Multi-sensory communications with haptics attract a number of researchers in recent years. To provide services of the communications with high realistic sensations, the researchers focus on the quality of service (QoS) control, which keeps as high quality as possible, and the quality of experience (QoE) assessment, which is carried out to investigate the influence on user perception and to verify the effectiveness of QoS control. In this paper, we report the present status of studies on multi-sensory communications with haptics. Then, we divide applications of the communications into applications in virtual environments and those in real environments, and we mainly describe collaborative work and competitive work in each of the virtual and real environments. We also explain QoS control which is applied to the applications and QoE assessment carried out in them. Furthermore, we discuss the future directions of studies on multi-sensory communications.

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Information affects almost all aspects of life, and thus the Quality of Information (IQ) plays a critical role in businesses and societies; It can have significant positive and negative impacts on the quality of life of citizens, employees and organizations. Over many years aspects and challenges of IQ have been studied within various contexts. As a result, the general approach to the study of IQ has offered numerous management and measurement approaches, IQ frameworks and list of IQ criteria. As the volume of data and information increases, IQ problems become pervasive. Whereas earlier studies investigated specific aspects of IQ, the next phase of IQ research will need to examine IQ in a wider context, thus its impact on the quality of life and societies. In this paper we apply an IQ oriented framework to two cases, cloud computing and lifelogging, illustrating the impact of IQ on the quality of life. The paper demonstrates the value of the framework, the impact IQ can have on the quality of life and in summary provides a foundation for further research.

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Three-dimensional (3D) video service is expected to be introduced as a next-generation television service. Stereoscopic video is composed of two 2D video signals for the left and right views, and these 2D video signals are encoded. Video quality between the left and right views is not always consistent because, for example, each view is encoded at a different bit rate. As a result, the video quality difference between the left and right views degrades the quality of stereoscopic video. However, these characteristics have not been thoroughly studied or modeled. Therefore, it is necessary to better understand how the video quality difference affects stereoscopic video quality and to model the video quality characteristics. To do that, we conducted subjective quality assessments to derive subjective video quality characteristics. The characteristics showed that 3D video quality was affected by the difference in video quality between the left and right views, and that when the difference was small, 3D video quality correlated with the highest 2D video quality of the two views. We modeled these characteristics as a subjective quality metric using a training data set. Finally, we verified the performance of our proposed model by applying it to unknown data sets.

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The IEEE 802.11 distributed coordinated function (DCF) adopts carrier sense multiple access with collision avoidance (CSMA/CA) as its medium access control (MAC) protocol. CSMA/CA is designed such that the transmission from any one station does not have priority over any other. In a congested environment with many DCF stations, this design makes it difficult to protect channel resources for certain stations such as when products are used for presentation at exhibitions, which should be protected based on priority. On the other hand, The IEEE 802.11 enhanced distributed channel access (EDCA) provides a quality-of-service (QoS) mechanism for DCF. However in EDCA, transmission opportunities are allocated based on not individual stations but on the defined traffic type of applications. This paper proposes a distributed dynamic resource allocation method that enables control of flexible bandwidth allocation to each specific station. The proposed method controls the priority level and can coexist with conventional CSMA/CA. Moreover, the proposed method improves the system throughput. Specifically, under the coexistence environment with DCF stations, the proposed method is able to obtain up to over 300% higher user throughput characteristic compared to the case in which the proposed method is not introduced. In addition, under non-coexistence environment, all the proposed stations achieve 70% higher throughput than DCF stations when the number of stations in a network is 50.

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Recently, network coding (NC) has been popularly applied to wireless networks in order to improve scarce wireless capacity. In wireless LANs, NC can be applied to packet retransmission in which multiple packets can be simultaneously transmitted by a single transmission trial at a base station (BS). In this paper, we assume wireless LANs with QoS functionality and propose adaptive cooperation between NC and IEEE 802.11e EDCA. In EDCA, when network load is high, QoS is significantly degraded even for high priority class. To solve this, existing methods improve backoff control, and decrease packet loss caused by collision. However, this cannot prevent packet loss caused by channel fading. In the proposed cooperation between NC and EDCA, QoS of all priority classes is improved from the aspect of efficient loss recovery. Unlike NC method with no QoS control, we encounter transmission scheduling problem among an NC packet, a single lost packet and a new packet. Moreover, in the constitution of packets encoded into NC packet, packet's intrinsic priority should be considered. Therefore, we propose how to schedule the packets to be transmitted in BS, and how to constitute NC packets to be encoded. Finally, we show the effectiveness of the proposed method by extensive computer simulations.

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This paper deals with two types of capacity allocation schemes, i.e., static and adaptive, for uplink and downlink burst durations in the IEEE 802.16 BE (Best Effort) service. We study QoE (Quality of Experience) enhancement of audio-video IP transmission over the uplink channel with the two capacity allocation schemes. We introduce a piggyback request mechanism for uplink bandwidth requests from subscriber stations to the base station in addition to a random access-based request mechanism. We assess QoE of audio-video streams for four schemes obtained from the combination of the capacity allocation schemes and the bandwidth request mechanisms. We also employ two types of audio-video contents. From the assessment result, we notice that the adaptive allocation scheme is effective for QoE enhancement particularly under heavily loaded conditions because of its efficient usage of OFDM symbols. In addition, the piggyback request mechanism can enhance QoE of audio-video transmission. We also find that the effects of capacity allocation schemes and piggyback request mechanism on QoE change according to the content types.

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Recent studies have shown that the traffic load is often distributed unevenly among the access points. Such load imbalance results in an ineffective bandwidth utilization. The load imbalance and the consequent ineffective bandwidth utilization could be alleviated via intelligently selecting user-AP associations. In this paper, the diversity in users' utilities is sufficiently taken into account, and a Stackelberg leader-follower game is formulated to obtain the optimal user-AP association. The effectiveness of the proposed algorithm on improving the degree of load balance is evaluated via simulations. Simulation results show that the performance of the proposed algorithm is superior to or at least comparable with the best existing algorithms.

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Measuring network resource information, including available bandwidth, propagation delay, and packet loss ratio, is an important task for efficient operation of overlay network services. Although measurement accuracy can be enhanced by frequent measurements, performing measurements with high frequency can cause measurement conflict problem that increases the network load and degrades measurement accuracy. In this paper, we propose a low-cost, distributed and conflict-aware measurement method that reduces measurement conflicts while maintaining high measurement accuracy. The main idea is that the overlay node exchanges the route information and the measurement results with its neighboring overlay nodes while decreasing the measurement frequency. This means our method trades the overhead of conducting measurements for the overhead of information exchange to enhance measurement accuracy. Simulation results show that the relative error in the measurement results of our method can be decreased by half compared with the existing method when the total measurement overheads of both methods are equal. We also confirm that exchanging measurement results contributes more to the enhancement of measurement accuracy than performing measurements.

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Network tomography is an inference technique for internal network characteristics such as link loss rate and link delay from end-to-end measurements. In this paper, we consider network tomography for link loss rates, which is referred to as loss tomography. We propose a loss tomography scheme with bitwise operation-based in-network processing. Intermediate nodes generate coded packets by performing bitwise-operations on received packets so as to embed information about paths along which those packets have been transmitted. The coded packets are then forwarded to downstream nodes. In this way, receiver nodes obtain information about paths along which packets are transmitted successfully. Moreover, we show a recursion to compute the likelihood function of path loss rates, which can be utilized in estimating link loss rates from path loss information.

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OpenFlow, originally proposed for campus and enterprise network experimentation, has become a promising SDN architecture that is considered as a widely-deployable production network node recently. It is, in a consequence, pointed out that OpenFlow cannot scale and replace today's versatile network devices due to its limited scalability and flexibility. In this paper, we propose OpenQFlow, a novel scalable and flexible variant of OpenFlow. OpenQFlow provides a fine-grained flow tracking while flow classification is decoupled from the tracking by separating the inefficiently coupled flow table to three different tables: flow state table, forwarding rule table, and QoS rule table. We also develop a two-tier flow-based QoS framework, derived from our new packet scheduling algorithm, which provides performance guarantee and fairness on both granularity levels of micro- and aggregate-flow at the same time. We have implemented OpenQFlow on an off-the-shelf microTCA chassis equipped with a commodity multicore processor, for which our architecture is suited, to achieve high-performance with carefully engineered software design and optimization.

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Probabilistic Packet Marking (PPM) is a scheme for IP traceback where each packet is marked randomly with an IP address of one router on the attack path in order for the victim to trace the source of attacks. In previous work, a network coding approach to PPM (PPM+NC) where each packet is marked with a random linear combination of router IP addresses was introduced to reduce number of packets required to infer the attack path. However, the previous work lacks a formal proof for benefit of network coding to PPM and its proposed scheme is restricted. In this paper, we propose a novel method to prove a strong theorem for benefit of network coding to PPM in the general case, which compares different perspectives (interests of collecting) at the collector in PPM+NC scheme. Then we propose Core PPM+NC schemes based on our core network coding approach to PPM. From experiments, we show that our Core PPM+NC schemes actually require less number of packets than previous schemes to infer the attack path. In addition, based on the relationship between Coupon Collector's Problem (CCP) and PPM, we prove that there exists numerous designs that CCP still benefits from network coding.

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This paper first formulates the optimal instantaneous resource allocation, including path selection, power allocation and subchannel scheduling with proportional fairness in MIMO, OFDMA and relay-enhanced network. The joint optimization problem is a NP-hard one with non-linear constraints. To simplify this problem, we first propose a water-filling method named ‘CP-AP w PF’ to adaptively allocate power only among transmitting antennas. Then, a modified iterative water-filling algorithm named ‘AP-AP w PF’ is proposed to achieve adaptive power allocation on each subchannel by using the Jensen's inequality. Simulation shows that ‘AP-AP w PF’ algorithm improves the throughput for cell-edge users, and achieve a tradeoff between maximizing system throughput and assuring individual QoS.

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Network tomography is an appealing technology to infer link delay distributions since it only relies on end-to-end measurements. However, most approaches in network delay tomography are usually computationally intractable. In this letter, we propose a Fast link Delay distribution Inference algorithm (FDI). It estimates the node cumulative delay distributions by explicit computations based on a subtree-partitioning technique, and then derives the individual link delay distributions from the estimated cumulative delay distributions. Furthermore, a novel discrete delay model where each link has a different bin size is proposed to efficiently capture the essential characteristics of the link delay. Combining with the variable bin size model, FDI can identify the characteristics of the network-internal link delay quickly and accurately. Simulation results validate the effectiveness of our method.

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The contradictions created by the differences in mass P2P data and transfer capability of wireless networks, and mismatch of overlay network topology and physical network topology are the main barriers hindering the implementation of P2P resource sharing in wireless multi-hop networks. This paper investigates the problem of enabling P2P resource sharing in WMNs with two-tier architecture. SpiralChord, the DHT approach implemented through routers in the upper tier, is proposed to address the major problems of wireless resource sharing — how to efficiently find resources currently available and reduce redundant messages as much as possible. SpiralChord uses an ID assignment technique to integrate location awareness with cross-layering. Location awareness aims at alleviating mismatch in physical network topology and overlay network topology, and it is designed to map neighboring routers to close-by IDs in the logical ring. Cross-layering aims at speeding up resource lookup operations in the application layer by exploiting the information that is available at the MAC layer, and it tends to be more effective when physically neighboring routers have faraway IDs in the logical ring. An ID assignment strategy based on spiral curve is proposed to meet the contradictory requirements of location awareness and cross-layering, mapping a peer's neighbors in the overlay network to peers which are its physical neighbors and distributing the remaining physical neighbors as widely as possible in the overlay network. In addition, a mobility management mechanism is proposed to address the adverse effect of the movements of clients in lower tier on resource sharing. A client is assigned a managing router to take the responsibility for the location of the client. Simulations show SpiralChord is more effective in reducing message overhead and increasing lookup performance than Chord, and mobility management for mobile clients performs well at reducing message overhead caused by mobile clients in SpiralChord.

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We use end-to-end measurements to address the problem of fault diagnosis in computer networks. Since link-level characteristics cannot be uniquely determined from available end-to-end measurements, most existing diagnosis approaches make statistical assumptions of the network to obtain a unique solution. However, the performance of these approaches is not assured due to the uncertainty of the assumptions. Thus the diagnostic accuracy cannot be guaranteed. In this paper, we propose a different paradigm for fault diagnosis which can find all identifiable links and the minimal identifiable link sequences, and infer their loss rates with the least error. Compared with a former representative diagnosis method through experiments, the experimental results show that our method has smaller diagnosis granularity and much less running time for most network topologies. We also conducted experiments using 105 Planetlab hosts. The results validate the performance of our method as well.

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We analyze measured traffic data to investigate the characteristics of TCP quality metrics such as packet retransmission rate, roundtrip time (RTT), and throughput of connections classified by their type (client-server (C/S) or peer-to-peer (P2P)), or by the location of the connection host (domestic or overseas). Our findings are as follows. (i) The TCP quality metrics of the measured traffic data are not necessarily consistent with a theoretical formula proposed in a previous study. However, the average RTT and retransmission rate are negatively correlated with the throughput, which is similar to this formula. Furthermore, the maximum idle time, which is defined as the maximum length of the packet interarrival times, is negatively correlated with throughput. (ii) Each TCP quality metric of C/S connections is higher than that of P2P connections. Here “higher quality” means that either the throughput is higher, or the other TCP quality metrics lead to higher throughput; for example the average RTT is lower or the retransmission rate is lower. Specifically, the median throughput of C/S connections is 2.5 times higher than that of P2P connections in the incoming direction of domestic traffic. (iii) The characteristics of TCP quality metrics depend on the location of the host of the TCP connection. There are cases in which overseas servers might use a different TCP congestion control scheme. Even if we eliminate these servers, there is still a difference in the degree of impact the average RTT has on the throughput between domestic and overseas traffic. One reason for this is thought to be the difference in the maximum idle time, and another is the fact that congestion levels of these types of traffic differ, even if their average RTTs are the same.

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The recent increase in mobile data traffic has resulted in service quality problems. Although an economic approach to control congestion can be achieved by pricing, the current pricing schedule of mobile data services instead causes smartphone users to create more traffic. We establish a pricing model based on the distribution of demand types among heterogeneous users to improve the current tariff structure; our method mixes usage-based and fixed-fee pricing schemes. The results derived from the application of this model to survey data on willingness-to-pay for mobile data service demonstrate that the provider can decrease the amount of data traffic and increase the expected revenue by lowering the price for a unit of data and raising the fixed-fee level for unlimited service. The model also explains the changing weight of usage-based and fixed-fee pricing schemes by considering shifts in the type distribution through service evolution and proposes pricing strategies for future communications services.

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A direction-of-arrival estimation (DoA) scheme that uses a uniform circular array (UCA) is proposed for near-field sources, where multiple pairs-of-subarrays exist with central symmetry. First, multiple generalized ESPRIT (G-ESPRIT) spectrums are obtained by applying the conventional G-ESPRIT algorithm to each of multiple pairs-of-subarrays. Second, a parallel spectrum is found by adding up the reciprocals of these G-ESPRIT spectrums and taking the reciprocal of the total. The locations of peaks in the parallel spectrum give the DoAs being estimated. When a DoA approaches the translation direction of two subarrays, the conventional G-ESPRIT spectrum is broken by a false peak. Since the translation directions of pairs-of-subarrays are different from each other, the false peak, due to the DoA approaching one of translation directions, does not exist simultaneously in all G-ESPRIT spectrums. The parallel concatenation of the spectrums suppresses the false peak and enhances the true DoA peaks. Simulation shows that the proposed scheme reduces the root mean square error of the DoA estimation, compared with the conventional G-ESPRIT algorithm.

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The important issue of an adaptive scheduling scheme is to maximize throughput while providing fair services to all users, especially under strict quality of service requirements. To achieve this goal, we consider the problem of multiuser scheduling under a given fairness constraint. A novel Adaptive Fairness and Throughput Control (AFTC) approach is proposed to maximize the network throughput while attaining a given min-max fairness index. Simulation results reveal that comparing to straightforward methods, the proposed AFTC approach can achieve the desired fairness while maximizing the throughput with short convergence time, and is stable in dynamic scenarios. The trade-off between fairness and throughput can be accurately controlled by adjusting the scheduler's parameters.

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Precoding is an excellent choice for complementing the MIMO systems. Linear precoding techniques offer better performance at low signal-to-noise ratios (SNRs) while non-linear techniques perform better at higher SNRs. In addition, the non-linear techniques can achieve near optimal capacity at the expense of reasonable levels of complexity. However, precoding depends on the knowledge of the wireless channel. Recent work on MIMO systems have shown that channel-knowledge at the transmitter, in either full or partial forms, can increase the channel capacity and system performance considerably. Therefore, hybrid techniques should be deployed in order to obtain a better trade-off in terms of complexity and performance. In this paper, we present a hybrid precoding technique which deals with the condition of partial channel-knowledge while offering robustness against the effects of correlation and poorly scattered channels while at the same time keeping low levels of complexity and high performance.

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In this paper, we investigate the outage probability of a dual-hop, channel state information (CSI)-assisted amplify-and-forward (AF) multiple antenna relay network when interference is present at the relay. The source and the destination are equipped with multiple antennas and communicate with each other with the help of a single antenna relay. Transmit antenna selection is performed at the source for source-relay communication. Three receiver combining schemes namely, maximal ratio combining (MRC), equal gain combining (EGC) and selection combining (SC) are considered at the destination. Exact analytical expressions are derived for the outage probability of MRC and SC receiving while an approximate expression is obtained for EGC. Monte-Carlo simulation results are provided to complement analytical results and to demonstrate the effect of interference.

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In this paper, an extended best linear unbiased estimator (EBLUE) based on a periodic training sequence is proposed and investigated for frequency offset estimation in orthogonal frequency division multiplexing (OFDM) systems. The structure of EBLUE is general and flexible so it adapts to different complexity constraints, and is attractive in practical implementation. Performance analysis and design strategy of EBLUE are provided to realize the best tradeoff between performance and complexity. Moreover, closed-form results of both weight and performance make EBLUE even more attractive in practical implementation. Both the performance and complexity of EBLUE are compared with other proposals and the Cramer-Rao lower bound (CRLB) to demonstrate the merit of EBLUE.

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A wireless node is called isolated if it has no links to other nodes. The number of isolated nodes in a wireless network is an important connectivity index. However, most previous works on analytically determining the number of isolated nodes were not based on practical channel models. In this work, we study this problem using a generic probabilistic channel model that can capture the behaviors of the most widely used channel models, including the disk graph model, the Bernoulli link model, the Gaussian white noise model, the Rayleigh fading model, and the Nakagami fading model. We derive the expected number of isolated nodes and further prove that their distribution asymptotically follows a Poisson distribution. We also conjecture that the nonexistence of isolated nodes asymptotically implies the connectivity of the network, and that the probability of connectivity follows the Gumbel function.

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With appropriate geometry configurations, bistatic Synthetic Aperture Radar (SAR) can break through the limitations of monostatic SAR for forward-looking imaging. Thanks to such a capability, bistatic forward-looking SAR (BFSAR) has extensive potential applications. This paper develops a frequency-domain imaging algorithm for translational invariant BFSAR. The algorithm uses the method of Lengendre polynomials expansion to compute the two dimensional point target reference spectrum, and this spectrum is used to perform the range cell migration correction (RCMC), secondary range compression and azimuth compression. In particular, the Doppler-centroid and bistatic-range dependent interpolation for residual RCMC is presented in detail. In addition, a method that combines the ambiguity and resolution theories to determine the forward-looking imaging swath is also presented in this paper.

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The imaging of humans using radar is promising for surveillance systems. Although conventional radar systems detect the presence or position of intruders, it is difficult to acquire shape and motion details because the resolution is insufficient. This paper presents a high-resolution human imaging algorithm for an ultra-wideband (UWB) Doppler radar. The proposed algorithm estimates three-dimensional human images using interferometry and, using velocity information, rejects false images created by the interference of body parts. Experiments verify that our proposed algorithm achieves adequate pedestrian imaging. In addition, accurate shape and motion parameters are extracted from the estimated images.

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Reversible data hiding has been a hot research topic since both the host media and hidden data can be recovered without distortion. In the past several years, more and more attention has been paid to reversible data hiding schemes for images in compressed formats such as JPEG, JPEG2000, Vector Quantization (VQ) and Block Truncation Coding (BTC). Traditional data hiding schemes in the BTC domain modify the BTC encoding stage or BTC-compressed data according to the secret bits, and they have no ability to reduce the bit rate but may reduce the image quality. This paper presents a novel reversible data hiding scheme for BTC-compressed images by further losslessly encoding the BTC-compressed data according to the secret bits. First, the original BTC technique is performed on the original image to obtain the BTC-compressed data which can be represented by a high mean table, a low mean table and a bitplane sequence. Then, the proposed reversible data hiding scheme is performed on both the high mean table and low mean table. Our hiding scheme is a lossless joint hiding and compression method based on 2×2 blocks in mean tables, thus it can not only hide data in mean tables but also reduce the bit rate. Experiments show that our scheme outperforms three existing BTC-based data hiding works, in terms of the bit rate, capacity and efficiency.

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In this letter, we prove that for fading multiuser orthogonal frequency division multiplexing networks, a simple fixed rate scheduling scheme with only 1bit channel state information feedback is capable of achieving the optimal performance in the wideband limit. This result indicates that the complexities of both the feedback and channel coding schemes can be reduced with nearly no system performance penalty in wideband wireless communication environments.

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In this letter we proposed the linear combination of two ISI-free pulses with different decay rates in order to obtain a new Nyquist pulse. The proposed pulse contains a new design parameter β, giving an additional degree of freedom to minimize the bit error probability performance in the presence of symbol-timing errors, for a given roll-off factor α. Several practical tools are implemented for evaluating the performance of the proposed filter. The novel pulse is evaluated in terms of the bit error probability performance in the presence of symbol-timing errors. Eye diagrams are presented to visually assess the vulnerability of the transmission system to ISI, and the maximum distortion is estimated as a quantitative measure of performance.

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In this letter, we propose a new QoS scheduling algorithm, referred to as the explicit traffic aware scheduling algorithm with explicit queue length notification (ETA-EQN), which aims at supporting multimedia services in HCCA of IEEE 802.11e WLAN. The results from intensive simulations with NS-2 verify that ETA-EQN provides much better network performance than the reference scheduler in terms of throughput, delay, and packet loss.

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Fast string matching is essential for deep packet inspection (DPI). Traditional string matchers cannot keep up with the continuous increases in data rates due to their natural speed limits. We add a multi-byte processing prefilter to the traditional string matcher to detect target patterns on a multiple character basis. The proposed winnowing prefilter significantly reduces the number of identity blocks, thereby reducing the memory requirements.

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This letter proposes a new mechanism for network configuration on a mobile device that provides Point of Attachment (PoA) specific information using IEEE 802.21 and DHCP before moving to a new PoA. This allows the mobile device to prepare for intelligent handover decision either stateless address configuration or stateful address configuration when entering an IPv6 network. It allows the mobile device to reduce time delay for IP address configuration in the new PoA. Implementation and evaluation results show that the proposed mechanism can be an acceptable network configuration mechanism for providing seamless television watching in IPv6 mobile networks, even when in motion.

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In this paper, we investigate the user scheduling algorithms with statistical eigen-mode transmission (SET) for downlink multiuser multiple-input multiple-output (MU-MIMO) system by utilizing the statistical channel state information (SCSI). Given the objective of maximizing the ergodic achievable sum rate per group (EASRPG), our first proposal, the Munkres user assignment algorithm (MUAA), solves the optimal user grouping problem. Different from the conventional user grouping algorithm (e.g. max-min method), MUAA can efficiently solve the user assignment problem and acquire an optimal solution. However, some user groups of the optimal solution called “unfriendly” groups severely degrade the EASRPG by performing the multiuser SET (MU-SET) due to excessive inter-user interference. To overcome this obstacle, the MUAA with sequential iterative separation (MUAA-SIS) is proposed to find the “unfriendly” groups and switch from the MU-SET to the single-user SET. Finally, our numerical results show that MUAA-SIS offers a higher EASRPG.

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In this letter, we propose a novel precoding scheme for base station (BS) cooperation in downlink cellular networks that allow overlapped clusters. The proposed precoding scheme is designed to mitigate the overlapping-BS interference by maximizing the so-called clustered virtual signal-to-interference-plus-noise ratio (CVSINR). Simulations show that with the proposed scheme, overlapped clustering provides substantial throughput gain over the traditional non-overlapped clustering methods, and user fairness is also improved.

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This paper proposes a scheme for fairness between uplink and downlink in error-prone 802.11 DCF WLANs by differentiating the contention window of AP. While existing schemes consider only collision, the proposed scheme takes into account packet error due to poor channel condition, too. Instead of complex analytical models based on Markov chain processes, a simpler model based on mean value analysis is proposed. It works on 802.11 DCF and so avoids being dependent on TXOP which lacks applicability. A performance evaluation shows that the proposed method can achieve fairness even in error-prone environments without decrease of total throughput when compared with existing schemes.

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The traditional selection cooperation scheme selects the relay with best instantaneous receive signal-to-noise ratio to forward the message and achieves good outage performance, which may however cause poor fairness among relays. In this letter, we propose two practical selection cooperation schemes in Decode-and-Forward (DF) fashion to improve the fairness of relay selection. Numerical results suggest that both of the proposed schemes can achieve fairness close to the strict fairness scheme without outage performance deterioration. It is also validated that these schemes have lower complexities than traditional ones and therefore are practical for real networks.

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In spectrum sharing cognitive radio (CR) networks, secondary user (SU) is allowed to share the same spectrum band concurrently with primary user (PU), with the condition that the SU causes no harmful interference to the PU. In this letter, the ergodic and outage capacity loss constraints are proposed to protect the PU according to its service types. We investigate the performance of the SU in terms of ergodic capacity under various power allocation policies of the PU. Specifically, three PU power allocation policies are considered, namely waterfilling, truncated channel inversion with fixed rate (TIFR) and constant power allocation. We obtain the ergodic capacities of the SU under the three PU power allocation policies. The numerical results show that the PU waterfilling and TIFR power allocation policies are superior to the PU constant power allocation in terms of the capacity of the PU. In particular, it is shown that, with respect to the ergodic capacity of the SU, the PU waterfilling power allocation is superior to the PU constant power allocation, while the PU TIFR power allocation is inferior to the PU constant power allocation.

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IEEE 802.11ac uses DL MU-MIMO and channelization for very high throughput. We propose a new algorithm for adaptive channelization in DL MU-MIMO WLANs. The proposed scheme can enhance the throughput efficiency for DL MU-MIMO transmission by adaptively applying the channelization scheme according to data size and MCS. Moreover, our proposal can reduce the overhead due to the exchange of control frames for DL MU-MIMO transmission in WLANs. A performance evaluation shows that the proposed scheme is superior to IEEE 802.11ac WLAN.

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In OFDM-based cognitive radio systems, due to the out-of-band leakage from the secondary transmission, the interference to primary users must be considered in order to guarantee the quality of service of the primary transmission. For multiuser cognitive radio systems, there exist two crucial issues in resource allocation: fairness and efficiency, in order to balance the two issues, we proposed a new utility-based cross-layer resource allocation algorithm, which can not only control the interference to primary users caused by secondary users, but also balance the spectral efficiency and fairness among cognitive users. Further, the optimal NP-hard resource allocation problem in multiuser OFDM-based systems is reduced to the sub-optimal solution by dividing the original problem into the subcarrier allocation problem and the power allocation problem. It is shown that the proposed algorithm can obtain the best performance in terms of the average rate or the utility among existing algorithms, and at the same time, all the users obtain fair resource allocation.

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