We have proposed a quality of experience (QoE)-oriented wireless local area network (WLAN) to provide sufficient QoE to important application flows. Unlike ordinary IEEE 802.11 WLAN, the proposed QoE-oriented WLAN dynamically performs admission control with the aid of the prediction of a “loadable capacity” criterion. This paper proposes an algorithm for dynamic network reconfiguration by centralized control among multiple basic service sets (BSSs) of the QoE-oriented WLAN, in order to maximize the number of traffic flows whose QoE requirements can be satisfied. With the proposed dynamic reconfiguration mechanism, stations (STAs) can change access point (AP) to connect. The operating frequency channel of a BSS also can be changed. These controls are performed according to the current channel occupancy rate of each BSS and the required radio resources to satisfy the QoE requirement of the traffic flow that is not allowed to transmit its data by the admission control. The effectiveness of the proposed dynamic network reconfiguration is evaluated through indoor experiments with assuming two cases. One is a 14-node experiment with QoE-oriented WLAN only, and the other is a 50-node experiment where the ordinary IEEE 802.11 WLAN and the QoE-oriented WLAN coexist. The experiment confirms that the QoE-oriented WLAN can significantly increase the number of traffic flows that satisfy their QoE requirements, total utility of network, and QoE-satisfied throughput, which is the system throughput contributing to satisfy the QoE requirement of traffic flows. It is also revealed that the QoE-oriented WLAN can protect the traffic flows in the ordinary WLAN if the border of the loadable capacity is properly set even in the environment where the hidden terminal problem occurs.

In recent times, wireless Local Area Networks (wireless LANs) based on the IEEE 802.11 standard have been spreading rapidly, and connecting to the Internet using wireless LANs has become more common. In addition, public wireless LAN service areas, such as train stations, hotels, and airports, are increasing and tethering technology has enabled smartphones to act as access points (APs). Consequently, there can be multiple APs in the same area. In this situation, users must select one of many APs. Various studies have proposed and evaluated many AP selection methods; however, existing methods do not consider AP mobility. In this paper, we propose an AP selection method based on cooperation among APs and user movement. Moreover, we demonstrate that the proposed method dramatically improves throughput compared to an existing method.

A cognitive radio user (CU) can get assistance from sensor nodes (SN) to perform spectrum sensing. However, the SNs are often powered by a finite-capacity battery, which can maintain operations of the SNs over a short time. Therefore, energy-efficiency of the SNs becomes a crucial problem. In this paper, an SN is considered to be a device with an energy harvester that can harvest energy from a non-radio frequency (non-RF) energy resource while performing other actions concurrently. In any one time slot, in order to maintain the required sensing accuracy of the CR network and to conserve energy in the SNs, only a small number of SNs are required to sense the primary user (PU) signal, and other SNs are kept silent to save energy. For this, an algorithm to divide all SNs into groups that can satisfy the required sensing accuracy of the network, is proposed. In a time slot, each SN group can be assigned one of two actions: stay silent, or be active to perform sensing. The problem of determining the optimal action for all SN groups to maximize throughput of the CR network is formulated as a framework of a partially observable Markov decision process (POMDP), in which the effect of the current time slot's action on the throughput of future time slots is considered. The solution to the problem, that is the decision mode of the SN groups (i.e., active or silent), depends on the residual energy and belief of absence probability of the PU signal. The simulation results show that the proposed scheme can improve energy efficiency of CR networks compared with other conventional schemes.

Throughput capacity is of great importance for the design and performance optimization of mobile ad hoc networks (MANETs). We study the exact per node throughput capacity of MANETs under a general 2HR-(g, x, f) routing scheme which combines erasure coding and packet replication techniques. Under this scheme, a source node first encodes a group of g packets into x (x ≥ g) distinct coded packets, and then replicates each of the coded packets to at most f relay nodes which help to forward them to the destination node. All original packets can be recovered once the destination node receives any g distinct coded packets of the group. To study the throughput capacity, we first construct two absorbing Markov chain models to depict the complicated packet delivery process under the routing scheme. Based on these Markov models, an analytical expression of the throughput capacity is derived. Extensive simulation and numerical results are provided to verify the accuracy of theoretical results on throughput capacity and to illustrate how system parameters will affect the throughput capacity in MANETs. Interestingly, we find that the replication of coded packets can improve the throughput capacity when the parameter x is relatively small.

A distributed antenna system, where the antennas of a base station are spatially distributed throughout the cell, can achieve better throughput at the cell edge than a centralized antenna system. On the other hand, the peak throughput degrades in general because each remote antenna unit has only a few antennas. To achieve both high peak and cell-edge throughputs, we need to increase the total number of antennas. However, this is not easy due to the pilot resource limitation when we use frequency division duplexing. In this paper, we propose using more antennas than pilot resources. The number mismatch between antennas and signals is solved by using a connection matrix. Here, we test two types of connection matrix: signal-distributing and signal-switching. Simulation results show that the sum throughput is improved by increasing the number of antenna elements per remote antenna unit under a constraint on the same number of pilot resources.

At present, wireless local area networks (WLANs) based on IEEE802.11 are widely deployed in both private premises and public areas. In a public environment offering several access points (APs), a station (STA) needs to choose which AP to associate with. In this paper, we propose a distributed association control scheme with user guidance to increase users' utility based on uplink and downlink throughputs of individual stations. As part of the scheme, we also present a simple throughput estimation method that considers physical data rate, traffic demand, and frame length in both uplink and downlink. Basically, in the proposed scheme, an AP selects a user and suggests that the user moves to another AP if certain conditions are met. The user then decides whether to accept the suggestion or not in a self-interested manner or in a voluntary manner for the benefit of all users including the user's own self. Through simulations under this condition, we confirm that our distributed association control scheme can improve user utility and fairness even though the channel quality of the new AP is unknown in advance.

This work investigates the physical layer security for three cooperative automatic-repeat-request (CARQ) protocols, including the decode-and-forward (DF) CARQ, opportunistic DF (ODF) CARQ, and the distributed space-time code (DSTC) CARQ. Assuming that there is no instantaneous channel state information (CSI) of legitimate users' channel and eavesdropper's channel at the transmitter, the connection outage performance and secrecy outage performance are derived to evaluate the reliability and security of each CARQ protocol. Then, we redefine the concept of the secrecy throughput to evaluate the overall efficiency of the system in terms of maintaining both reliable and secure transmission. Furthermore, through an asymptotic analysis in the high signal-to-noise ratio (SNR) regime, the direct relationship between reliability and security is established via the reliability-security tradeoff (RST). Numerical results verify the analysis and show the efficiency of the CARQ protocols in terms of the improvement on the secrecy throughput. More interestingly, increasing the transmit SNR and the maximum number of transmissions of the ARQ protocols may not achieve a security performance gain. In addition, the RST results underline the importance of determining how to balance the reliability vs. security, and show the superiority of ODF CARQ in terms of RST.

In this paper, an energy harvesting architecture in an Underlay Cooperative Cognitive Network (UCCN) is investigated, in which power constrained Decode-and-Forward relays harvest energy from radio-frequency signals received from a source, and then consume the harvested energy by forwarding the recoded signals to their destination. These recoded signals are launched by a transmitting power which is the harvested energy per a time interval. Based on the energy harvesting architectures that have been studied, two operation protocols are proposed: UCCN with Power Splitting architecture (UCCN-PS), and UCCN with Time Switching architecture (UCCN-TS). The best cooperative relay in both protocols is taken to be the one that satisfies the following conditions: maximum harvested energy, and maximum decoding capacity. As a result of the best relay selection, the signal quality of the selected link from the best relay to the destination is enhanced by the maximum harvested energy. The system performance of the secondary network in the UCCN-PS and UCCN-TS protocols is analyzed and evaluated by the exact closed-form outage probabilities and throughput analyses over Rayleigh fading channels. The Monte Carlo simulation method is performed to verify the theoretical expressions. Evaluations based on outage probability and throughput show that the system performance of the secondary network in the UCCN-PS and UCCN-TS protocols improves when the number of cooperative relays and the interference constraint increase as well as when the primary receiver is farther from the transmitting nodes such as the source and relays of the secondary network. In addition, the throughput performance of the UCCN-PS protocol outperforms that of the UCCN-TS protocol. Finally, the effects of the power splitting ratio, energy harvesting time, energy conversion efficiency, target Signal-to-Noise Ratio (SNR), and location of cooperative relays on the system performance of the secondary network are presented and discussed.

In this paper, we propose a new cross-layer scheme Cooperation between channel Access control and TCP Rate Adaptation (CATRA) aiming to manage TCP flow contention in multi-hop ad hoc networks. CATRA scheme collects useful information from MAC and physical layers to estimate channel utilization of the station. Based on this information, we adjust Contention Window (CW) size to control the contention between stations. It can also achieve fair channel access for fair channel access of each station and the efficient spatial channel usage. Moreover, the fair value of bandwidth allocation for each flow is calculated and sent to the Transport layer. Then, we adjust the sending rate of TCP flow to solve the contention between flows and the throughput of each flow becomes fairer. The performance of CATRA is examined on various multi-hop network topologies by using Network Simulator (NS-2).

This paper presents a prediction model based on historical data to achieve optimal values of pipelining, concurrency and parallelism (PCP) in GridFTP data transfers in Cloud systems. Setting the correct values for these three parameters is crucial in achieving high throughput in end-to-end data movement. However, predicting and setting the optimal values for these parameters is a challenging task, especially in shared and non-predictive network conditions. Several factors can affect the optimal values for these parameters such as the background network traffic, available bandwidth, Round-Trip Time (RTT), TCP buffer size, and file size. Existing models either fail to provide accurate predictions or come with very high prediction overheads. The author shows that new model based on historical data can achieve high accuracy with low overhead.

Computer systems with GPUs are expected to become a strong methodology for high-speed encryption processing. Moreover, power consumption has remained a primary deterrent for such processing on devices of all sizes. However, GPU vendors are currently announcing their future roadmaps of GPU architecture development: Nvidia Corp. promotes the Kepler architecture and AMD Corp. emphasizes the GCN architecture. Therefore, we evaluated throughput and power efficiency of three 128-bit block ciphers on GPUs with recent Nvidia Kepler and AMD GCN architectures. From our experiments, whereas the throughput and per-watt throughput of AES-128 on Radeon HD 7970 (2048 cores) with GCN architecture are 205.0Gbps and 1.3Gbps/Watt respectively, those on Geforce GTX 680 (1536 cores) with Kepler architecture are, respectively, 63.9Gbps and 0.43Gbps/W; an approximately 3.2 times throughput difference occurs between AES-128 on the two GPUs. Next, we investigate the reasons for the throughput difference using our micro-benchmark suites. According to the results, we speculate that to ameliorate Kepler GPUs as co-processor of block ciphers, the arithmetic and logical instructions must be improved in terms of software and hardware.

In cognitive radio networks, the dynamic traffic of the primary user can lead to not only the spectrum sensing performance degradation, but also co-channel interference between primary user and secondary user, and, furthermore, the secondary system throughput can be decreased. Taking into account the impact of the dynamic primary-user traffic on spectrum sensing performance and the secondary throughput, we study the optimization problem of maximizing the secondary throughput under the constraints of probability of detection, average interference and transmit power budget, and derive its optimal solution. The optimal power allocation scheme and the algorithm that can find the optimal sensing time are also proposed. The proposed algorithm is of great practical significance in the scenario where primary-user traffic varies very quickly, for example, in public safety spectrum band.

The throughput rate of Viterbi decoding (VD) is not limited by the speed of functional units when look-ahead computation techniques are used. The disadvantages of the look-ahead computation in VD are the hardware complexity and the decode latency. In this paper, implementation methods of the look-ahead ACS computation are proposed to improve the hardware efficiency and reduce the latency where the hardware efficiency and the latency can be balanced with a single parameter.

This paper addresses the sensing-throughput tradeoff problem by using cluster-based cooperative spectrum sensing (CSS) schemes in two-layer hierarchical cognitive radio networks (CRNs) with soft data fusion. The problem is formulated as a combinatorial optimization problem involving both discrete and continuous variables. To simplify the solution, a reasonable weight fusion rule (WFR) is first optimized. Thus, the problem devolves into a constrained discrete optimization problem. In order to efficiently and effectively resolve this problem, a lexicographical approach is presented that solving two optimal subproblems consecutively. Moreover, for the first optimal subproblem, a closed-form solution is deduced, and an optimal clustering scheme (CS) is also presented for the second optimal subproblem. Numerical results show that the proposed approach achieves a satisfying performance and low complexity.

The capacity of general mobile ad hoc networks (MANETs) remains largely unknown up to now, which significantly hinders the development and commercialization of such networks. Available throughput capacity studies of MANETs mainly focus on either the order sense capacity scaling laws, the exact throughput capacity under a specific algorithm, or the exact throughput capacity without a careful consideration of critical wireless interference and transmission range issues. In this paper, we explore the exact throughput capacity for a class of MANETs, where we adopt group-based scheduling to schedule simultaneous link transmissions for interference avoidance and allow the transmission range of each node to be adjusted. We first determine a general throughput capacity upper bound for the concerned MANETs, which holds for any feasible packet delivery algorithm in such networks. We then prove that the upper bound we determined is just the exact throughput capacity for this class of MANETs by showing that for any traffic input rate within the throughput capacity upper bound, there exists a corresponding two-hop relay algorithm to stabilize such networks. A closed-form upper bound for packet delay is further derived under any traffic input rate within the throughput capacity. Finally, based on the network capacity result, we examine the impacts of transmission range and node density upon network capacity.

In a multihop wireless network, wireless interference is a crucial factor in the maximum multiflow (MMF) problem, which studies the maximum throughput between multiple pairs of sources and sinks with a link schedule to support it. In this paper, we observe that network coding could help to decrease the impact of wireless interference, and thus propose a framework to study the MMF problem for multihop wireless networks with network coding. Firstly, a network model is established to describe the new conflict relations and schedulability modified by network coding. Next, we formulate the MMF problem to compute the maximum throughput of multiple unicast flows supported by the multihop wireless network with network coding, and show that its capacity region could be enlarged by performing network coding. Finally, we show that determining the capacity region of a multihop wireless network with network coding is an NP-hard problem, and thus propose a greedy heuristic algorithm, called coding-first collecting (CFC), to determine a capacity subregion of the network. We also show that finding an optimal hyperarc schedule to meet a given link demand function is NP-hard, and propose a polynomial algorithm, called coding-first scheduling (CFS), to find an approximate fractional hyperarc schedule in the multihop wireless network with network coding. A numerical analysis of a grid wireless network and a random wireless network is presented to demonstrate the efficiencies of the CFC algorithm and the CFS algorithm based on the framework.

This paper presents a hardware design of high throughput, low latency preamble detector for 3GPP LTE physical random access channel (PRACH) receiver. The presented PRACH receiver uses the pipelined structure to improve the throughput of power delay profile (PDP) generation which is executed multiple times during the preamble detection. In addition, to reduce detection latency, we propose an instantaneous preamble detection method for both restricted and unrestricted set. The proposed preamble detection method can detect all existing preambles directly and instantaneously from PDP output while conducting PDP combining for restricted set. The PDP combining enables the PRACH receiver to detect preambles robustly even in severe Doppler effect or frequency error exist. Using proposed method, the worst case preamble detection latency time can be less than 1 ms with 136 MHz clock and the proposed PRACH receiver can be implemented with approximately 237k equivalent ASIC gates count or occupying 30.2% of xc6vlx130t FPGA device.

IEEE802.11 Wireless Local Area Networks (WLANs) are becoming more and more pervasive due to their simple channel access mechanism, Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA), but this mechanism provides all nodes including Access Point and other Stations with the same channel access probability. This characteristic does not suit the infrastructure mode which has so many downlink flows to be transmitted at the Access Point that congestion at the Access Point is more likely to occur. To resolve this asymmetry traffic problem, we develop an Optimal Contention Window Adjustment method assuming the condition of erroneous channels over WLANs. This method can be easily implemented and is compatible with the original CSMA/CA mechanism. It holds the ratio of downlink and uplink flows and at the same time achieves the maximum saturation throughput in the WLANs. We use the Markov Chain analytical model to analyze its performance and validate it through the simulations.

We show an improved throughput scaling law for an ultra-wide band (UWB) ad hoc network by using a modified hierarchical cooperation (HC) strategy; the n wireless nodes are assumed to be randomly sited. In a dense network of unit area, our result indicates that the derived throughput scaling depends on the path-loss exponent α for certain operating regimes due to the power-limited characteristics. It also turns out that the use of HC is helpful in improving the throughput scaling of our UWB network in some conditions. More specifically, assuming that the bandwidth scales faster than nα+1(log n)α/2, it is shown that the HC protocol outperforms nearest multi-hop routing for 2 < α < 3 while using nearest multi-hop routing leads to higher throughput for α ≥ 3.

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.