Cross-modal communications that incorporate audio-visual and tactile signals will bring a more holistic immersive experience to people. However, due to the different transmission requirements of these signals, it is a challenging task to rationalize the allocation of transmission resources. Therefore, this work proposes a joint transmission scheme to deal with the resource allocation problem of diverse signals. Network slicing and puncturing architecture are introduced in the scheme to achieve flexible resource allocation and reduce the wasting of resources. To reduce the negative impact of puncturing transmission on users, we construct the optimization problem related to transmission rate and reliability. This problem can realize the reasonable allocation of radio resources and meet the transmission requirements of the two types of signals. Next, we divide the optimization problem into two parts: video traffic resources allocation and tactile traffic puncturing resources allocation. To solve both of the problems, we leverage the channel matching (CM) algorithm and puncturing resource allocation (PRA) algorithm. In addition, we discuss the advantages and disadvantages of both ways to occupy puncturing resources, namely, occupy resources proportionally (ORP) and occupy resources blocks for transmission (ORB). Finally, the effectiveness of the proposed scheme is verified by comparing the excepted rate and resources loss ratio of system users with different schemes.

This paper introduces a lightweight convolutional neural network, called FDDWNet, for real-time accurate semantic segmentation. In contrast to recent advances of lightweight networks that prefer to utilize shallow structure, FDDWNet makes an effort to design more deeper network architecture, while maintains faster inference speed and higher segmentation accuracy. Our network uses factorized dilated depth-wise separable convolutions (FDDWC) to learn feature representations from different scale receptive fields with fewer model parameters. Additionally, FDDWNet has multiple branches of skipped connections to gather context cues from intermediate convolution layers. The experiments show that FDDWNet only has 0.8M model size, while achieves 60 FPS running speed on a single RTX 2080Ti GPU with a 1024 × 512 input image. The comprehensive experiments demonstrate that our model achieves state-of-the-art results in terms of available speed and accuracy trade-off on CityScapes and CamVid datasets.

Simultaneous wireless information and power transfer (SWIPT) is a promising solution for future wireless networks as it provides convenient and perpetual energy supplies to wireless users. This study proposes three new transceiver design schemes in two‐way relay networks with SWIPT. Firstly, a transmit power minimisation solution is proposed with an aim to minimise the transmit power while meeting an energy harvesting requirement. Then, a harvested energy maximisation solution that has the same complexity as the first solution but provides a much better sum harvested energy is proposed. Finally, a signal‐to‐interference‐plus‐noise ratio maximisation solution is developed, which gives the best sum‐rate performance for the two‐way relay networks while ensuring a desired level of energy harvesting. Furthermore, the complexity of the three new transceiver solutions is discussed. Simulation results have demonstrated the effectiveness of the proposed transceiver design schemes in two‐way relay networks with SWIPT.

Mobile crowdsensing (MCS) has become a promising solution to support the location-based content sharing applications. To meet users' demand on personalized content sharing, a general region of interest (RoI) distribution model that allows each user to have its specific RoI needs to be considered. In this context, how to deal with the asymmetry of cooperation caused by different RoI distribution is of significance for achieving the full benefits of personalized content sharing. Thus motivated, we propose an intelligent content sharing scheme based on cooperative crowdsensing, which ensures both efficiency and fairness. Specifically, users' decision-making of whether to participate in MCS is cast as a MCS participation game (MPG). The game captures the impact of different RoI distributions on the collective cooperation of MCS. By computing the Nash equilibrium of MPG with desirable properties, we develop a cooperation scheme that maximizes the overall system utility and is acceptable to all users. The system efficiency of the proposed scheme is further quantified by numerical simulations over various parameters.

With extensive promising applications of M2M (machine-to-machine) or MTC (machine type communication), while supporting multiple MTC device access networks has been considered essential for M2M communication. In a roaming environment, it has always been a great challenge to ensure safe and efficient access for MTC device groups. In this paper, in order to solve the real-time secure and efficient access problem of multiple MTCs, we proposed a group authentication protocol based on bilinear-pairing and aggregate signature. In proposed protocol, node key is generated jointly by KGC (Key Generation Center) and node simultaneously to resist camouflage attack, and the computational complexity in authentication process is significantly ameliorated as the session key is engendered by DLP (Discrete Logarithm Problem). Security analysis shows the strong security of proposed protocol, and performance evaluation proves that both transmission overhead and computational complexity decrease significantly compared with conventional schemes. In addition, it overcomes the weakness of key escrow in identity based aggregate signature protocol.

This work explores the true user QoE according to the users' preferences and behaviors when the users know that they are being observed and concern about their privacy. We propose a systematic privacy-aware QoE evaluation scheme based on the observable user data. Firstly, we translate the subjective privacy- aware QoE evaluation problem into the objective rational user analysis procedure. Then, a novel class-level joint user classification and data cleaning strategy is proposed by frequently updating the training processes. In particular, an efficient correlation analysis and QoE model framework is constructed for online implementation. Our results reveal that the true user QoE can be precisely captured if only some conditions are satisfied even for the privacy-aware users.

To achieve the flexible and efficient transmission of files in the video on demand system, this paper proposed a three-tier fragmentation strategy which provided a unfiled method of fragmentation for video of HTTP Live Streaming and large file. In order to prove the rationality of the three-tier fragmentation strategy, we compared it with the two layers fragmentation strategy and the fragmentation strategy of equal time. And the comparisons proved the superiority of three-tier fragmentation strategy.

On the basis of studying the principle and application technology of P2P protocol, we design the private protocol of P2P application layer to meet the needs of P2P communication. This application layer protocol splits up video into three types of blocks in order to improve transmission efficiency. Besides, the protocol can be expanded when needed since there are some invalid bits in the state list.

Sparse adaptive filtering algorithms are utilized to exploit potential sparse structure information as well as to mitigate noises in many unknown sparse systems. Sparse recursive least square (RLS) algorithms have been attracted intensely attentions due to their low-complexity and easy- implementation. Basically, these algorithms are constructed by standard RLS algorithm and sparse penalty functions (e.g., l_1-norm). However, existing sparse RLS algorithms do not exploit the sparsity efficiently. In this paper, an improved adaptive filtering algorithm is proposed by incorporating a novel correntropy induced metric (CIM) constraint into RLS, which is termed as RLS- CIM algorithm. Specifically, we adopt a well-known Gaussian kernel in CIM and further devise a novel variable kernel width to control the sparse penalty in different transient-error scenarios. Numerical simulation results are given to corroborate the proposed algorithm via mean square deviation (MSD).

Abstract In low signal‐to‐noise ratio (SNR) cases, the performance of spectrum sensing algorithms cannot meet the practical needs, which is a major problem faced by spectrum sensing technology in current cognitive radio field. Now, existing algorithms based on random matrix theory (RMT) have high sensing performance, but they require a large number of samples, which are very difficult to satisfy in practice. Free probability theory (FPT) is a main branch of RMT. It describes the asymptotic behavior of large random matrices and portrays a strong link between two matrices and their sum or product matrices. FPT can also be utilized to the digital communication system that can be modeled by random matrices and has been applied to spectrum sensing in simplified ideal channels, for example, additive white Gaussian noise channel. The most pivotal issue and difficulty of the FPT‐based methods is to set up and solve the asymptotic freeness equation corresponding to a specific communication model. In this paper, FPT‐based spectrum sensing schemes are proposed for some typical wireless communication systems, such as multiple‐input multiple‐output system, Rayleigh multipath fading system, and orthogonal frequency division multiplexing system. It is shown that the asymptotic freeness behavior of random matrices and the property of Wishart distribution can be used to assist spectrum sensing for these typical systems with low SNR and very limited samples. Simulation results demonstrate that compared with the existing RMT‐based spectrum detection methods, for example, the maximum and minimum eigenvalue detectors, the proposed FPT‐based schemes offer superior detection performance and are more robust to low SNR cases, especially for a small sample of observations. Copyright © 2015 John Wiley & Sons, Ltd.

Recently, attracted by the abundant computation and networking resources in the cloud, an increased number of mobile media services have been hosted by the cloud computing platforms. These mobile media clouds (MMCs) run hundreds of thousands of servers and consume megawatts of power with massive carbon emission. Virtualization is adopted to allocate resources elastically from a shared resource pool. Therefore, effective virtual machine (VM) consolidation is of paramount importance to reduce energy consumption. We especially focus on applications with different resource (e.g., CPU, memory, network) demands. In this paper, we formulate this problem as a mixed integer linear programming (MILP) problem. We prove that the optimal energy efficiency can be obtained for a homogeneous cloud. Based on this analytical result, we develop an approximation algorithm for VM consolidation and placement which jointly considers CPU and network constraints. Through extensive simulations, we validate the effectiveness of the proposed algorithm.

In this paper, we investigate the secrecy outage probability (SOP) for the cooperative decode-and-forward (DF) underlay cognitive radio networks (CRNs). Duo to the spectrum sharing approach in underlay CRNs, the secondary transmitters (secondary source (SUS) and secondary relay (SUR)) are subjected to interference power constraint at primary user (PU), and the SU receivers (SURand secondary destination (SUD)) suffer from the co-channel interferences (CCIs) from PU. We focus on the practical scenario where the SU transmitter has no channel state information (CSI) of the eavesdropper's channel. Interference-power-confined selection scheme is proposed for the cooperative DF CRNs in the presence of an eavesdropper. The proposed scheme selects the “best” terminal (SUSor SUR) to enhance the secure performance which must firstly satisfy the interference power constraint. What's more, the effect of feedback delay on the selection scheme is studied. We derive an exact closed-form expression for the SOP. Simulation results validate our theoretical analysis and show that the proposed selection scheme determinately enhance the performance, and feedback delay decreases the SOP seriously, specially, the interference power constraint hugely confine the SOP.

Multiuser multiple‐input–multiple‐output (MIMO) has great potential to substantially improve throughput of wireless networks. Unfortunately, it requires a significant amount of feed back for user selection, which prevents practical implementation. The authors propose a feed back reduced downlink multiuser MIMO system, where a signal‐to‐interference‐plus‐noise ratio (SINR) threshold is carefully designed. Only the users whose SINRs are above the threshold feed back their SINRs and channel direction information (CDI) to the base station. They establish a monotonic relation between the threshold and the average feed back overhead. Based on the established relation, they design the threshold that balances the tradeoff between the feed back load and the sum rate. Simulation results show that the proposed approach can achieve the same performance as the conventional full‐feed back scheme (where every user feeds back its SINR and CDI), while the proposed approach is able to reduce the system overhead by more than 40%.

Traditional distributed flow scheduling for wireless body sensor networks (WBSNs) is designed based on perfect control channels where the instantaneous control information from the neighbors is available. However, in practice it is very difficult, sometimes even impossible, to obtain this information especially for dynamic WBSNs. This motivates us in this paper to study the distributed flow scheduling with heterogeneous delayed control information (DCI). First, we translate this scheduling problem into a stochastic optimization problem that opens up a new methodology to exploit in a tractable framework. Subsequently, we investigate the relationship between the DCI and scheduling performance, and derive a general performance property bound for any distributed scheduling. Importantly, a class of asynchronous flow scheduling scheme is proposed to achieve the performance bound by making use of the correlation among the time-scale control information.

Data of the internet of things (IoT) typically consists of packets with small payloads since the protocol header is a significant and energy-expensive overhead. A variety of applications in IoT make it more complicated than that in wireless sensor networks in which one application generally exists. In this work, we present a scheme that replaces conventional frame design with a multiple-frame solution which aims at maximizing the network bandwidth utility for prolonging the network lifetime of energy-constrained IoT. Specifically, it is designed for inheriting all advantages of the fixed size packet MAC protocols for wireless sensor networks. Basically, the proposed scheme can be viewed as a proper extension of fixed-length frame scheme whether in wireline network or wireless network in IoT. The effectiveness of scheme is demonstrated by comparing the energy efficiency with the fixed-size frame for WSN and the variable-size frame for WLANs. This would be of great use in energy-constrained IoT applications.

There is a growing interest in energy efficient or so-called “green” wireless communication to reduce the energy consumption in cellular networks. Since today's wireless terminals are typically equipped with multiple network access interfaces such as Bluetooth, Wi-Fi, and cellular networks, this paper investigates user terminals cooperating with each other in transmitting their data packets to a base station (BS) by exploiting the multiple network access interfaces, referred to as inter-network cooperation, to improve the energy efficiency in cellular uplink transmission. Given target outage probability and data rate requirements, we develop a closed-form expression of energy efficiency in Bits-per-Joule for the inter-network cooperation by taking into account the path loss, fading, and thermal noise effects. Numerical results show that when the cooperating users move towards to each other, the proposed internetwork cooperation significantly improves the energy efficiency as compared with the traditional non-cooperation and intranetwork cooperation. This implies that given a certain amount of bits to be transmitted, the inter-network cooperation requires less energy than the traditional non-cooperation and intra-network cooperation, showing the energy saving benefit of inter-network cooperation.

In this paper, we propose an opportunistic network coding (ONC) scheme in cellular relay networks, which operates depending on whether the relay decodes source messages successfully or not. A fully distributed method is presented to implement the proposed opportunistic network coding scheme without the need of any feedback between two network nodes. We consider the use of proposed ONC for cellular downlink transmissions and derive its closed-form outage probability expression considering cochannel interference in a Rayleigh fading environment. Numerical results show that the proposed ONC scheme outperforms the traditional non-cooperation in terms of outage probability. We also develop the diversity-multiplexing tradeoff (DMT) of proposed ONC and show that the ONC scheme obtains the full diversity and an increased multiplexing gain as compared with the conventional cooperation protocols.

In recent years there has been a growing interest in sparse representation of signals based on overcomplete dictionaries. Selecting few atoms that best match the signal structure, the signal is described by linear combination of these atoms. In this paper, we propose a novel overcomplete dictionary design algorithm for sparse representation of piecewise stationary signals. An effective and easy-to-use overcomplete dictionary is constructed in accordance with the parametric autocorrelation function model of piecewise stationary processes. Furthermore, a sparse decomposition algorithm in terms of nonlinear approximation is designed to obtain sparse representation of piecewise stationary signals, which has lower computational complexity and better practicability than the conventional sparse decomposition algorithms. The experimental results demonstrate that the proposed method avails for higher sparsiry of signal representation and better reconstruction performance than sparse representation of signals based on overcomplete DCT dictionary.

In this paper, we consider a power-aware multimedia communications over internet of things (IoT). Specifically, we consider a generic IoT scenario where a multimedia server provides heterogeneous applications without knowing the application's quality of experience (QoE) model and playout period. Our objective aims at dynamically adjusting the power allocation for each application over a uncertain period to maximize the system overall mean opinion score (MOS). Note that the practical QoE model can be observed over time, but the underlying functional relationship between the power and MOS is unknown. The highlight of this paper is to develop a dynamic powering algorithm, in which one learns the satisfaction function and optimizes power-aware user satisfaction with on-line operation. More precisely, the proposed algorithm performance is measured in terms of loss which denotes the MOS loss compared to the optimal one. Numerical simulation results validate the efficiency of the proposed algorithm.

In this work, we study the quality-delay tradeoff for video streaming over mobile ad hoc network by utilizing a class of scheduling schemes. We show that node spatial mobility indeed impacts on the performance of wireless video transmission under the assumption that all the nodes can identically and uniformly visit the entire network. To describe a practical mobile scenario, we consider a random walk mobility model in which each node can randomly and independently choose its mobility direction at each time-slot. The contributions of this work are twofold: 1) It investigates the optimal node velocity for the mobile video network which helps to identify the impact of mobility on the video performance; 2) It derives the achievable quality-delay tradeoff range for any node mobility velocity, and thus it is helpful to design appropriate quality and delay requirements. These results provide insights on network design and fundamental guidelines on establishing an efficient mobile wireless video transmission system.

In this paper, we study the outage performance of a two-way relay transmission, where each terminal has a single antenna and operates in a half-duplex manner, especially, a decode-and-forward (DF) relay is employed to help the bidirectional communications between two user terminals and superposition coding is applied at the relay to re-encode the successfully decoded messages. Unlike existing works, we consider a more general setup that the two user terminals have different target rates (i.e., asymmetric two-way relay transmission). First, an achievable rate region of the network scenario under consideration is characterized followed by a definition of the overall system outage probability. Then, the investigated network scenario is evaluated in terms of outage probability, after which the corresponding closed-form expressions are formulated over Rayleigh fading channels. Next, to maximize the energy efficiency, optimum power allocation between the superposed signals at the relay are examined. As a result, two different policies implementing fixed and variable scaling coefficients of superposition coding are proposed. Then, simulation experiments are performed and performance comparisons are conducted. The provided results validate the accuracy of our derived expressions and the efficiency of our propositions.

In this paper, we first explore a selective cooperation framework for secondary user transmissions in a cognitive radio network with single relay. In the selective cooperation framework, two transmission modes (i.e., relay diversity transmission and non-relay direct transmission) are considered. We study two specific selective cooperation schemes with and without an acknowledgement (ACK) from a cognitive destination as to if it succeeds in decoding or not, called ACK and non-ACK based selective cooperation, respectively. We derive closed-form outage probability expressions for the two schemes with imperfect spectrum sensing, showing that an outage probability floor occurs in high signal-to-noise ratio (SNR) regions due to mutual interference between primary and secondary users. We consider the use of the outage probability floor to generalize the traditional diversity-multiplexing tradeoff (DMT) definition, based on which a DMT analysis is conducted for the non-ACK and ACK based selective cooperation schemes. We then extend the selective cooperation framework to a multiple-relay cognitive radio network considering the best cognitive relay only to participate in assisting secondary transmissions, referred to as the selective best-relay cooperation. We also consider the non-ACK and ACK based selective best-relay cooperation schemes and develop their DMTs by using the generalized DMT definition.

In cognitive radio networks, cooperative spectrum sensing typically requires two essential phases: the phase of primary user's signal detection by cognitive users and the phase of initial detection result reporting from the cognitive users to a fusion center, which are referred to as detection and reporting phases, respectively. Common control channels (also called dedicated reporting channels) from the cognitive users to fusion center are assumed in previous research to avoid interfering with the primary user in the reporting phase. This, however, requires additional channel resources and increases implementation complexity due to the dedicated reporting channels management. In this paper, we propose an alternative cooperative spectrum sensing framework without dedicated reporting channels and present an interference analysis of its impact on primary users. We show that the interference caused by the proposed scheme is controllable and can be constrained to satisfy a given primary user's quality-of-service (QoS) requirement. By jointly considering the detection and reporting phases, we further examine the receiver operating characteristics (ROC) performance of the proposed cooperative spectrum sensing scheme in Rayleigh fading environment. Numerical results illustrate that, with a guaranteed detection probability constraint, a minimized false alarm probability can be achieved through an optimization of the time durations between the detection and reporting phases.

Free probability theory as a main branch of random matrix theory is a valuable tool for describing the asymptotic behavior of multiple systems, especially for those with large random matrices. But classical freeness results mainly focus on random matrices with independent and identically distributed (i.i.d.) entries. In this paper, by using the latest research results of random Vandermonde matrix (a class of matrix that does not satisfy the i.i.d. condition) in free probability theory, a new spectrum sensing scheme is proposed, which shows how the asymptotic behavior of random Vandermonde matrices can be used to assist spectrum sensing for cognitive radio. Simulation results show that the proposed scheme has a better detection performance than the energy detection technique and the maximum-minimum eigenvalue scheme even for the case of a small sample of observations.

Distributed scheduling for hybrid media flows over wireless body sensor network faces three technical challenges: constrained communication channel, random node placement and strict transmission latency. In this work, we study this problem by jointly considering the above three challenges to achieve the minimum media distortion and optimal network resource utilization. At first, we construct a general flow transmission model according to network's transmission mechanism, as well as media-aware flow's characteristics. Then, a distributed scheduling scheme is proposed based on dynamic network resource update. It is proved that the proposed scheme can achieve the optimal scheduling solution with an exponential convergence rate, and an explicit form of the asymptotic convergence rate is provided. Furthermore, the realization of the distributed scheduling scheme through the collaboration between the network and the sources is the highlight of this paper. Extensive simulation results are provided to demonstrate the effectiveness of our proposed scheme.

In this paper, we adopt the DMT framework to study a cooperative downlink OFDMA system with multiple relays. We derive the closed-form expression of the DMT curve for the cooperative OFDMA system employing linear constellation precoding at the base station, and linear detection at the mobile users, and develop the optimal symbol loading, relay selection and subcarrier allocation strategy. Simulation results are presented to verify the theoretical analysis and show that our proposed resource allocation strategy can improve the system performance significantly.

In cognitive radio networks, each cognitive transmission process typically requires two phases: the spectrum sensing phase and data transmission phase. In this paper, we investigate cognitive transmissions with multiple relays by jointly considering the two phases over Rayleigh fading channels. We study a selective fusion spectrum sensing and best relay data transmission (SFSS-BRDT) scheme in multiple-relay cognitive radio networks. Specifically, in the spectrum sensing phase, only the initial spectrum sensing results, which are received from the cognitive relays and decoded correctly at a cognitive source, are selected and used for fusion. In the data transmission phase, only the best relay is utilized to assist the cognitive source for data transmissions. Under the constraint of satisfying a required probability of false alarm of spectrum holes (for the protection of the primary user), we derive an exact closed-form expression of the spectrum hole utilization efficiency for the SFSS-BRDT scheme, which is used as a measure to quantify the percentage of spectrum holes utilized by the cognitive source for its successful data transmissions. For the comparison purpose, we also examine the spectrum hole utilization efficiency for a fixed fusion spectrum sensing and best relay data transmission (FFSS-BRDT) scheme, where all the initial spectrum sensing results are used for fusion without any refined selection. Numerical results show that, under a target probability of false alarm of spectrum holes, the SFSS-BRDT scheme outperforms the FFSS-BRDT scheme in terms of the spectrum hole utilization efficiency. Moreover, the spectrum hole utilization efficiency of the SFSS-BRDT scheme always improves as the number of cognitive relays increases, whereas the FFSS-BRDT scheme's performance improves initially and degrades eventually after a critical number of cognitive relays. It is also shown that a maximum spectrum hole utilization efficiency can be achieved through an optimal allocation of the time durations between the spectrum sensing and data transmission phases for both the FFSS-BRDT and SFSS-BRDT schemes.

Typically, each cooperative spectrum sensing process requires two phases: the primary user's signal detection phase, in which all cognitive users attempt to detect the presence of the primary user within a certain observation window (called signal detection overhead); and the initial detection result reporting phase, in which the cognitive users forward their detection results to a fusion center. To avoid interfering with the primary user in the reporting phase, previous research assumed that there is a common control channel (also known as dedicated reporting channel) between the cognitive users and fusion center, which, however, requires extra channel resources and introduces an additional complexity due to the dedicated channel resource management. In this paper, we propose a selective-relay based cooperative spectrum sensing scheme, which is able to control and reduce the interference from cognitive reporting users to primary user without the dedicated channel. We analyze the interference impact on the primary user and show that the interference induced by the reporting users is controllable and can be reduced to satisfy a given outage probability requirement of the primary transmissions. In addition, we investigate the receiver operating characteristics (ROC) of the traditional cooperative sensing scheme (with dedicated reporting channel) and the proposed scheme (without dedicated reporting channel) by jointly considering the signal detection and reporting phases. It is proven that, given a target detection probability, a unique optimal signal detection overhead exists to minimize an asymptotic overall false alarm probability in high SNR regions. We illustrate that, compared to the traditional scheme, the selective-relay based cooperative sensing scheme can save the dedicated channel resources without sacrificing ROC performance. Numerical results also show that, under a guaranteed overall detection probability, an overall false alarm probability can be minimized through an optimization of the signal detection overhead.

In this paper, we propose a cognitive transmission scheme with the best relay selection in a multiple-relay cognitive radio network to improve the secondary transmission performance while guaranteeing the quality-of-service (QoS) of the primary transmissions. We derive the closed-form expressions of outage probability for the secondary transmissions, called secondary outage probability, with the constraint of ensuring a target outage probability of primary transmissions (primary outage probability) for both the traditional non-relay and proposed best-relay selection based cognitive transmission schemes. Numerical results illustrate that, under a primary outage probability constraint, a secondary outage probability floor of the cognitive transmission occurs in high signal-to-noise ratio regions. Besides, the secondary outage probability floor of the proposed scheme is lower than that of the non-relay transmission, which is further reduced with an increasing number of cognitive relays.

Cognitive orthogonal frequency division multiplexing (C-OFDM) is an extremely promising technique for achieving high transmission capacity in the next generation cellular and wireless local area network (WLAN) systems with limited spectrum resources. Since the greedy bit allocation algorithm is the optimal method for single user, however, in the case of plenty of sub-carriers and bits to be distributed, the computational complexity will be extraordinarily unacceptable. This paper presents a new bit and power allocation scheme for C-OFDM systems based on the margin adaptive (MA) principle in which the overall transmission power is minimized by constraining the fixed data rate and bit error rate. The presented bit allocation algorithm is derived from geometric progression of the additional transmission power required by the sub-carriers and the arithmetic-geometric means inequality. Consequently, compared with the algorithm existing now, this algorithm has a simple procedure and low computational complexity. Simulation results show that the proposed algorithm is superior to the traditional algorithm, while reducing the computational complexity from exponential to linear in the number of sub-carriers.

Free probability theory, which has became a main branch of random matrix theory, is a valuable tool for describing the asymptotic behavior of multiple systems, especially for large random matrices. In this paper, using free probability theory, a new spectrum sensing scheme for cognitive OFDM system is proposed, which shows how asymptotic free behavior of random matrices and the property of Wishart distribution can be used to assist spectrum sensing for cognitive radios. Simulations over Rayleigh fading and AWGN channels demonstrate the proposed scheme has better detection performance and lower power need compared with the energy detection technique even for the case of a small sample of observations.

In cognitive radio systems, cooperative spectrum sensing can detect the presence of the primary user accurately. However, with the increasing number of cooperative users, a larger dedicated control channel bandwidth is needed to transmit the local binary decisions of SUs to the fusion center. To further improve the sensing performance of cooperative spectrum sensing under bandwidth-limited constraints, we propose a new cooperative spectrum sensing. More specifically, only the secondary users with reliable information are allowed to send their local binary decisions to the fusion center while the others will send nothing. The sensing performance of the proposed method is studied and the analytical performance results are given. Our analysis and numerical results verify that the sensing performance is improved significantly compared to conventional cooperative spectrum sensing.

Security is increasingly becoming an important issue in the design of multimedia applications. However, existing scheduling schemes for real-time multimedia services over heterogeneous networks generally do not take into account security requirements when making control decisions. In this paper, we develop and evaluate a security-aware multimedia scheduling scheme in heterogeneous environment. Firstly, we exploit a multimedia transmission model in the context of heterogeneous wireless networks. Then, a security-aware scheduling scheme is proposed by taking into account applications' timing and security requirements in addition to precedence constraints. Furthermore, the proposed scheme is applied to heuristically find resource allocations, which maximize the quality of security and the probability of meeting deadlines for all the multimedia applications. Additionally, extensive experiments are provided to demonstrate the effectiveness of the proposed scheme.

In cognitive radio networks, a cognitive source node requires two essential phases to complete a cognitive transmission process: the phase of spectrum sensing with a certain time duration (also referred to as spectrum sensing overhead) to detect a spectrum hole and the phase of data transmission through the detected spectrum hole. In this paper, we focus on the outage probability analysis of cognitive transmissions by considering the two phases jointly to examine the impact of spectrum sensing overhead on system performance. A closed-form expression of an overall outage probability that accounts for both the probability of no spectrum hole detected and the probability of a channel outage is derived for cognitive transmissions over Rayleigh fading channels. We further conduct an asymptotic outage analysis in high signal-to-noise ratio regions and obtain an optimal spectrum sensing overhead solution to minimize the asymptotic outage probability. Besides, numerical results show that a minimized overall outage probability can be achieved through a tradeoff in determining the time durations for the spectrum hole detection and data transmission phases. In this paper, we also investigate the use of cognitive relay to improve the outage performance of cognitive transmissions. We show that a significant improvement is achieved by the proposed cognitive relay scheme in terms of the overall outage probability.

Free probability theory, which has became a main branch of random matrix theory, is a valuable tool for describing the asymptotic behavior of multiple systems, especially for large random matrices. In this paper, using free probability theory, a new cooperative scheme for spectrum sensing is proposed, which shows how asymptotic free behavior of random matrices and the property of Wishart distribution can be used to assist spectrum sensing for cognitive radios. Simulations over Rayleigh fading and AWGN channels demonstrate the proposed scheme has better detection performance compared with the energy detection techniques even for the case of a small sample of observations.

An important issue of supporting multi-user video streaming over wireless networks is how to optimize the systematic scheduling by intelligently utilizing the available network resources while, at the same time, to meet each video's QoS (quality of service) requirement. In this work, we study the problem of video scheduling over multi-channel multi-radio multi-hop networks with the goals of minimizing the video distortion. At first, we construct a general distortion model according to the network's transmission mechanism, as well as video's rate-distortion characteristics. Then, by joint considering the channel assignment, rate allocation and routing, we develop a fully distributed scheduling scheme to get an optimal QoS performance. Furthermore, the realization of the distributed scheduling scheme through cooperation among the channel, link and source is the highlight of this paper. Extensive simulation results are provided which demonstrate the effectiveness of our proposed scheme.

We propose a feedback strategy based on SINR threshold for downlink multiuser wireless systems. By using the proposed strategy the base station receives feedback only from those users whose SINRs are above a threshold which is elaborately chosen and broadcast to all users in the cell by the base station. So not all users need send their channel direction information (CDI) and channel quality information (CQI) to the base station. It is proved that downlink wireless systems using the proposed strategy can achieve the multiplexing diversity and multiuser diversity gain with greatly reduced the sum feedback rate.

The support for multiple high-definition video streams in wireless home networks requires appropriate routing and rate control measures, ascertaining the reasonable links for transmitting each stream and the rate of the video to be delivered over the chosen links. In this paper, we invest the combination of the routing and rate control in a united convex optimization formulation and propose a distributed joint solution based on cross-layer design. We first develop a distortion model which captures both the impact of encoder quantization and packet loss due to network congestion on the overall video quality. Then, the optimal joint rate control and routing scheme is realized by adapting its rate to the time-varying traffic and minimizing the overall network congestion. Furthermore, simulation results are provided, which demonstrate the effectiveness of our proposed joint routing and rate control scheme in the context of wireless home networks.

Cooperation is emerging as a promising technology to combat the wireless fading and enhance the channel capacity. However,cooperative transmission can not be guaranteed to perform better always than direct transmission, since the statistics of both direct and relay channels are varied due to large scale fading. Therefore, we design an opportunistic criterion to automatically determine which transmission mode should be adopted depending on the channel quality from the source to the cooperative relay, as opposed to the deterministic cooperation regardless of relay channel conditions. According to the proposed criterion, we further present two opportunistic cooperation schemes, namely, the SDC (selection diversity combining) -based and the MRC (maximum ratio combining) -based opportunistic cooperation, and develop the closed-form expressions of outage probability for the proposed schemes over Rayleigh fading channels. For the purpose of comparison, we also analyze the outage probability for the known deterministic cooperation and coded cooperation. Numerical results show that our schemes outperform the traditional schemes in terms of outage probability, especially when the relay channel conditions worsen. In addition, we compare the MRC-based opportunistic cooperation with the SDC-based opportunistic cooperation, showing the superiority of the former scheme.

The cooperative communication technology proposed in recent years enables network nodes to share their antennas to achieve diversity gain. In this paper, an efficient variation scheme on opportunistic cooperation is proposed by using an outage criterion, in which the cooperation mode will be adopted only when the channel from source to relay does not occur outage event. We derive a closed-form BER (bit error rate) expression for the proposed scheme over Rayleigh fading channels, showing that the full diversity is achieved by the new scheme. Also, the BER performance of the known coded cooperation is presented for the purpose of comparison with our scheme. Numerical results illustrate the superiority of the proposed scheme over the coded cooperation in terms of BER performance. It is pointed out that the corresponding BER advantage of the proposed scheme comes at the expense of increasing system overhead since the new scheme needs some feedback from relay to both source and destination.

The traditional cooperative diversity could improve the system performance greatly through sharing some single-antenna users' antennas of the network, but can't achieve the diversity gain and coding gain at the same time. Accordingly, a novel cooperative diversity scheme based on concatenating channel code and distributed space-time block code (DSTBC) is proposed in this paper to further obtain much more performance gain. And the analytic expressions and numerical results of the single-user capacity, outage probability and bit error rate (BER) for the cooperative transmission over the Rayleigh fading channel are also presented by the theoretical derivation and system simulation. Numerical results show that, even though the interuser channel is noisy, our proposed scheme outgoes the traditional cooperative diversity in terms of system capacity, outage probability and BER.

An important issue for supporting multimedia applications in multiple heterogeneous networks, a typical pervasive computing environment, is how to optimize the rate allocation by intelligently utilizing the available network resources while, at the same time, to meet each application's QoS (Quality of Service) requirement. In this work, we develop and evaluate a rate allocation scheme in terms of audio and video applications based on a cross-layer design framework. At first, we construct a general distortion model according to the observed parameters in each network, as well as each application's rate-distortion characteristic. Then, the rate allocation is formulated as a convex optimization problem that minimizes the sum of the expected distortion of all applications. Furthermore, the realization of the distributed rate allocation algorithm for achieving an optimal or close-to-optimal end-to-end QoS under the overall limited resource budget is the highlight of this paper. Simulation results are provided which demonstrate the effectiveness of our proposed distributed rate allocation scheme.

Wireless mesh networks are emerging as a favorable technology for last-mile Internet access. Nodes in WMNs can be equipped with multiple radios which work in different channels to increase the available bandwidth. In this work, we present an analytical model for almost surely k-connectivity of WMNs with multi-radio multi-channel in two-dimensional case through a random uniform distribution and the analysis of the minimum node degree. Based on our model, the numerical results show the factors - the density of nodes, the minimum degree of neighbors, the probability of selection of channels and the different transmission ranges can impact the connectivity probability significantly by their variable values.

Quantum neural network (QNN) is a promising area in the field of quantum computing and quantum information processing. A model of feedback quantum neuron (FQN) is proposed and its property is analyzed. A novel multi-user detector based on FQN and quantum register is proposed. An analysis is given to the theoretical basis and practical performance of the proposed detector. The simulation results show that the proposed detector has more powerful properties both in bit error rate and near-far resistance than Hopfield neural network based detector. A multi-user detector based on improved FQN is also proposed and the simulation results have shown that the improved FQN multi-user detector is obviously superior to the FQN multi-user detector. Its performance is closer to optimal, compared with the other multi-user detector.

The classical optimal solution of CDMA multi-user detection is consistent with the optimization of a quadratic function, and to find the optimum is a NP hard problem. Reducing the complexity of optimum based on quantum parallel computation is a new trend of multi-user detection techniques. In this paper, we propose a scheme based on Grover's searching algorithm to find the optimum. We give the relationship of bit error rate against signal-to-noise and correlation coefficient by numerical simulation, and simply evaluate the computational complexity of our proposed scheme. The results show that our solution has almost the same performance to the classical optimal one, however, with low complexity

A computationally efficient mixed feature based neural network (MFNN) is proposed for the detection of microcalcification clusters (MCCs) in digitized mammograms. The MFNN employs features computed in both the spatial and spectral domain and uses spectral entropy as a decision parameter. Backpropagation with Kalman filtering (KF) is employed to allow more efficient network training as required for evaluation of different features, input images, and related error analysis. A previously reported, wavelet-based image-enhancement method is also employed to enhance microcalcification clusters for improved detection. The relative performance of the MFNN for both the raw and enhanced images is evaluated using a common image database of 30 digitized mammograms, with 20 images containing 21 biopsy proven MCCs and ten normal cases. The computed sensitivity (true positive (TP) detection rate) was 90.1% with an average low false positive (FP) detection of 0.71 MCCs/image for the enhanced images using a modified k-fold validation error estimation technique. The corresponding computed sensitivity for the raw images was reduced to 81.4% and with 0.59 FP's MCCs/image. A relative comparison to an earlier neural network (NN) design, using only spatially related features, suggests the importance of the addition of spectral domain features when the raw image data is analyzed.