing protocol by contention control in the MAC layer, called TCP Contention Control (TCP-CC). It adjusts the lower bound of the contention window in order to optimize the overall TCP throughput in both one-hop and multi-hop topology. Finally, comparative simulations are conducted in order to verify the improvements of our protocol on both TCP Reno and TCP Vegas. [ABSTRACT FROM AUTHOR]

The energy cost of cellular networks is ever increasing to match the surge of wireless data traffic, and savings in this cost is important to reduce the operational expenditure of wireless operators in the future. Recent advancements in renewable energy integration and two-way energy flow in smart grid provide potential new solutions to save cost. However, they also impose challenges, especially on how to use the stochastically and spatially distributed renewable energy harvested at cellular BSs to reliably supply time- and space-varying wireless traffic over cellular networks. To overcome these challenges, in this article we present three approaches, energy cooperation, communication cooperation, and joint energy and communication cooperation, in which different BSs bidirectionally trade or share energy via the aggregator in smart grid, and/or share wireless resources and shift loads with each other to reduce the total energy cost. [ABSTRACT FROM PUBLISHER]

The capacities of wireless networks are increasingly challenged by the traffic stresses generated by data-intensive applications. Multicast is a bandwidth-efficient solution to simultaneously disseminate data to multiple receivers. In this paper, we present NCOM, a network coding based overlay multicast design, that integrates network coding (NC), opportunistic routing (OR), and cross-layer link scheduling to achieve high efficiency and reliability in multi-hop wireless multicast. In NCOM, the source and receivers are connected by an overlay Steiner tree optimized for the minimum OR distance between nodes. With NC, coded packets are opportunistically transmitted along overlay links. The transmissions of adjacent nodes in the overlay multicast are coordinated by a novel multicast acknowledgement scheme and cross-layer MAC scheduling. We implement NCOM in OPNET by customizing the IEEE 802.11b modules. Through OPNET simulations, we demonstrate that NCOM can achieve a higher throughput and lower source transmission redundancy than the existing NC and OR based wireless multicast designs. NCOM can be easily deployed for efficient and reliable multicast in multi-hop wireless networks. [ABSTRACT FROM AUTHOR]

The search for a method of utilizing the scarce spectrum in an efficient manner is an active area of research in both academic and industrial communities. IEEE 802.22 is a standard for wireless regional area network (WRAN) based on cognitive radio (CR) that operates over underutilized portions of TV bands (54-862MHz). Time division duplex (TDD)-based WRAN cells have such advantages as dynamic traffic allocation, traffic asymmetry to users and ease of spectrum allocation. However, these cells suffer from severe cross time slot (CTS) interference when the frames of the cells are not synchronized with adjacent WRAN cells. In this paper, we evaluate the location-based duplex (LBD) scheme for eliminating the CTS interference. The proposed LBD system is much more flexible and efficient in providing asymmetric data service and eliminating CTS interference by exploiting the advantages of both TDD and frequency division duplex (FDD) schemes. We also compare the performance of LBD systems with virtual cell concepts. Furthermore, our simulation results reveal that LBD-based systems outperform the virtual cell approach in terms of the low signal-to-interference (SIR) ratio requirement by mitigating the effects of CTS. [ABSTRACT FROM AUTHOR]

Rapid growing demand for mobile data traffic challenges capacities and service provision in the next-generation (5G) cellular networks. Real measurement data from operating cellular networks indicates that the traffic models and scenarios disobey our traditional assumptions (i.e., expressing bursty nature). As a result, current network architectures and service management may cause experience deterioration of subscribers in future networks. In this article, we propose three approaches to alleviate the influence of various traffic bursts: baseband resource pool on a cloud platform as wireless infrastructure to enhance the capacity and flexibility of networks, cloud core networks to provide dynamic extension and service flow control abilities, and software-defined bearer networks to simplify service delivery instructed by core networks. Different from conventional stovepipe-like cloud computing network architectures, our proposed architecture interconnects and shares information between entities, breaking through horizontal device barriers and vertical layers. These cloud-based approaches not only avoid the potentially negative impact of bursts, but also provide a software-controlled end-to-end service management framework for future cellular networks. In addition, by taking advantage of open interfaces of cloud-based network elements, service control algorithms and network APIs could also be implemented to realize smart and soft 5G cellular networks. [ABSTRACT FROM PUBLISHER]

5G networks are expected to achieve gigabit-level throughput in future cellular networks. However, it is a great challenge to treat 5G wireless backhaul traffic in an effective way. In this article, we analyze the wireless backhaul traffic in two typical network architectures adopting small cell and millimeter wave communication technologies. Furthermore, the energy efficiency of wireless backhaul networks is compared for different network architectures and frequency bands. Numerical comparison results provide some guidelines for deploying future 5G wireless backhaul networks in economical and highly energy-efficient ways. [ABSTRACT FROM PUBLISHER]

Powered by renewable energy sources, cellular communication systems usually have different wireless traffic loads and available resources over time. To match their traffics, it is beneficial for two neighboring systems to cooperate in resource sharing when one is excessive in one resource (e.g., spectrum), while the other is sufficient in another (e.g., energy). In this paper, we propose a joint energy and spectrum cooperation scheme between different cellular systems to reduce their operational costs. When the two systems are fully cooperative in nature (e.g., belonging to the same entity), we formulate the cooperation problem as a convex optimization problem to minimize their weighted sum cost and obtain the optimal solution in closed form. We also study another partially cooperative scenario where the two systems have their own interests. We show that the two systems seek for partial cooperation as long as they find inter-system complementarity between the energy and spectrum resources. Under the partial cooperation conditions, we propose a distributed algorithm for the two systems to gradually and simultaneously reduce their costs from the non-cooperative benchmark to the Pareto optimum. This distributed algorithm also has proportional fair cost reduction by reducing each system's cost proportionally over iterations. Finally, we provide numerical results to validate the convergence of the distributed algorithm to the Pareto optimality and compare the centralized and distributed cost reduction approaches for fully and partially cooperative scenarios. [ABSTRACT FROM AUTHOR]