Adaptive Optimal Capacity Perception and Control for Wireless Multi-Hop Networks

In wireless multimedia communications, it is extremely difficult to derive general end-to-end capacity results because of decentralized packet scheduling and the interference between communicating nodes. In this paper, we present a state-based channel capacity perception scheme to provide statistical Quality-of-Service (QoS) guarantees under a medium or high traffic load for IEEE 802.11 wireless multi-hop networks. The proposed scheme first perceives the state of the wireless link from the MAC retransmission information and extends this information to calculate the wireless channel capacity, particularly under a saturated traffic load, on the basis of the interference among flows and the link state in the wireless multi-hop networks. Finally, the adaptive optimal control algorithm allocates a network resource and forwards the data packet by taking into consideration the channel capacity deployments in multi-terminal or multi-hop mesh networks. Extensive computer simulations demonstrate that the proposed scheme can achieve better performance in terms of packet delivery ratio and network throughput compared to the existing capacity prediction schemes.

Distributed link scheduling method with physical interference model in wireless multi-hop networks

To further increase the throughput of wireless multi-hop networks,a distributed scheduling method is proposed,which takes physical interference model into account.It is assumed that nodes in the network can perform physical carrier sensing,and the carrier sensing range can be set to different values.In the traditional carrier sensing mechanism,the carrier sensing range is computed under the protocol interference model,which is not accurate.Here the optimal carrier sensing range with physical interference model is achieved.Each sending node implements the distributed approach in three phases at each time slot,and all the concurrent transmissions are interference free.Good performance can be achieved under this scheduling approach.The approximation ratio of the distributed method to the optimal one is also proved.

Reclaiming the Efficiency of Opportunistic Routing in Wireless Multi-Hop Networks

Opportunistic routing(OR) is an effective way to guarantee transmission reliability in wireless multi-hop networks.However,little research focuses on transmission efficiency.Thus,an analytical model based on open queuing network with Markov chains was proposed to evaluate the efficiency.By analyzing two typical ORs,we find duplicate transmission and collision avoidance overhead are the root reasons behind inefficiency.Therefore,a new scheme called dual priority cooperative opportunistic routing(DPCOR) was proposed.In DPCOR,forwarding candidates are configured with dual priority,which enables the network to classify forwarding candidates more effectively so as to reduce the back-off time and obtain more diversity gain.Theoretical analysis and simulation results show DPCOR achieves significant performance improvement with less time overhead compared with traditional routings and typical ORs.

Cooperative Relay Selection Mechanism in Multi-Hop Networks

In this paper, we consider a three-hop relay system based on interference cancellation technique in Underlay cognitive radio (CR) network. Although underlay CR has been shown as a promising technique to better utilize the source of primary users (PUs), its secondary performance will be severely degraded. On one hand, by adapting the Underlay spectrum sharing pattern, secondary users (SUs) would observe the strict power constraints and be interfered by primary users. On the other hand, limited transmit power results in limited transmission range, which greatly degrade the secondary transmission capacity. To solve the problems above, we propose an interference cancellation protocol for multi-hop wireless communication networks in underlay CR, which could develop the long-distance transmission performance and improve the transmission efficiency significantly. As simulation results shows, proposed scheme significantly reduce the secondary outage probability and increase the secondary diversity than the traditional cases.

Application of virtual reality technology improves the functionality of brain networks in individuals experiencing pain

Medical procedures are inherently invasive and carry the risk of inducing pain to the mind and body.Recently,efforts have been made to alleviate the discomfort associated with invasive medical procedures through the use of virtual reality(VR)technology.VR has been demonstrated to be an effective treatment for pain associated with medical procedures,as well as for chronic pain conditions for which no effective treatment has been established.The precise mechanism by which the diversion from reality facilitated by VR contributes to the diminution of pain and anxiety has yet to be elucidated.However,the provision of positive images through VR-based visual stimulation may enhance the functionality of brain networks.The salience network is diminished,while the default mode network is enhanced.Additionally,the medial prefrontal cortex may establish a stronger connection with the default mode network,which could result in a reduction of pain and anxiety.Further research into the potential of VR technology to alleviate pain could lead to a reduction in the number of individuals who overdose on painkillers and contribute to positive change in the medical field.

Unlocking the future:Mitochondrial genes and neural networks in predicting ovarian cancer prognosis and immunotherapy response

BACKGROUND Mitochondrial genes are involved in tumor metabolism in ovarian cancer(OC)and affect immune cell infiltration and treatment responses.AIM To predict prognosis and immunotherapy response in patients diagnosed with OC using mitochondrial genes and neural networks.METHODS Prognosis,immunotherapy efficacy,and next-generation sequencing data of patients with OC were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus.Mitochondrial genes were sourced from the MitoCarta3.0 database.The discovery cohort for model construction was created from 70% of the patients,whereas the remaining 30% constituted the validation cohort.Using the expression of mitochondrial genes as the predictor variable and based on neural network algorithm,the overall survival time and immunotherapy efficacy(complete or partial response)of patients were predicted.RESULTS In total,375 patients with OC were included to construct the prognostic model,and 26 patients were included to construct the immune efficacy model.The average area under the receiver operating characteristic curve of the prognostic model was 0.7268[95% confidence interval(CI):0.7258-0.7278]in the discovery cohort and 0.6475(95%CI:0.6466-0.6484)in the validation cohort.The average area under the receiver operating characteristic curve of the immunotherapy efficacy model was 0.9444(95%CI:0.8333-1.0000)in the discovery cohort and 0.9167(95%CI:0.6667-1.0000)in the validation cohort.CONCLUSION The application of mitochondrial genes and neural networks has the potential to predict prognosis and immunotherapy response in patients with OC,providing valuable insights into personalized treatment strategies.

Resting-state brain network remodeling after different nerve reconstruction surgeries:a functional magnetic resonance imaging study in brachial plexus injury rats

Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected limb.However,differences among reconstruction strategies at the brain network level have not been elucidated.This study aimed to explore intranetwork changes related to altered peripheral neural pathways after different nerve reconstruction surgeries,including nerve repair,endto-end nerve transfer,and end-to-side nerve transfer.Sprague–Dawley rats underwent complete left brachial plexus transection and were divided into four equal groups of eight:no nerve repair,grafted nerve repair,phrenic nerve end-to-end transfer,and end-to-side transfer with a graft sutured to the anterior upper trunk.Resting-state brain functional magnetic resonance imaging was obtained 7 months after surgery.The independent component analysis algorithm was utilized to identify group-level network components of interest and extract resting-state functional connectivity values of each voxel within the component.Alterations in intra-network resting-state functional connectivity were compared among the groups.Target muscle reinnervation was assessed by behavioral observation(elbow flexion)and electromyography.The results showed that alterations in the sensorimotor and interoception networks were mostly related to changes in the peripheral neural pathway.Nerve repair was related to enhanced connectivity within the sensorimotor network,while end-to-side nerve transfer might be more beneficial for restoring control over the affected limb by the original motor representation.The thalamic-cortical pathway was enhanced within the interoception network after nerve repair and end-to-end nerve transfer.Brain areas related to cognition and emotion were enhanced after end-to-side nerve transfer.Our study revealed important brain networks related to different nerve reconstructions.These networks may be potential targets for enhancing motor recovery.

Cross-layer resource allocation in wireless multi-hop networks with outdated channel state information

The cross-layer resource allocation problem in wireless multi-hop networks(WMHNs)has been extensively studied in the past few years.Most of these studies assume that every node has the perfect channel state information(CSI)of other nodes.In practical settings,however,the networks are generally dynamic and CSI usually becomes outdated when it is used,due to the time-variant channel and feedback delay.To deal with this issue,we study the cross-layer resource allocation problem in dynamic WMHNs with outdated CSI under channel conditions where there is correlation between the outdated CSI and current CSI.Two major contributions are made in this work:(1)a closed-form expression of conditional average capacity is derived under the signal-to-interferenceplus-noise ratio(SINR)model;(2)a joint optimization problem of congestion control,power control,and channel allocation in the context of outdated CSI is formulated and solved in both centralized and distributed manners.Simulation results show that the network utility can be improved significantly using our proposed algorithm.

Physical Layer Security of Multi-hop Aided Downlink MIMO heterogeneous Cellular Networks

This study investigates physical layer security in downlink multipleinput multiple-output(MIMO) multi-hop heterogeneous cellular networks(MHCNs),in which communication between mobile users and base stations(BSs) is established by a single or multiple hops,to address the problem of insufficient security performance of MIMO heterogeneous cellular networks.First,two-dimensional homogeneous Poisson point processes(HPPPs) are utilized to model the locations of K-tier BSs in MIMO MHCNs and receivers,including those of legitimate users and eavesdroppers.Second,based on the channel gain distribution and the statistics property of HPPP,the achievable ergodic rates of the main and eavesdropper channels in direct and ad hoc links are derived,respectively.Third,the secrecy coverage probability and the achievable ergodic secrecy throughput of downlink MIMO MHCNs are explored,and their expressions are derived.Lastly,the correctness of the theoretical derivation is verified through Monte Carlo simulations.

Practical network coding-aware routing protocol for multi-hop wireless networks

Network coding has been considered as one of the effective strategies that improve the throughput of multi- hop wireless networks. In order to effectively apply network coding techniques to the real multi-hop wireless networks, a practical network coding aware routing protocol is proposed in this paper, for unicast sessions in multi- hop wireless networks. The protocol is based on a novel routing metric design that captures the characteristics of network coding and unicast sessions. To ensure the novel routing mettle can operate with practical and widely available path calculation algorithms, a unique mapping process is used to map a real wireless network to a virtual network. The mapping process ensures that the paths with the biggest coding opportunities will be selected by commonly used path calculation algorithms. Simulation results show that the proposed routing protocol is effective to improve the network throughput.

A Novel Multi-Hop Algorithm for Wireless Network with Unevenly Distributed Nodes

Node location estimation is not only the promise of the wireless network for target recognition,monitoring,tracking and many other applications,but also one of the hot topics in wireless network research.In this paper,the localization algorithm for wireless network with unevenly distributed nodes is discussed,and a novel multi-hop localization algorithm based on Elastic Net is proposed.The proposed approach is formulated as a regression problem,which is solved by Elastic Net.Unlike other previous localization approaches,the proposed approach overcomes the shortcomings of traditional approaches assume that nodes are distributed in regular areas without holes or obstacles,therefore has a strong adaptability to the complex deployment environment.The proposed approach consists of three steps:the data collection step,mapping model building step,and location estimation step.In the data collection step,training information among anchor nodes of the given network is collected.In mapping model building step,the mapping model among the hop-counts and the Euclidean distances between anchor nodes is constructed using Elastic Net.In location estimation step,each normal node finds its exact location in a distributed manner.Realistic scenario experiments and simulation experiments do exhibit the excellent and robust location estimation performance.

Load balancing strategy of heterogeneous wireless networks based on multi-hop routing algorithm of ad hoc network

Because of different system capacities of base station （BS） or access point （AP） and ununiformity of traffic distribution in different cells, quantities of new call users may be blocked in overloaded cell in communication hot spots. Whereas in some neighboring under-loaded cells, bandwidth may be superfluous because there are only few users to request services. In order to raise resource utilization of the whole heterogeneous networks, several novel load balancing strategies are proposed, which combine the call ad- mission control policy and multi-hop routing protocol of ad-hoc network for load balancing. These loadbalancing strategies firstly make a decision whether to admit a new call or not by considering some parameters like load index and route cost, etc., and then transfer the denied users into neighboring under-loaded cell with surplus channel according to optimum multi-hop routing algorithm. Simulation results show that the proposed load balancing strategies can distribute traffics to the whole heterogeneous wireless netorks, improve the load balance index efficiently, and avoid the call block phenomenon almost absolutely.

QMCR:A Q-Learning-Based Multi-Hop Cooperative Routing Protocol for Underwater Acoustic Sensor Networks

Routing plays a critical role in data transmission for underwater acoustic sensor networks(UWSNs)in the internet of underwater things(IoUT).Traditional routing methods suffer from high end-toend delay,limited bandwidth,and high energy consumption.With the development of artificial intelligence and machine learning algorithms,many researchers apply these new methods to improve the quality of routing.In this paper,we propose a Qlearning-based multi-hop cooperative routing protocol(QMCR)for UWSNs.Our protocol can automatically choose nodes with the maximum Q-value as forwarders based on distance information.Moreover,we combine cooperative communications with Q-learning algorithm to reduce network energy consumption and improve communication efficiency.Experimental results show that the running time of the QMCR is less than one-tenth of that of the artificial fish-swarm algorithm(AFSA),while the routing energy consumption is kept at the same level.Due to the extremely fast speed of the algorithm,the QMCR is a promising method of routing design for UWSNs,especially for the case that it suffers from the extreme dynamic underwater acoustic channels in the real ocean environment.

Radio resource management scheme and outage analysis for network- assisted multi-hop D2D communications

In a cellular network it＇s very difficult to make spectrum resource more efficiently. Device-to-Device （D2D） technology enables new service opportunities, and provides high throughput and reliable communication while reducing the base station load. For better total performance, short-range D2D links and cellular links share the same radio resource and the management of interference becomes a crucial task. Here we argue that single-hop D2D technology can be used to further improve cellular networks performance if the key D2D radio resource management algorithms are suitably extended to support multi-hop D2D communications. Aiming to establish a new paradigm for the analysis and design of multi-hop D2D communications, We propose a radio resource allocation for multi-hop D2D routes based on interference avoidance approach in LTE-A networks. On top of that, we investigate the outage probability of D2D communication. We first introduce a new definition of outage probability by considering the maximum distance to be allowable for single-hop transmission. Then we study and analyze the outage performance of a multi-hop D2D route. We derive the general dosed form expression of outage probability of the multi-hop D2D routes. The results demonstrate that the D2D radio, sharing the same resources as the cellular network, provide higher capacity compared to pure cellular communication where all the data is transmitted through the base station. They also demonstrate that the new method of calculation of D2D multi hop outage probability has better performance than classical method defined in the literature.

Incentive Schemes of Nodes for Ad Hoc and Multi-hop Cellular Networks

Nodes cooperation is a significant prerequisite for the realization of the relaying Ad Hoc.While with the development of multi-hop cellular networks, how to stimulate intermediate nodes to do the packet-forwarding deserves more concerning.At present research,the incentive schemes in pure Ad Hoc and multi-hop cellular networks are analyzed and compared to classify the strengths and drawbacks of each scheme.We explain in particular what the key issues are to implement incentive schemes for cooperation. Finally,an incentive scheme based on integration of reputation and charging systems is proposed not only to block the existence of selfish nodes,but to satisfy the rational requirement of nodes.

A distributed adaptive multi-hop certification authority schemefor mobile Ad Hoc networks

This paper theoretically analyzes a deficiency of the existing scheme, and proposes a distributed multi-hop certification authority scheme for mobile Ad Hoc networks. In our design, we distribute the certification authority functions through a threshold secret sharing mechanism, in which each node holds a secret share and multiple nodes jointly provide complete services. Certification authority is not limited in a local neighborhood but can be completed within multi-hop location. In addition, we replace broadcast by multicast to improve system performance and reduce communication overhead. This paper resolves some technical problems of ubiquitous certification authority services, and presents a wieldy multi-hop certification authority algorithm. Simulation results confirm the availability and effectiveness of our design.

Multiway Relay Based Framework for Network Coding in Multi-Hop WSNs

In today’s information technology(IT)world,the multi-hop wireless sensor networks(MHWSNs)are considered the building block for the Internet of Things(IoT)enabled communication systems for controlling everyday tasks of organizations and industry to provide quality of service(QoS)in a stipulated time slot to end-user over the Internet.Smart city(SC)is an example of one such application which can automate a group of civil services like automatic control of traffic lights,weather prediction,surveillance,etc.,in our daily life.These IoT-based networks with multi-hop communication and multiple sink nodes provide efficient communication in terms of performance parameters such as throughput,energy efficiency,and end-to-end delay,wherein low latency is considered a challenging issue in next-generation networks(NGN).This paper introduces a single and parallels stable server queuing model with amulti-class of packets and native and coded packet flowto illustrate the simple chain topology and complexmultiway relay(MWR)node with specific neighbor topology.Further,for improving data transmission capacity inMHWSNs,an analytical framework for packet transmission using network coding at the MWR node in the network layer with opportunistic listening is performed by considering bi-directional network flow at the MWR node.Finally,the accuracy of the proposed multi-server multi-class queuing model is evaluated with and without network coding at the network layer by transmitting data packets.The results of the proposed analytical framework are validated and proved effective by comparing these analytical results to simulation results.

Power-Effective in the Cell Sectorization Using Wide-Beam and Narrow-Beam for Multi-hop Relay Network

Multi-hop relay is a significant topic in the wireless communication and it is provisioned in the 802.16j standards.At present,the major research on multi-hop relay is focused on the capacity,coverage,coordination,throughput,etc.But in this paper,a new concept about power-effective was discussed.Then,two power-effective coverage extension methods using two sectorized cellular approaches were introduced,i.e.,the widebeam three sector cell(WBTC) and the narrow-beam three sector cell(NBTC).Under such topologies,the consumption of power and optimal numbers of base stations(BSs) and relay stations(RSs) with respect to various user traffic densities were investigated.Finally,it is found that the performance of WBTC is better than NBTC.

Joint channel allocation and power control with fairness in multi-hop cognitive radio networks

This paper investigates channel allocation and cognitive radio networks. The color-sensitive graph power control schemes in OFDM-based multi-hop coloring （CSGC） model is viewed as an efficient solution to the spectrum assignment problem. The model is extended to combine with the power con- trol strategy to avoid interference among secondary users and adapt dynamic topology. The optimiza- tion problem is formulated encompassing the channel allocation and power control with the interfer- ence constrained below a tolerable limit. Meanwhile, the proposed resource allocation scheme takes the fairness of secondary users into account in obtaining the solution of optimization. Numerical re- suits show that the proposed strategy outperforms the existing spectrum assignment algorithms on the performance of both the network throughput and minimum route bandwidth of all routes, as well as the number of connected multi-hop routes which implies the fairness among secondary users.

Energy-Efficient Sensing and Transmission for Multi-Hop Relay Cognitive Radio Sensor Networks

How to achieve transmissions in an energy-efficient way in multi-hop decode and forward(DF) relay cognitive radio sensor networks(CRSNs) is important since sensor nodes in CRSNs are usually battery powered. This paper aims to maximize energy efficiency(EE) by joint optimizing sensing time and power allocation in multi-channels & multihops DF relay CRSNs under constraints on outage probability and sensing performance. First, we design a channel selection scheme for sensing according to the available probabilities of multi channels. Second, we analyze the expected throughput and energy consumption and formulate the EE problem as a concave/concave fractional program. Third, coordinate ascent and Charnes-Cooper Transformation(CCT) methods are used to transform the nonlinear fractional problem into an equivalent concave problem. Subsequently, the closed form of outage probability is derived and the convergence rate of the iterative algorithm is analyzed. Finally, simulation results show that the proposed scheme can achieve effective EE.