Showing papers in "Eurasip Journal on Wireless Communications and Networking in 2013"

Coordinating transmit power and carrier phase for wireless networks with multi-packet reception capability

Abstract: Driven by advances in signal processing and multiuser detection (MUD) technologies, it has become possible for a wireless node to simultaneously receive multiple signals from other transmitters. In order to take full advantage of MUD in multi-packet reception (MPR) capable wireless networks, it is highly desirable to make the compound signals from multiple transmitters more separable on its constellation at the receiver by coordinating both the transmit power level and carrier phase offsets of the transmitters. In this article, we propose a feedback-based transmit power and carrier phase adjustment scheme that estimates the symbol energy and the carrier phase offset for each transmitter’s received signal, computes the optimal received power level and carrier phase shift to maximize the minimum Euclidean distance between the constellation points, and finally feeds the optimal transmit power level and phase shift information back to the transmitters. We then evaluate the performance of the proposed transmit power and carrier phase adjustment scheme and subsequently show that the proposed scheme significantly reduces the error probability in a multiuser communication system having MPR capability.

Intelligent feature selection and classification techniques for intrusion detection in networks: a survey

Abstract: Rapid growth in the Internet usage and diverse military applications have led researchers to think of intelligent systems that can assist the users and applications in getting the services by delivering required quality of service in networks. Some kinds of intelligent techniques are appropriate for providing security in communication pertaining to distributed environments such as mobile computing, e-commerce, telecommunication, and network management. In this paper, a survey on intelligent techniques for feature selection and classification for intrusion detection in networks based on intelligent software agents, neural networks, genetic algorithms, neuro-genetic algorithms, fuzzy techniques, rough sets, and particle swarm intelligence has been proposed. These techniques have been useful for effectively identifying and preventing network intrusions in order to provide security to the Internet and to enhance the quality of service. In addition to the survey on existing intelligent techniques for intrusion detection systems, two new algorithms namely intelligent rule-based attribute selection algorithm for effective feature selection and intelligent rule-based enhanced multiclass support vector machine have been proposed in this paper.

New indoor navigation system for visually impaired people using visible light communication

Abstract: In this study, we propose an indoor navigation system that utilizes visible light communication technology, which employs LED lights and a geomagnetic correction method, aimed at supporting visually impaired people who travel indoors. To verify the effectiveness of this system, we conducted an experiment targeting visually impaired people. Although acquiring accurate positional information and detecting directions indoors is difficult, we confirmed that using this system, accurate positional information and travel direction can be obtained utilizing visible light communication technology, which employs LED lights, and correcting the values of the geomagnetic sensor integrated in a smartphone.

Interference alignment for spectral coexistence of heterogeneous networks

Abstract: The coexistence of heterogeneous networks within the same spectrum for enhancing the spectrum efficiency has attracted large interest lately in the research community Furthermore, the research interest towards the deployment of small cells and multibeam satellites is increasing due to high capacity, easier deployment and higher energy efficiency However, due to the scarcity of available spectrum and the requirement of additional spectrum for these systems, small cells need to coexist with macrocells and multibeam satellites need to coexist with monobeam satellites within the same spectrum In this context, this contribution investigates an underlay spectral coexistence mechanism which exploits an interference alignment (IA) technique in order to mitigate the interference of cognitive transmitters towards the primary receivers in a normal uplink mode More specifically, three types of IA techniques, namely static, uncoordinated and coordinated are investigated The performance of the IA technique is evaluated and compared with primary only, resource division and no-mitigation techniques in terms of sum-rate capacity, primary to secondary rate ratio and primary rate protection ratio It is shown that the coordinated IA technique perfectly protects the primary rate in both terrestrial and satellite coexistence scenarios

Throughput analysis of buffer-constrained wireless systems in the finite blocklength regime

Abstract: In this paper, a single point-to-point wireless link operating under queueing constraints in the form of limitations on the buffer violation probabilities is considered. The achievable throughput under such constraints is captured by the effective capacity formulation. It is assumed that finite blocklength codes are employed for transmission. Under this assumption, a recent result on the channel coding rate in the finite blocklength regime is incorporated into the analysis, and the throughput achieved with such codes in the presence of queueing constraints and decoding errors is identified. The performance of different transmission strategies (e.g., variable-rate, variable-power, and fixed-rate transmissions) is studied. Interactions and tradeoffs between the throughput, queueing constraints, coding blocklength, decoding error probabilities, and signal-to-noise ratio are investigated, and several conclusions with important practical implications are drawn.

Improved least mean square algorithm with application to adaptive sparse channel estimation

Abstract: Least mean square (LMS)-based adaptive algorithms have attracted much attention due to their low computational complexity and reliable recovery capability. To exploit the channel sparsity, LMS-based adaptive sparse channel estimation methods have been proposed based on different sparse penalties, such as l1-norm LMS or zero-attracting LMS (ZA-LMS), reweighted ZA-LMS, and lp-norm LMS. However, the aforementioned methods cannot fully exploit channel sparse structure information. To fully take advantage of channel sparsity, in this paper, an improved sparse channel estimation method using l0-norm LMS algorithm is proposed. The LMS-type sparse channel estimation methods have a common drawback of sensitivity to the scaling of random training signal. Thus, it is very hard to choose a proper learning rate to achieve a robust estimation performance. To solve this problem, we propose several improved adaptive sparse channel estimation methods using normalized LMS algorithm with different sparse penalties, which normalizes the power of input signal. Furthermore, Cramer-Rao lower bound of the proposed adaptive sparse channel estimator is derived based on prior information of channel taps' positions. Computer simulation results demonstrate the advantage of the proposed channel estimation methods in mean square error performance.

Automatic ARIMA modeling-based data aggregation scheme in wireless sensor networks

Abstract: Data aggregation is a very important method to conserve energy by eliminating the inherent redundancy of raw data in wireless sensor networks (WSNs). In this article, we developed an automatic auto regressive-integrated moving averagemodeling-based data aggregation scheme in WSNs. The main idea behind this scheme is to decrease the number of transmitted data values between sensor nodes and aggregators by utilizing time series prediction model. The proposed scheme can effectively save the precious battery energy of wireless sensor nodes while keeping the predicted data values of aggregators within application-defined error threshold. We show through experiments with real data that the predicted data values of our proposed scheme fit the real sensed data values very well and fewer messages are transmitted between sensor nodes and aggregators than the native data aggregation scheme. Furthermore, the characteristics of the proposed data aggregation scheme are also discussed in this article.

Investigation of routing reliability of vehicular ad hoc networks

Abstract: In intelligent transportation systems, the cooperation between vehicles and the road side units is essential to bring these systems to fruition. Vehicular ad hoc networks (VANETs) are a promising technology to enable the communications among vehicles on one hand and between vehicles and road side units on the other hand. However, it is a challenging task to develop a reliable routing algorithm for VANETs due to the high mobility and the frequent changes of the network topology. Communication links are highly vulnerable to disconnection in VANETs; hence, the routing reliability of these ever-changing networks needs to be paid special attention. In this paper, we propose a new vehicular reliability model to facilitate the reliable routing in VANETs. The link reliability is defined as the probability that a direct communication link between two vehicles will stay continuously available over a specified time period. Furthermore, the link reliability value is accurately calculated using the location, direction and velocity information of vehicles along the road. We extend the well-known ad hoc on-demand distance vector (AODV) routing protocol to propose our reliable routing protocol AODV-R. Simulation results demonstrate that AODV-R outperforms significantly the AODV routing protocol in terms of better delivery ratio and less link failures while maintaining a reasonable routing control overhead.

Handover management in high-dense femtocellular networks

Abstract: Femtocell technology is envisioned to be widely deployed in subscribers’ homes to provide high data rate communications with quality of service. Dense deployment of femtocells will offload large amounts of traffic from the macrocellular network to the femtocellular network by the successful integration of macrocellular and femtocellular networks. Efficient handling of handover calls is the key for successful femtocell/macrocell integration. For dense femtocells, intelligent integrated femtocell/macrocell network architecture, a neighbor cell list with a minimum number of femtocells, effective call admission control (CAC), and handover processes with proper signaling are the open research issues. An appropriate traffic model for the integrated femtocell/macrocell network is also not yet developed. In this article, we present the major issues of mobility management for the integrated femtocell/macrocell network. We propose a novel algorithm to create a neighbor cell list with a minimum, but appropriate, number of cells for handover. We also propose detailed handover procedures and a novel traffic model for the integrated femtocell/macrocell network. The proposed CAC effectively handles various calls. The numerical and simulation results show the importance of the integrated femtocell/macrocell network and the performance improvement of the proposed schemes. Our proposed schemes for dense femtocells will be very effective for those in research and industry to implement.

Energy-efficient cluster-based security mechanism for intra-WBAN and inter-WBAN communications for healthcare applications

Abstract: Wireless body area networks (WBANs) are formed by using tiny health monitoring sensors on the human body in order to collect and communicate the human personal data. WBANs serve as a solution to facilitate the tasks performed in the medical sector, and minimize the chances of errors during the process of medical diagnosis. Due to the unreliable wireless media, the communication in a WBAN is exposed to a variety of attacks. These attacks pose major threats to WBAN security. In order to overcome these threats, several cryptographic techniques have been proposed in the recent past. Effectiveness of these cryptographic techniques largely depends on a good key management scheme. However, using an expensive key management scheme is not feasible in highly resource-constrained WBANs. Therefore, we propose and evaluate an energy-efficient key management scheme for WBANs that takes into account available resources of a node during the whole life cycle of key management. Our proposed scheme is a cluster-based hybrid security framework that supports both intra-WBAN and inter-WBAN communications. By using multiple clusters, energy-efficiency can be ensured. The cluster formation process itself is secured by using electrocardiogram (EKG)-based key agreement scheme. The proposed technique is hybrid because we use both preloading of keys and physiological value-based generated keys. We use highly dynamic and random EKG values of the human body for pairwise key generation and refreshment. The performance comparison of our proposed cluster-based key management scheme and low-energy adaptive clustering hierarchy (LEACH)-based key agreement scheme shows that the proposed scheme is secure, more energy-efficient, and provides better network lifetime.

Detection of jamming attacks in 802.11b wireless networks

Abstract: The work in this paper is about to detect and classify jamming attacks in 802.11b wireless networks. The number of jamming detection and classification techniques has been proposed in the literature. Majority of them model individual parameters like signal strength, carrier sensing time, and packet delivery ratio to detect the presence of a jammer and to classify the jamming attacks. The demonstrated results by the authors are often overlapping as most of the jamming regions are closely marked, and they do not help to clearly distinguish different jamming mechanisms. We investigate a multi-modal scheme that models different jamming attacks by discovering the correlation between three parameters: packet delivery ratio, signal strength variation, and pulse width of the received signal. Based on that, profiles are generated in normal scenarios during training sessions which are then compared with test sessions to detect and classify jamming attacks. Our proposed model helps in clearly differentiating the jammed regions for various types of jamming attacks. In addition, it is equally effective for both the protocol-aware and protocol-unaware jammers. The reported results are not based on simulations, but a test-bed was established to experiment real scenarios demonstrating significant enhancements in previous results reported in the literature.

Cell range expansion using distributed Q -learning in heterogeneous networks

Abstract: Cell range expansion (CRE) is a technique to expand a pico cell range virtually by adding a bias value to the pico received power, instead of increasing transmit power of pico base station (PBS), so that coverage, cell-edge throughput, and overall network throughput are improved. Many studies have focused on inter-cell interference coordination (ICIC) in CRE, because macro base station’s (MBS’s) strong transmit power harms the expanded region (ER) user equipments (UEs) that select PBSs by bias value. Optimal bias value that minimizes the number of outage UEs depends on several factors such as the dividing ratio of radio resources between MBSs and PBSs. In addition it varies from UE to another. Thus, most articles use the common bias value among all UEs determined by trial-and-error method. In this article, we propose a scheme to determine the bias value of each UE by using Q-learning algorithm where each UE learns its bias value that minimizes the number of outage UEs from its past experience independently. Simulation results show that, compared to the scheme using optimal common bias value, the proposed scheme reduces the number of outage UEs and improves network throughput.

Modern smart device-based concept of sensoric networks

Abstract: The modern society evolves into a sensorial network environment where individual sensor data can be transformed into cumulative and comprehensive representation for human. In a real time, it is independent of current location or behavior. The only limits to increase productivity and to create a smarter surrounding environment are personal habits and technology progress. The paper describes sensorial framework, which is dealing with the current aspects of technology, sociology, and usability in daily life usage of ubiquitous mobile devices with sensors, and arising computed and energy power. Nowadays, most of the common tasks of our lives are mainly influenced by network and social connectivity where infrastructural speed limits are provided by the information flow.

Joint source-channel coding and optimization for mobile video streaming in heterogeneous wireless networks

Abstract: This paper investigates mobile video delivery in a heterogeneous wireless network from a video server to a multi-homed client. Joint source-channel coding (JSCC) has proven to be an effective solution for video transmission over bandwidth-limited, error-prone wireless networks. However, one major problem with the existing JSCC approaches is that they consider the network between the server and the client as a single transport link. The situation becomes more complicated in the context of multiple available links because involving a low-bandwidth, highly lossy, or long-delay wireless network in the transmission will only degrade the video quality. To address the critical problem, we propose a novel flow rate allocation-based JSCC (FRA-JSCC) approach that includes three key phases: (1) forward error correction redundancy estimation under loss requirement, (2) source rate adaption under delay constraint, and (3) dynamic rate allocation to minimize end-to-end video distortion. We present a mathematical formulation of JSCC to optimize video quality over multiple wireless channels and provide comprehensive analysis for channel distortion. We evaluate the performance of FRA-JSCC through emulations in Exata and compare it with the existing schemes. Experimental results show that FRA-JSCC outperforms the competing models in improving the video peak signal-to-noise ratio as well as in reducing the end-to-end delay.

I3S: Intelligent spectrum sensing scheme for cognitive radio networks

Abstract: Reliable spectrum sensing is one of the most crucial aspects for the successful deployment of cognitive radio (CR) technology. For CR, it is not possible to transmit on a licensed band and sense it simultaneously, therefore sensing must be interleaved with transmission. Spectrum sensing in CR is challenged by a number of uncertainties, which degrade the sensing performance and in turn require much more time to achieve the targeted sensing efficiency. Hence, the authors propose a spectrum sensing scheme which obtains reliable results with less mean detection time. First, the scheme determines a better matched filter, or a combination of energy and cyclostationary detectors based on the power and band of interest. In the combined energy and cyclostationary detector, an energy detector with a bi-threshold is used, and the cyclostationary detector is applied only if the energy of the signal lies between two thresholds. Second, sensing is performed by the selection choice resulting from the first step. To evaluate the scheme’s performance, the results are compared with those where only an energy detector, matched filter, or cyclostationary detector are performed. The performance metrics are the probability of detection, probability of false alarm, and mean detection time.

A cluster-based selective cooperative spectrum sensing scheme in cognitive radio

Abstract: Developing an effective cooperative spectrum sensing (CSS) scheme in cognitive radio (CR), which is considered as promising system for enhancing spectrum utilization, is necessary. In this paper, a cluster-based optimal selective CSS scheme is proposed for reducing reporting time and bandwidth while maintaining a certain level of sensing performance. Clusters are organized based on the identification of primary signal signal-to-noise ratio value, and the cluster head in each cluster is dynamically chosen according to the sensing data qualities of CR users. The cluster sensing decision is made based on an optimal threshold for selective CSS which minimizes the probability of sensing error. A parallel reporting mechanism based on frequency division is proposed to considerably reduce the time for reporting decision to fusion center of clusters. In the fusion center, the optimal Chair-Vashney rule is utilized to obtain a high sensing performance based on the available cluster’s information.

Adaptive generalized space shift keying

Abstract: In this article, we propose a closed-loop precoding method for the Generalized Space Shift Keying (GSSK) modulation scheme, suitable for Multiple-Input-Single-Output (MISO) systems and denoted as adaptive GSSK (AGSSK), which achieves transmit-diversity gains in contrast to GSSK. For the case of a perfect feedback channel, we analytically show that for three and four antennas at the transmitter and rates 1 and 2 bits per channel use (bpcu), respectively, a full transmit-diversity can be achieved without reducing the achievable rate. For higher number of transmit antennas and rates, the performance of the proposed scheme degrades due to the smaller average minimum Euclidean distance as the rate increases. Due to this, we, furthermore, propose an enhancing method for AGSSK which relies on the use of time-orthogonal shaping filters for the different constellation points. For the enhanced method, named as AGSSK with time-orthogonal signal design (AGSSK-TOSD), we analytically prove that it offers transmit-diversity gains which are greater than the number of active transmit antennas for any number of transmit antennas and supported rate. This is attained without any antenna subset selection technique, which alleviates the processing burden on the terminal side. Monte Carlo simulations show that AGSSK significantly outperforms GSSK in terms of average bit error probability (ABEP) and, moreover, for medium to high rates and practical signal-to-noise ratio (SNR) regions AGSSK-TOSD outperforms well-known feedback-based multiple-antenna schemes. This advantage of AGSSK-TOSD is further substantiated with an energy effficiency comparison over the conventional schemes for a target (uncoded) ABEP.

A novel link switching scheme using pre-scanning and RSS prediction in visible light communication networks

Abstract: Visible light communication (VLC) is gaining increasing attention and is considered as a promising technology for future wireless indoor communications. Because movable users expect a seamless connectivity experience when switching among transmitters (i.e., VLC access points) in the VLC system, fast link switching operations must be supported by the networks. This paper presents a novel hard link switching scheme for VLC networks with the use of pre-scanning and received signal strength (RSS) prediction. Our proposed scheme achieves the advantages of both conventional hard and soft link switching schemes without changing device hardware or the IEEE 802.15.7 medium access control (MAC) protocol. To help compare our proposed scheme with conventional hard and soft link switching schemes, the signal-to-interference-plus-noise ratio (SINR), the outage probability regarding the link switching situation, and the queuing models for link switching schemes are taken into account. Simulation and numerical results validate that our proposed scheme outperforms conventional hard and soft link switching schemes.

A scalable data dissemination protocol for both highway and urban vehicular environments

Abstract: Vehicular ad hoc networks (VANETs) enable the timely broadcast dissemination of event-driven messages to interested vehicles. Especially when dealing with broadcast communication, data dissemination protocols must achieve a high degree of scalability due to frequent deviations in the network density. In dense networks, suppression techniques are designed to prevent the so-called broadcast storm problem. In sparse networks, protocols incorporate store-carry-forward mechanisms to take advantage of the mobility of vehicles to store and relay messages until a new opportunity for dissemination emerges. Despite numerous efforts, most related works focus on either highway or urban scenarios, but not both. Highways are mostly addressed with a single directional dissemination. For urban scenarios, protocols mostly concentrate on either using infrastructure or developing methods for selecting vehicles to perform the store-carry-forward task. In both cases, dense networks are dealt with suppression techniques that are not optimal for multi-directional dissemination. To fill this gap, we present an infrastructure-less protocol that combines a generalized time slot scheme based on directional sectors and a store-carry-forward algorithm to support multi-directional data dissemination. By means of simulations, we show that our protocol scales properly in various network densities in both realistic highway and urban scenarios. Most importantly, it outperforms state-of-the-art protocols in terms of delivery ratio, end-to-end delay, and number of transmissions. Compared to these solutions, our protocol presents up to seven times lower number of transmissions in dense highway scenarios.

Energy-efficient cooperative spectrum sensing schemes for cognitive radio networks

Abstract: Rapidly rising energy costs and increasingly rigid environmental standards have led to an emerging trend of addressing “energy efficiency” aspect of wireless communication technologies. Cognitive radio can play an important role in improving energy efficiency in wireless networks, because from the green perspective, spectrum is a natural resource which should not be wasted but be shared. In this article, we propose two energy-efficient and time-saving one-bit cooperative spectrum sensing schemes, which have two stages in the spectrum sensing process. If the signal-to-noise ratio is high or no primary user exists, only one stage of coarse spectrum sensing is needed, by which the sensing time and energy are saved. Otherwise, the second stage of fine spectrum sensing will be performed to increase the spectrum sensing accuracy. Furthermore, only one-bit decision is sent by each secondary user to minimize the overhead. The second proposed algorithm fully utilizes the local decisions of the coarse detection, and its energy consumption is further reduced with its sensing performance close to the first one. Plenty of simulation is performed, and the results show that the sensing time and energy consumption are both reduced significantly in the proposed schemes.

Facilitating the creation of IoT applications through conditional observations in CoAP

Abstract: With the advent of IPv6, the world is getting ready to incorporate smart objects to the current Internet to realize the idea of Internet of Things. The biggest challenge faced is the resource constraint of the smart objects to directly utilize the existing standard protocols and applications. A number of initiatives are currently witnessed to resolve this situation. One of such initiatives is the introduction of Constrained Application Protocol. This protocol is developed to fit in the resource-constrained smart object with the ability to easily translate to the prominent representational state transfer implementation, hypertext transfer protocol (and vice versa). The protocol has several optional extensions, one of them being, resource observation. With resource observation, a client may ask a server to be notified every state change of the resource. However, in many applications, all state changes are not significant enough for the clients. Therefore, the client will have to decide whether to use a value sent by a server or not. This results in wastage of the already constrained resources (bandwidth, processing power,…). In this paper, we introduced an alternative to the normal resource observation function, named Conditional Observation, where clients tell the servers the criteria for notification. We evaluated the power consumption and number of packets transmitted between clients and servers by using different network sizes and number of servers. In all cases, we found out that the existing observe option results in excessive number of packets (most of them unimportant for the client) and higher power consumption. We also made an extensive theoretical evaluation of the two approaches which give consistent result with the results we got from experimentation.

On-demand routing protocols for cognitive radio ad hoc networks

Abstract: Cognitive radio ad hoc networks (CRAHNs) are a class of cognitive radio networks. In recent years, they have gained popularity, and routing protocols have been proposed. Above all, the protocols based on on-demand routing are considered favorable in the literature. It is mainly because the accomplishments of ad hoc on-demand distance vector (AODV) routing and dynamic source routing (DSR) in mobile ad hoc networks have lead to a number of adaptations of both protocols to suit CRAHNs. In this paper, we review the on-demand routing protocols applicable for CRAHNs, which are based on AODV, DSR, and hybrid protocols. After explaining their basic principles, we qualitatively compare the protocols in terms of inherent characteristics and performance. This paper further addresses the pros and cons of routing protocols and discusses research challenges and open issues.

Simulation of impulse response for indoor visible light communications using 3D CAD models

Abstract: In this article, a tool for simulating the channel impulse response for indoor visible light communications using 3D computer-aided design (CAD) models is presented. The simulation tool is based on a previous Monte Carlo ray-tracing algorithm for indoor infrared channel estimation, but including wavelength response evaluation. The 3D scene, or the simulation environment, can be defined using any CAD software in which the user specifies, in addition to the setting geometry, the reflection characteristics of the surface materials as well as the structures of the emitters and receivers involved in the simulation. Also, in an effort to improve the computational efficiency, two optimizations are proposed. The first one consists of dividing the setting into cubic regions of equal size, which offers a calculation improvement of approximately 50% compared to not dividing the 3D scene into sub-regions. The second one involves the parallelization of the simulation algorithm, which provides a computational speed-up proportional to the number of processors used.

A real-time device-free localization system using correlated RSS measurements

Abstract: Device-free localization (DFL) with wireless sensor networks (WSN) is an emerging technology for target localization, which has received much attention in the area of Internet of Things. Received signal strength (RSS) measurements are the key to realize DFL and mainly affects the localization performance. Most existing approaches need to measure the RSS of all the wireless links in WSN, which take much time on measurement process and localization algorithm due to the large amounts of RSS data, thus they are inefficient, especially in the case of target tracking. In this paper, by making full use of the consecutiveness of motion, we present an efficient measurement strategy based on a small set of correlated wireless links. Furthermore, a lightweight compressed maximum matching select (CMMS) algorithm is proposed to localize target, which only needs a small-scale matrix-vector product operating for one estimation. The proposed approach can significantly reduce the number of RSS measurements and improve the real-time capability of the DFL system. Experimental results demonstrate the superior performance of the proposed method in the context of target localization and tracking.

Performance analysis of IEEE 802.11ac wireless backhaul networks in saturated conditions

Abstract: According to the ongoing IEEE 802.11ac amendment, the wireless network is about to embrace the gigabit-per-second raw data rate. Compared with previous IEEE standards, this significant performance improvement can be attributed to the novel physical and medium access control (MAC) features, such as multi-user multiple-input multiple-output transmissions, the frame aggregation, and the channel bonding. In this paper, we first briefly survey the main features of IEEE 802.11ac, and then, we evaluate these new features in a fully connected wireless mesh network using an analytic model and simulations. More specifically, the performance of the MAC scheme defined by IEEE 802.11ac, which employs the explicit compressed feedback (ECFB) mechanism for the channel sounding, is evaluated. In addition, we propose an extended request-to-send/clear-to-send scheme that integrates the ECFB operation to compare with the IEEE 802.11ac-defined one in saturated conditions. The comparison of the two MAC schemes is conducted through three spatial stream allocation algorithms. A simple but accurate analytical model is derived for the two MAC schemes, the results of which are validated with simulations. The observations of the results not only reveal the importance of spatial stream allocations but also provide insight into how the newly introduced features could affect the performance of IEEE 802.11ac-based wireless mesh networks.

A new mathematical analysis of the probability of detection in cognitive radio over fading channels

Abstract: Cognitive radio (CR) enriches wireless technology systems by harnessing spectrum white spaces. Such systems require continuous and reliable sensing to provide high-quality service to their users and to minimize the interference they may cause to legacy networks. As the simplicity of implementation of energy detectors and their incoherent requirements make them an ideal candidate for this type of application, this work provides a further mathematical analysis to the probability of detection over different fading channels. We derive a tight closed-form expression for the probability of detection over Nakagami channels. In addition, we introduce an accurate recursive algorithm to compute the probability of detection for an odd degree of freedom over additive white Gaussian noise channels, which has been overlooked in the literature so far. Finally, we present the simulation results which concur with the numerical results and which are also a perfect match with the mathematical expressions derived.

Security and quality of service (QoS) co-design in cooperative mobile ad hoc networks

Abstract: Cooperative communication has been considered as a promising technique to improve communication quality of service (QoS) in wireless networks, including mobile ad hoc networks (MANETs). Due to their unorganized and decentralized infrastructure, cooperative MANETs (CO-MANETs) are vulnerable to attacks initiated on relays. Although encryption and authentication protocols may prevent compromised data transmission when a selected relay is attacked, their cost is high. In this paper, we propose a game-theoretic approach to quantitatively analyze the attack strategies of the attacker so as to make a rational decision on relay selection and the authentication parameter adaptation to reach a trade-off between security and QoS in CO-MANETs. Simulation results show the effectiveness of the proposed approach for security and QoS co-design in CO-MANETs.

Fingerprint indoor positioning algorithm based on affinity propagation clustering

Abstract: Recently, the fingerprint-based wireless local area network (WLAN) positioning has gained significant interest. A probability distribution-aided indoor positioning algorithm based on the affinity propagation clustering is proposed. Different from the conventional fingerprint-based WLAN positioning algorithms, the paper first utilizes the affinity propagation clustering to minimize the searching space of reference points (RPs). Then, we introduce the probability distribution-aided positioning algorithm to obtain the target's refined position. Furthermore, because the affinity clustering can effectively lead to a reduction of the computational cost for the RP searching which is involved in the probability distribution-aided positioning algorithm, the proposed algorithm can lower the difficulty and minimize the power consumption when estimating the user's position. Experimental results conducted in the real environments show that our proposed algorithm will significantly improve the performance of the probability distribution-aided positioning algorithm in both the positioning accuracy and real-time ability.

Mobility robustness optimization in self-organizing LTE femtocell networks

Abstract: Femtocell is a promising solution for enhancing the indoor coverage and capacity in wireless networks. However, for the small size of femtocell and potentially frequent power on/off, existing handover schemes may not be reliable enough for femtocell networks. Moreover, improper handover parameters settings may lead to handover failures and unnecessary handovers, which make it necessary to enhance the mobility robustness for femtocells. In this article, we propose a gradient method and cost function-based mobility robustness optimization scheme for long term evolution (LTE) femtocell self-organizing networks. Moreover, signalling overhead of the scheme is analyzed. Simulation results show that the proposed scheme has a better performance than the fixed parameters method in terms of reduced the number of handover failures and unnecessary handovers with limited signalling modifications.

Low complexity subcarrier and power allocation algorithm for uplink OFDMA systems

Abstract: In this article, we consider the joint subcarrier and power allocation problem for uplink orthogonal frequency division multiple access system with the objective of weighted sum-rate maximization. Since the resource allocation problem is not convex due to the discrete nature of subcarrier allocation, the complexity of finding the optimal solution is extremely high. We use the optimality conditions for this problem to propose a suboptimal allocation algorithm. A simplified implementation of the proposed algorithm has been provided, which significantly reduced the algorithm complexity. Numerical results show that the presented algorithm outperforms the existing algorithms and achieves performance very close to the optimal solution.