Number Of Available Channels Research Articles

Lower Extremity Somatosensory Evoked Potential P37 Waveform Optimization

ABSTRACTSomatosensory evoked potentials (SEPs) using tibial nerve stimulation are used during neurophysiologic intraoperative monitoring (NIOM). These SEPs produce a P37 waveform that is recorded from scalp electrodes. In this study, we attempted to determine the best derivation for recording the P37 waveform. Surgical cases using tibial nerve SEP NIOM were reviewed. Only cases in which the P37 was recorded using all of the following derivations were analyzed: centroparietal ipsilateral–centroparietal contralateral (CPi-CPc), centroparietal midline–frontopolar midline (CPz-Fpz), and CPz-CPc. The amplitude of the P37 waveform was measured in each derivation. Descriptive statistics were obtained for the P37 waveform amplitude. The mean amplitude in each of the derivations was compared using a chi-square test. Data from 39 patients (78 lower limbs) were available for analysis. The mean age of the patients was 49.64 years (range: 4–87 years); 18 were female. The highest amplitude P37 waveform was recorded from the CPz-Fpz derivation in 29 (35.4%) limbs, whereas the CPz-CPc and CPi-CPc derivations showed the highest amplitude in 29 (35.4%) and 20 (24.4%) limbs, respectively. The mean amplitudes were not significantly different between the various derivations. In only 10 (24.4%) of patients was the best derivation the same for both left and right limbs. A single best derivation was not found for recording the P37 waveform. Multiple derivations should be used to record cortical channels whenever possible. If the number of available channels is limited, using at least the CPz-Fpz and CPz-CPc derivations is recommended.

Soft-GORA: Soft Constrained Globally Optimal Resource Allocation for Critical Links in IoT Backhaul Communication

The Internet of Things gateways with multi-radio facilities in wireless networks can simultaneously communicate using multiple available channels. This feature enhances the carrying capacity of wireless links and thus increases the overall network throughput. However, designing an efficient resource allocation strategy is a complex task due to the decisive behavior of interference. There is only a limited number of available channels; therefore, the resource allocation requires careful planning to mitigate the effect of interference. This research proposes a backtracking search-based resource allocation scheme that maps resource allocation to the constraint satisfaction problem. Some of the resource allocation constraints are applied as soft constraints which are relaxed to find a feasible solution, provided the perfect allocation of limited resources is not possible. The proposed approach has been benchmarked through simulations and the results prove the effectiveness of the proposed approach especially in dense multi-hop network deployments.

Impact of Channel Heterogeneity on Clustering Formation in Cognitive Ad Hoc Radio Networks

In cognitive radio, wireless ad hoc networks, the rapid changes in environment in addition to heterogeneous spectrum availability among the CR users resulted in the connectivity and stability problem of the network. A cluster structure is seen as an effective technique to overcome this problem. Presently, most existing works in cognitive radio focus on forming clusters under the homogenous channel model. Withal, the channels that are situated in vastly isolated frequency bands show a remarkable heterogeneity in transmission ranges. In this paper, we proposed a greedy heuristic algorithm for clustering to identify the effect of channel heterogeneity on cluster formation performance. A new metric for cluster head selection named selection factor is proposed. This metric is computed based on the number of available channels, the number of common channels that a CR user share with each of its neighbors, channel reward (coverage) for the available channels and the number of neighbors. To the best of our knowledge this is the first effort to add the channel heterogeneity into the formulation of cluster head election in cognitive wireless networks. We investigate the clustering formation, performance for the CRAHN under both heterogeneous and homogeneous channel models. Particularly, we evaluate the average number of clusters, cluster size, number of common available channels within each cluster and load balance among clusters. The algorithm has been implemented and tested using Matlab. Simulation results revealed that the performance of clustering is significantly affected by the channel heterogeneity.

Multi-Channel Distributed DSA Networks: Connectivity and Rendezvous Tradeoffs

In this paper, we investigate and characterize the effects of multi-channel and rendezvous protocols on the connectivity of dynamic spectrum access networks using percolation theory. In particular, we focus on the scenario where the secondary nodes have plenty of vacant channels to choose from a phenomenon which we define as channel abundance. To cope with the existence of multi-channel, we use two types of rendezvous protocols: naive ones which do not guarantee a common channel and advanced ones which do. We show that, with more channel abundance, even with the use of either type of rendezvous protocols, it becomes difficult for two nodes to agree on a common channel, thereby, potentially remaining invisible to each other. We model this invisibility as a Poisson thinning process and show that invisibility is even more pronounced with channel abundance. Following the disk graph model, we represent the multiple channels as parallel edges in a graph and build a multi-layered graph (MLG) in $\boldsymbol {\mathcal {R}}^{\mathbf{2}}$ . In order to study the connectivity, we show how percolation occurs in the MLG by coupling it with a typical discrete percolation. Using a Boolean model and the MLG, we study both cases of primaries’ absence and presence. For both cases, we define and characterize connectivity of the secondary network in terms of the available number of channels, deployment densities, number of simultaneous transmissions per node, and communication range. When primary users are absent, we derive the critical number of channels which maintains super-criticality of the secondary network. When primary users are present, we characterize and analyze the connectivity for all the regions: channel abundance, optimal, and channel deprivation. For each region we show the requirement and the outcome of using either type of rendezvous techniques. Moreover, we find the tradeoff between deployment-density versus rendezvous probability which results in a connected network. Our results can be used to decide on the goodness of any channel rendezvous algorithm by computing the expected resultant connectivity. They also provide a guideline for achieving connectivity using minimal resources.

Interference Management in Full-Duplex Cellular Networks With Partial Spectrum Overlap

Full-duplex (FD) communication is promoted to double the spectral efficiency when compared with the half-duplex counterpart. In the context of cellular networks, however, FD communication exacerbates the aggregate uplink (UL) and downlink (DL) interference, which diminishes the foreseen FD gains. This paper considers a flexible duplex system, denoted by $\alpha $ -duplex system, wherein a fine-grained bandwidth control for each UL/DL channel pair in each base station (BS) is allowed, which also leads to partial spectrum overlap between the UL and DL channels. This paper addresses the resulting interference management problem by maximizing a network-wide rate-based utility function subject to UL/DL power constraints, so as to determine user-to-BS association, user-to-channel scheduling, the UL and DL transmit powers, and the fraction of spectrum overlap between UL and DL for every user, under the assumption that the number of available channels and users is equal. This paper solves such a non-convex mixed-integer optimization problem in an iterative way by decoupling the problem into several sub-problems. Particularly, the user-to-BS association problem is solved using a matching algorithm that is a generalization of the stable marriage problem. The scheduling problem is solved by an iterative Hungarian algorithm. The power and spectrum overlap problem is solved by successive convex approximation. The proposed iterative strategy guarantees an efficient one-to-one user to BS and channel assignment. It further provides optimized flexible duplexing and power allocation schemes for all transceivers. Simulations results show appreciable gains when comparing the proposed solution with different schemes from the literature.

Traffic-Aware Joint Allocation of Uplink Control and Communication Channels in Multicast Systems

In multicast wireless access systems such as a trunked mobile radio system, channel allocation is performed based on multicast groups instead of radio units. Thus, in these systems, the call source units are these groups, which we also call the users . In a practical system, these users are finite in number, and each user or group may consist of many radio units. In this paper, we discuss the coupling of uplink control and communication segments (layers) of such finite source systems, in which the performance of one layer directly affects that of the other. The conventional studies model these system segments separately and, thus, are unable to capture the coupling issues in networks with the finite sources' constraint. We first propose a novel model that incorporates this coupling by jointly quantifying both the collision loss at the control layer and congestion loss at the communication layer. Under our proposed framework, we further optimize the number of uplink control and communication channels to minimize the joint total loss rate given a constraint on the total number of available channels. In addition, we demonstrate the capability of our proposed model in estimating the invisible actual traffic load and provide guidelines for developing an algorithm for the traffic-aware allocation of channels, based on the proposed model.

A novel spectrum handoff-based sensing-throughput tradeoff scheme in cognitive radio

In cognitive radio (CR), there is a tradeoff between spectrum sensing time and throughput of secondary user (SU). In the conventional sensing-throughput tradeoff scheme, when the presence of the primary user (PU) is detected, the SU will stop forwarding data and wait to redetect the PU in the following frame, yielding great throughput loss. In order to improve the SU's throughput, a novel sensing-throughput tradeoff scheme is proposed, which allows the SU to search for a new idle channel through spectrum searching and transfer to this channel to continue communication, when the presence of the PU is detected. An optimization problem is proposed to maximize the SU's throughput in the proposed scheme through jointly optimizing the sensing time, the searching time and the number of available channels, providing that the detection probability to the PU is guaranteed. By fixing the number of channels, based on alternating direction optimization, the joint optimization algorithm of sensing time and searching time is proposed, and then the optimal number of channels is obtained through enumerative searching. The simulation results how that there exist the optimal solutions to the proposed scheme, and the proposed scheme outperforms the conventional scheme notably, with different detection probabilities and sampling frequencies.

Channel Selection for Spectrum Sharing in Wireless Networks

In this paper, we study a spectrum sharing network (SSN) where a spectrum sharing device (SSD) coexists with multiple wireless communication systems (WCSs) in the same channel. The SSD can operate with either a duty cycle (DC) channel access mechanism or a listen-before-talk (LBT) channel access mechanism, whereas WCSs operate with an LBT mechanism. An opportunistic channel selection scheme for the SSD in the SSN is first proposed to minimize the outage probability. The optimal data transmission time for the DC-based SSD is derived to further improve the outage probability. We also derive the exact and closed-form outage probability of the proposed channel selection in the SSN by assuming that the number of WCSs operating in each channel is uniformly distributed. The simulation results show that the proposed channel selection scheme outperforms other channel selection schemes. It was also observed that a DC-based SSD with an optimal data transmission time provides a better outage performance than an LBT-based SSD. As the number of available channels increases, the channel selection scheme plays an important role in minimizing the outage probability of the SSNs.

Spectrum allocation and protocol based on cognitive acoustic technique in underwater networks

In this paper, a strategy is developed for spectrum sharing among multiple cognitive users in underwater environment. This strategy requires all nodes to negotiate and reallocate the channels before sending data, and Hungarian method is used to maximize the sharing rewards. Simulation results show that the proposed strategy can avoid collisions between source-destination node pairs, and guarantee that the communication system gets maximum sharing rewards. Both the parameters of POMDP model and the number of available channels have influence on the system sharing rewards, and the rewards will increase when the channels have larger transition probabilities or more channels are available for communication. However, the channels with larger bandwidths can attract more nodes to access, and thus will lead to more collisions.

Optimal Cooperative Spectrum Aware Opportunistic Routing in Cognitive Radio Ad Hoc Networks

Opportunistic cognitive routing coupled with dual-stage collaborative spectrum sensing in multi-channel multi-hop cognitive radio ad hoc networks (CRAHNs) is investigated in this work. Due to the dynamics of available spectrum and complex radio environment in CRAHNs, an opportunistic cognitive routing protocol is proposed, that exploits a dual-stage collaborative spectrum sensing (DCSS) scheme to improve spectrum availability under the effects of Primary Users' activities. Solutions to select the optimal routing path were provided by adopting the proposed two routing metrics with routing access opportunity and routing transmission delay. The expressions in terms of the proposed two routing metrics are analytically derived and validated. Performance evaluation is conducted through simulations, and simulation results reveal that routing access opportunity and expected transmission delay are improved by using the proposed DCSS scheme, compared with those using the single cooperative spectrum sensing scheme and non-cooperation sensing scheme. In addition, it is observed that the number of next hop neighboring nodes, the number of available channels, and hop counts also affect the routing establishment and expected transmission delay.

Pliable Cognitive MAC for Heterogeneous Adaptive Cognitive Radio Sensor Networks.

The rapid expansion of wireless monitoring and surveillance applications in several domains reinforces the trend of exploiting emerging technologies such as the cognitive radio. However, these technologies have to adjust their working concepts to consider the common characteristics of conventional wireless sensor networks (WSNs). The cognitive radio sensor network (CRSN), still an immature technology, has to deal with new networks that might have different types of data, traffic patterns, or quality of service (QoS) requirements. In this paper, we design and model a new cognitive radio-based medium access control (MAC) algorithm dealing with the heterogeneous nature of the developed networks in terms of either the traffic pattern or the required QoS for the node applications. The proposed algorithm decreases the consumed power on several fronts, provides satisfactory levels of latency and spectrum utilization with efficient scheduling, and manages the radio resources for various traffic conditions. An intensive performance evaluation is conducted to study the impact of key parameters such as the channel idle time length, node density, and the number of available channels. The performance evaluation of the proposed algorithm shows a better performance than the comparable protocols. Moreover, the results manifest that the proposed algorithm is suitable for real time monitoring applications.

Impact of User Identities and Access Conditions on Downlink Performance in Closed Small-Cell Networks

This paper investigates the effect of various operation parameters on the downlink user performance in overlaid small-cell networks. The case study considers closed-access small cells (e.g., femtocells), wherein only active authorized user equipment (UE) can be served, each of which is allocated a single downlink channel at a time. On the other hand, the macrocell base station can unconditionally serve macrocell UEs that exist inside its coverage space. The available channels can be shared simultaneously in the macrocell network and the femtocell network. Moreover, a channel can be reused only at the macrocell base station. The analysis provides quantitative approaches to model UE identities, their likelihoods of being active, and their likelihoods of producing interference, considering UE classifications, locations, and access capabilities. Moreover, it develops models for various interference sources observed from effective interference femtocells, considering femtocells capacities and operation conditions. The associated formulations to describe a desired UE performance and the impact of the number of available channels and the adopted channel assignment approach are thoroughly investigated. The results are generally presented for any channel models of interference sources and the desired source of the served UE. Moreover, specific channel models are then adopted, for which generalized closed-form analytical results for the desired UE outage probability performance are obtained. Numerical and simulation results are presented to further clarify the main outcomes of the developed analysis.

Efficient Multichannel Communications in Wireless Sensor Networks

This article demonstrates how to use multiple channels to improve communication performance in Wireless Sensor Networks (WSNs). We first investigate multichannel realities in WSNs through intensive empirical experiments with Micaz motes. Our study shows that current multichannel protocols are not suitable for WSNs because of the small number of available channels and unavoidable time errors found in real networks. With these observations, we propose a novel tree-based, multichannel scheme for data collection applications, which allocates channels to disjoint trees and exploits parallel transmissions among trees. In order to minimize interference within trees, we define a new channel assignment problem that is proven NP-complete. Then, we propose a greedy channel allocation algorithm that outperforms other schemes in dense networks with a small number of channels. We implement our protocol, called the Tree-based, Multichannel Protocol (TMCP), in a real testbed. To adjust to networks with link quality heterogeneity, an extension of TMCP is also proposed. Through both simulation and real experiments, we show that TMCP can significantly improve network throughput and reduce packet losses. More important, evaluation results show that TMCP better accommodates multichannel realities found in WSNs than other multichannel protocols.

The impact of DTT in the willingness to pay for TV in Spain

Abstract The analogue switchover took place in Spain in April 2010, with the subsequent increase in the number of available channels for the citizens. New suppliers of audio-visual contents have appeared and a mixture of pay-services and free ones are competing. The aim of this article is to analyse the influence of socio-demographic variables in the subscription to television services before and after the full implementation of digital terrestrial television. Moreover, we will explore the possible relations between socio-demographic variables and reasons to subscribe. The theoretical framework is based on the nature of pay television as a media product and the audience satisfaction and willingness to pay for television. In order to contextualize the Spanish market in a broader international perspective, we provide some comparative aspects of the digital television developments in other European countries. The data for the empirical analysis of the willingness to pay for television contents in Spain come from two original surveys conducted in 2008 and 2012 and the sample size was 1000 individuals.

Cache-Filter: A Cache Permission Policy for Information-Centric Networking

Wireless mesh networks (WMNs) based on IEEE 802.11s have emerged as one of the prominent technologies in multi-hop communications. However, the deployment of WMNs suffers from serious interference problem which severely limits the system capacity. Using multiple radios for each mesh router over multiple channels, the interference can be reduced and improve system capacity. Nevertheless, interference cannot be completely eliminated due to the limited number of available channels. An effective approach to mitigate interference is to apply dynamic channel switching (DCS) in WMNs. Conventional DCS schemes trigger channel switching if interference is detected or exceeds a predefined threshold which might cause unnecessary channel switching and long protocol overheads. In this paper, a P-learning based dynamic switching algorithm known as learning automaton (LA)-based DCS algorithm is proposed. Initially, an optimal channel for communicating node pairs is determined through the learning process. Then, a novel switching metric is introduced in our LA-based DCS algorithm to avoid unnecessary initialization of channel switching. Hence, the proposed LA-based DCS algorithm enables each pair of communicating mesh nodes to communicate over the least loaded channels and consequently improve network performance.

Teletraffic and Blocking Probability Estimation of OFDMA System

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.

An Efficient Cooperative Neighbor Discovery Framework of Cognitive Radio Ad-Hoc Networks for Future Internet of Things

In the paper, an efficient cooperative neighbor discovery framework for cognitive radio ad-hoc networks (CRAHNs) is proposed for future internet of things. Unlike classical ad-hoc networks, users in a CRAHN do not have a pre-allocated set of channels or common control channel (CCC), which makes the situation much more complicated in neighbor discovery. The proposed framework addresses these issues in the absence of a central controller and a CCC, and can discover a large number of neighbors within a limited time. The absence of a CCC necessitates channel hopping to search for new neighbors, which can be time-consuming with a large number of available channels. In the proposed scheme, a node expedites the rate of neighbor discovery by choosing only a subset of available channels for hopping and working in a group. In addition, while working in a group, the nodes are assigned disjoint sets of channels so that different nodes explore different channels at the same time to discover new neighbors. Simulation results show that the proposed scheme outperforms the random channel hopping scheme which takes whole available channel set to search for neighbors.

THE MODEL FOR ASSESSMENT THE RELIABILITY OF STRUCTURES IN VIRTUALIZED DATA CENTERS

In this paper has been proposed model of communication system with dynamic network topology in which the process of changing the topology graph over time is to create or break connections between components within a single physical server or between pairs of components that are located on different machines. An essential criterion is the availability of system performance connectivity graph at the time of transition from one state to another topological and fixed number of nodes. Analysis showed that virtual topological structure of such a cloud network will depend on the probability of failure in the middle of the road segment. The probability of blocking close to zero when the number of available channels is 20-30% of the total subscribers

Fuzzy call admission control combined with distributed dynamic channel assignment and reassignment for cellular mobile systems

In a cellular mobile system (CMS), the service area is divided into cells, each of which has numerous channels, which are shared by two types of call - new calls and handoff calls. Giving a higher priority to handoff calls than new calls is common practice. However, giving too much priority to handoff calls will result to excessive blocking of new calls. This work firstly proposes a distributed dynamic channel assignment and reassignment (DDCAR) scheme to satisfy three types of constraint - co-channel constraint (CCC), adjacent channel constraint (ACC), and co-site constraint (CSC), simultaneously. The purpose is to minimize the number of available channels that become unavailable for the assignment to new calls and to maximize the number of unavailable channels that become available for release when calls complete. To provide a higher priority to handoff calls, a fuzzy call admission control (FCAC) scheme, combined with the DDCAR, is proposed herein for implementation at the base station. A 7 × 7 CMS with two traffic patterns is employed as the test example. The test results reveal that the FCAC scheme significantly reduces the dropping probability of handoff calls at the cost of increasing the blocking probability of new calls to an acceptable level.

Exploiting Multiple Channels for Low Latency and Semireliable Broadcasting in Cognitive Wireless Sensor Networks

In Wireless Sensor Networks (WSNs), disaster management is a crucial issue that focuses on disaster relief and recovery. Mobile sensor nodes support disaster relief and recovery by means of real-time bidirectional communication. For its high data rate requirement, IEEE 802.11 specification can be used for the radio interface of sensor nodes, and the nodes can be equipped with multiple 802.11 radios to utilize multiple channels and link data rates. Channel assignment algorithms can be applied in cognitive radio enabled networks which performs dynamic channel configuration for utilizing multiple channels. For efficient and semireliable broadcast in cognitive radio WSNs, we focus on reducing broadcast latency and achieving 100% delivery percentage. To realize these goals, in this study, we present our design for a novelChannel Assignment Algorithm for a Collision-Reduced Broadcast Tree(CA-CBT). Fundamentally, CA-CBT builds a broadcast tree and then uses several heuristic procedures to allocate collision-free channels to links on the tree. If CA-CBT fails to allocate collision-free channels due to a limited number of available channels, it allocates non-collision-free channels with the smallest number of interfering nodes. Through extensive simulations, we demonstrated that CA-CBT supports lower broadcast latency and higher delivery percentages compared with existing broadcast algorithms.