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Recently, the combination of cognitive radio networks with the nonorthogonal multiple access (NOMA) approach has emerged as a viable option for not only improving spectrum usage but also supporting large numbers of wireless communication connections. However, cognitive NOMA networks are unstable and vulnerable because multiple devices operate on the same frequency band. To overcome this drawback, many techniques have been proposed, such as optimal power allocation and interference cancellation. In this paper, we consider an approach by which the secondary transmitter (STx) is able to find the best licensed channel to send its confidential message to the secondary receivers (SRxs) by using the NOMA technique. To combat eavesdroppers and achieve reasonable performance, a power allocation policy that satisfies both the outage probability (OP) constraint of primary users and the security constraint of secondary users is optimized. The closed-form formulas for the OP at the primary base station and the leakage probability for the eavesdropper are obtained with imperfect channel state information. Furthermore, the throughput of the secondary network is analyzed to evaluate the system performance. Based on that, two algorithms (i.e., the continuous genetic algorithm (CGA) for CR NOMA (CGA-CRN) and particle swarm optimization (PSO) for CR NOMA (PSO-CRN)), are applied to optimize the throughput of the secondary network. These optimization algorithms guarantee not only the performance of the primary users but also the security constraints of the secondary users. Finally, simulations are presented to validate our research results and provide insights into how various factors affect system performance.

Low power wide area network (LPWAN) technologies have become an integral part of Internet-of-Things (IoT) applications due to their ability to meet key requirements such as long range, low cost, massive device numbers, and low energy consumption. Among all available LPWAN technologies, LoRaWAN has garnered significant interest from both industry and academia. Due to wide communication range of LoRaWAN, the coverage of gateway (GW) may overlap and the packet transmissions from nodes in the overlapping area would collide, which deteriorates the network performance. How to tune the backoff parameter settings to reduce collision and maximize the network throughput in multi-GW LoRaWAN is still an open issue. To solve this issue, in this paper, we first propose a low-complexity model for multi-GW LoRaWAN, which divides nodes into different groups based on GWs they can communicate with. Key performance metrics, i.e., the network throughput, access delay and the probability of successful transmission, are derived as functions of backoff parameter and input rate. As the throughput performance crucially depends on whether each group is saturated or not, we propose an iterative algorithm to analyze the stability of the multi-GW LoRaWAN, based on which we further develop an iterative algorithm to tune the backoff parameter of each group iteratively for the network throughput optimization. The simulation results validate the effectiveness of the proposed algorithms and reveal the trade-off between fairness and efficiency.

Network densification has led to a renewed emphasis on means to improve aggregate network throughput for next-gen (High Efficiency) WLANs. The introduction of BSS color feature in support of enhanced spatial reuse sets IEEE 802.11ax apart from legacy WLAN. BSS color enables stations within a network to identify whether a transmission originates from an overlapped BSS and provides an option for mitigating the exposed node problem by allowing it to transmit (over the on-going OBSS transmission) albeit with reduced transmit power. As a result, distances between networks can be reduced, thereby improving the area spectral efficiency. To the best of our knowledge, this is the first work to develop an analytical model for IEEE 802.11ax spatial reuse that provides useful rules for optimizing network area throughput. We show that the spatial reuse gain is tightly linked to the interference range properties of each BSS in the network. Further, the analytical model predictions are validated and expanded via definitive ns-3 simulation results exploiting a recently concluded upgrade to 802.11 WLAN network stack (that implemented the necessary spatial reuse features). [ABSTRACT FROM AUTHOR]

Nowadays, network softwareization is an emerging techno-economic transformation trend that significantly impacts how enterprises deploy their network services. As an essential technology in this trend, Network Function Virtualization (NFV) enables scalable and inexpensive network services by flexibly instantiating Virtualized Network Functions (VNFs) on commercial-off-the-shelf devices. In this paper, we focus on the VNF placement problem in NFV-enabled networks, aiming to maximize the number of accepted Service Function Chain Requests (SFCRs) while guaranteeing their delay requirements. To improve resource utilization efficiency, we take account of Fundamental Resource Overheads (FROs) and the shareability of VNF instances. We mathematically formulate the VNF placement problem and propose the Throughput Optimization and Delay Guarantee (TO-DG) heuristic solution, consisting of an affinity-based SFCR mapping algorithm and a VNF request adjustment algorithm. The evaluation results show that the performance of TO-DG is near to results derived by ILP solver for small scale problems. Moreover, TO-DG obtains higher network throughput than contrasting schemes in different scenarios and significantly improves network resource utilization. [ABSTRACT FROM AUTHOR]

Timing violations in high performance communication channels in system-on-chips (SoC) may occur in the late stages of the physical design process. To address that, latency insensitive systems (LISs) employ pipelining in the communication channels through the insertion of relay stations. Although the functionality of an LIS is robust with respect to the communication latencies, imbalances in relay station insertion may degrade the throughput of the system. While having a large number of buffer queues can eliminate such performance loss, the system may not have adequate area to accommodate these buffers. The problem of buffer queue sizing for maximizing throughput while meeting buffer area constraints has been solved using a mixed-integer linear program (MILP) formulation; however, such an approach is not scalable. In this work, we formulate the buffer queue sizing problem as a parameterized graph optimization problem where for every communication channel there is a parameterized edge with buffer counts as the edge weight. We then use a minimum cycle mean algorithm to determine from which edges buffers can be removed safely. Experimental results on large LISs suggest that the proposed approach is scalable. Moreover, quality of the solutions, in terms of the throughput and the size of buffer queues, is observed to be as good as that of the MILP-based approach. [ABSTRACT FROM AUTHOR]

The paper is the first work that considers a constrained feedback control strategy to navigate an unmanned aerial vehicle (UAV) from a given starting point to a given terminal point while harvesting solar energy and providing a wireless communication service for ground users. Wireless communication channels are stochastic and cannot be known off-line, making the problem of off-line UAV path planning for wireless communication as considered in most existing works less meaningful. We consider the problem of navigating a solar-powered UAV from a starting point to a terminal point to harvest solar energy while serving the two-way communication between multiple pairs of ground users in a complex terrain. The objective is to jointly optimize the UAV’s flight time and its flight path by trading-off between the harvested energy and power consumption subject to the ground users’ minimum throughput requirement. We develop a new model predictive control (MPC) technique to address this problem. Namely, based on the well-known statistics of the air-to-ground (A2G) and ground-to-air (G2A) wireless channels, a predictive control model is proposed at each time-instant, which leads to an optimization problem over a receding horizon for the control design. This problem is non-convex due to the involvement of various optimization variables, which is then solved via novel convex iterations. Simulation results show the merits of the proposed algorithm. The results obtained by the proposed algorithm match with the benchmark non-MPC and offline-MPC approaches. [ABSTRACT FROM AUTHOR]

This paper studies a full-duplex symbiotic radio network, where a full-duplex access point (FAP) transmits downlink orthogonal frequency division multiplexing signals to a legacy user (LU) and simultaneously receives signals backscattered from multiple passive backscatter devices (BDs) with capability of radio-frequency energy harvesting. A non-orthogonal-multiple-access enhanced dynamic-time-division-multiple-access (NOMA-DTDMA) transmission scheme is proposed to exploit the channel dynamics and further improve the spectrum efficiency. In order to maximize the throughput performance and ensure BD fairness, we maximize the minimum throughput among all BDs by jointly optimizing the FAP's subcarrier power allocation, the BDs' backscatter time allocation and power reflection coefficients, subject to the LU's throughput requirement, the BDs' harvested energy requirements, and other practical constraints. An efficient iterative algorithm is proposed to solve the formulated non-convex problem, by utilizing the block coordinated descent and successive convex optimization techniques. The convergence and complexity of the proposed algorithm are also analyzed. Numerical results show that the proposed NOMA-DTDMA scheme significantly outperforms the benchmark scheme of dynamic TDMA in terms of both throughput performance and BD fairness. Also, the trade-off performances between the BDs' throughput and the LU's throughput requirement as well as the BDs' harvested energy requirements are numerically verified.

A significant number of processing cores in any many-core systems nowadays and likely in the future have to be switched off or forced to be idle to become dark cores, in light of ever increasing power density and chip temperature. Although these dark cores cannot make direct contributions to the chip's throughput, they can still be allocated to applications currently running in the system for the sole purpose of heat dissipation enabled by the temperature gradient between the active and dark cores. However, allocating dark cores to applications tends to add extra waiting time to applications yet to be launched, which in return can have adverse implications on the overall system performance. Another big issue related to dark core allocation stems from the fact that application characteristics are prone to undergo rapid changes at runtime, making a fixed dark core allocation scheme less desirable. In this paper, a runtime dark core allocation and dynamic adjustment scheme is thus proposed. Built upon a dynamic programming network (DPN) framework, the proposed scheme attempts to optimize the performance of currently running applications and simultaneously reduce waiting times of incoming applications by taking into account both thermal issues and geometric shapes of regions formed by the active/dark cores. The experimental results show that the proposed approach achieves an average of 61% higher throughput than the two state-of-the-art thermal-aware runtime task mapping approaches, making it the runtime resource management of choice in many-core systems.

Unmanned aerial vehicle (UAV)-aided two-way relaying networks are designed, where a UAV is deployed to assist multiple pairs of users in their information exchange. There are two basic approaches for the user pairs’ information exchange within a single time slot via the UAV relay. The first approach is based on full-duplex, where all participants operate in the full-duplex mode to transmit and receive signals simultaneously. However, all transceivers have to operate in the face of severe self-interference, which cannot be completely suppressed. The second approach is based on conventional half-duplex, where the users send their information to the UAV within a certain fraction of the time slot, and the UAV relays them within the remaining fraction to avoid the self-interference. In either approach, the joint bandwidth and power allocation maximizing the sum information exchange throughput under realistic resource and user throughput constraints poses a complex nonconvex problem. New inner approximations are proposed for developing path-following algorithms for their computation. Our numerical results show that the time-fraction-based half-duplex approach clearly outperforms the high-complexity full-duplex approach. [ABSTRACT FROM AUTHOR]

In this letter, we propose an energy harvesting (EH) based incremental relaying cooperative non-orthogonal multiple access (IR-EH-NOMA) protocol, considering two user downlink network. We derive analytical expressions for the system throughput of IR-EH-NOMA network and conventional cooperative relaying NOMA network with EH (CR-EH-NOMA network) in the delay limited transmission mode, considering imperfect successive interference cancellation (i-SIC) and maximal ratio combining (MRC). We also derive expressions for the optimal power splitting (OPS) factors at the relay that maximizes the asymptotic throughput of the considered systems. Numerical and simulation results are described to establish the supremacy of IR-EH-NOMA system over CR-EH-NOMA system in terms of outage and throughput. [ABSTRACT FROM AUTHOR]

D2D communications are considered as effective means to achieve vehicle-to-vehicle (V2V) communications, which can be used to improve the performance in vehicular ad hoc networks (VANETs). In this paper, we investigate the resource allocation and interference management based on clustering mechanism in the D2D communications under-laying VANETs aiming to optimize resource utilization efficiency. Firstly, given the transmission resources of intra-cluster for D2D communications, we design a vehicle clustering algorithm to improve intra-cluster resource efficiency and nullify the intra-cluster interference. Secondly, by analyzing the wireless service in VANETs, a cooperative communication scheme with optimized resource utilization is proposed to maximize intra-cluster spectral efficiency. Thirdly, when uplink spectrums are shared, an interference neutralization (IN) model is developed to manage inter-cluster interference, while each vehicle is equipped with one antenna and there is no extra antenna for interference cancellation. In accordance with the IN model, a cross-layer optimization frame for multi-hop VANETs is proposed to maximize the end-to-end throughput of multiple coexisting communication sessions. To evaluate the performance, we select the method without cooperative communication and IN as a benchmark and compare it against the method with cooperative communication only and the method with both cooperative communication and IN. The simulation results show that the method that uses cooperative communication and IN can dramatically increase the throughput. Furthermore, the throughput gains increase along with vehicle density growing in VANETs. [ABSTRACT FROM AUTHOR]

LoRa is an extremely flexible low-power wide-area technology that enables each IoT node to individually adjust its transmission parameters. Consequently, the average per-node throughput of LoRa-based networks has been mathematically formulated and the optimal network-level configuration derived. For end nodes to update their transmission parameters, this centrally computed global configuration must then be disseminated by LoRa gateways. Unfortunately, the regional limitations imposed on the usage of ISM bands—especially those related to the maximum utilization of the band—pose a potential handicap to this parameter dissemination. To solve this problem, a set of tools from the machine learning field have been used. Precisely, the updating process has been formulated as a reinforcement learning (RL) problem whose solution prescribes optimal disseminating policies. The use of these policies together with the optimal network configuration has been extensively analyzed and compared to other well-established alternatives. Results show an increase of up to 147% in the accumulated per-node throughput when our RL-based approach is employed. [ABSTRACT FROM AUTHOR]

Interference neutralization (IN) is regarded as a promising interference management techniques for multi-hop wireless networks. Yet most existing results of IN are limited to two-hop networks such as the relay-aided cellular network. Little progress has been made so far in the exploration of IN in generic multi-hop (more than two hops) networks. This paper aims to bridge this gap by developing an optimization framework for IN in a generic multi-hop network with the objective of maximizing the end-to-end throughput of multiple coexisting communication sessions. We first derive a mathematical model for IN in a special one-hop network to characterize the capability of IN, and then generalize this model to a multi-hop network. Based on the IN model, we develop a cross-layer optimization framework for a multi-hop network with the objective of fully translating the benefits of IN to the end-to-end throughput of the multi-hop sessions. To evaluate the performance of IN in multi-hop networks, we compare its performance against the case where IN is not employed. Simulation results show that the use of IN can significantly (more than 50%) increase the session throughput and, more notably, the throughput gain of IN increases with the node density and traffic intensity in the network. [ABSTRACT FROM PUBLISHER]

All the cores of a many-core chip cannot be active at the same time, due to reasons like low CPU utilization in server systems and limited power budget in dark silicon era. These free cores (referred to as bubbles) can be placed near active cores for heat dissipation so that the active cores can run at a higher frequency level, boosting the performance of applications that run on active cores. Budgeting inactive cores (bubbles) to applications to boost performance has the following three challenges. First, the number of bubbles varies due to open workloads. Second, communication distance increases when a bubble is inserted between two communicating tasks (a task is a thread or process of a parallel application), leading to performance degradation. Third, budgeting too many bubbles as coolers to running applications leads to insufficient cores for future applications. In order to address these challenges, in this paper, a bubble budgeting scheme is proposed to budget free cores to each application so as to optimize the throughput of the whole system. Throughput of the system depends on the execution time of each application and the waiting time incurred for newly arrived applications. Essentially, the proposed algorithm determines the number and locations of bubbles to optimize the performance and waiting time of each application, followed by tasks of each application being mapped to a core region. A Rollout algorithm is used to budget power to the cores as the last step. Experiments show that our approach achieves 50 percent higher throughput when compared to state-of-the-art thermal-aware runtime task mapping approaches. The runtime overhead of the proposed algorithm is in the order of 1M cycles, making it an efficient runtime task management method for large-scale many-core systems. [ABSTRACT FROM AUTHOR]

The wireless network that integrates a heterogeneous cellular network and a WLAN is referred to as a WLAN/cellular integrated network (WCIN). In a fourth generation WCIN, in order to achieve collision-avoidance between the LTE-A and IEEE 802.11 family, some interference-free mechanisms, such as carrier sense adaptive transmission and listen-before-talk, are proposed. However, the interference-free medium access mechanisms leave some unexploited partially overlapped 802.11ac channels, which result in a waste of spectrum. In this paper, we propose an interference-tolerant medium access method to optimize the WCIN throughput by utilizing those partially overlapped channels (POCs). First, we show the feasibility of enhancing WLAN throughput by utilizing 802.11ac POCs in a WCIN. Second, we mathematically model the partial overlap when an 802.11ac channel is partially overlapping with an LTE-A component carrier. Third, we propose an interference-tolerant medium access mechanism to optimize the WCIN throughput. The interference-tolerant one ensures that the interference to LTE-A users is tolerable in a given WCIN. Finally, we construct a hardware-in-the-loop testbed to evaluate and compare our proposed mechanism with three other state-of-the-art mechanisms. The experimental results show that our approach achieves at most 39% more throughput than one of the state-of-the-art collision-avoidance mechanisms regarding the entire WCIN. [ABSTRACT FROM PUBLISHER]

The growing demand for video content is reshaping our view of the current Internet, and mandating a fundamental change for future Internet paradigms. A current focus on Information-Centric Networks (ICN) promises a novel approach to intrinsically handling large content dissemination, caching and retrieval. While ubiquitous in-network caching in ICNs can expedite video delivery, a pressing challenge lies in provisioning scalable video streaming over adaptive requests for different bit rates. In this paper, we propose novel video caching schemes in ICN, to address variable bit rates and content sizes for best cache utilization. Our objective is to maximize overall throughput to improve the Quality of Service (QoS). In order to achieve this goal, we model the dynamic characteristics of rate adaptation, deriving caps on average delay, and propose DaCPlace which optimizes cache placement decisions. Building on DaCPlace, we further present a heuristic scheme, StreamCache, for low-overhead adaptive video caching. We conduct comprehensive simulations on NS-3 (specifically under the ndnSIM module). Results demonstrate how DaCPlace enables users to achieve the least delay per bit and StreamCache outperforms existing schemes, achieving near-optimal performance to DaCPlace . [ABSTRACT FROM PUBLISHER]

For IEEE 802.11 networks with multiple basic service sets (BSSs), most studies have focused on how to allocate different frequency sub-channels to BSSs for minimizing the co-channel interference. With the significant increase of the sub-channel bandwidth, however, it becomes increasingly important to study the network performance with universal frequency reuse. In this paper, we focus on an uplink $M$ -BSS IEEE 802.11 network, where all the BSSs share the frequency band rather than operate at different sub-channels. By dividing the nodes in each BSS into multiple groups according to the set of access points (APs) they can be heard by, the steady-state points of $M$ BSSs in saturated conditions are obtained as the functions of the number of nodes in each group and the initial backoff window size of nodes of each BSS. The maximum network throughput is further characterized by optimally choosing the initial backoff window sizes of all the nodes and shown to be closely dependent on the percentage of nodes that can be heard by multiple APs. The comparison with orthogonal frequency division reveals that although the maximum network throughput is degraded due to interference among BSSs, a higher network data rate can still be achieved by universal frequency reuse, which makes it a preferable option for multi-BSS IEEE 802.11 networks. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the performance of an analog network coding based two-way relay system with multiple-antenna source terminals and single-antenna energy harvesting (EH) relay. We consider time-switching relaying protocol to perform EH and information processing at the amplify and forward EH relay. Assuming that the multiple-antenna source with a better link beamforms energy to the relay, we derive expressions for the system outage, ergodic sum-rate, and sum symbol error rate. In the analysis, we take into account the sensitivity of the energy harvesting circuit. We investigate the problem of throughput maximization by optimizing the fraction $\alpha $ of time spent on EH, and derive closed-form expressions for optimum $\alpha $ in important special cases. We analyze the problem of relay location for fixed $\alpha $ , and show that the optimum location varies with source terminal antennas. We further show that joint optimization of relay location and $\alpha $ yields best throughput performance. We show through simulations that unlike throughput, the optimum $\alpha $ that maximizes the ergodic sum-rate does not show much variation with system parameters. Simulation results with practical parameter values demonstrate the accuracy of the derived analytical expressions. [ABSTRACT FROM PUBLISHER]

In this paper, the secure transmission strategy for a multi-input-single-output multi-eavesdropper system with coexistence of a secure user (Bob) and a normal user (NU) is investigated. The NU and Bob require normal and secure data transmissions, respectively, and thus, the stream for the NU can be exploited to confuse the eavesdroppers. To guarantee the security of Bob, artificial noise (AN) is also deliberately injected into the null space of Bob and NU. The power allocation among Bob, NU, and AN, as well as the wiretap code rates, is jointly optimized to maximize the effective secrecy throughput (EST), under the average throughput constraint of the NU and statistical channel state information (CSI) of eavesdroppers. Both non-adaptive and adaptive transmission schemes are proposed, based on the statistical and instantaneous CSI of the legitimate channels, respectively. An alternative optimization algorithm is proposed to obtain the optimal parameters. It is proved that the EST is a quasi-concave function of the secrecy rate and the power allocated to Bob, and for fixed wiretap code rates, the optimal power allocation is derived in a closed-form expression. Numerical results show that the EST increases with the increase in transmitting power and the number of transmit antennas, and decreases with the increasing throughput constraint of the NU. Improved EST can be achieved through injecting AN and concurrent transmission of Bob and NU. [ABSTRACT FROM PUBLISHER]

This paper studies the coexistence of heterogeneous multi-hop networks, which use different physical-layer technologies. We propose a new paradigm, called cooperative interference mitigation (CIM), which exploits recent advancement in interference cancellation (IC), such as technology-independent multiple output. CIM makes it possible for disparate networks to cooperatively mitigate the interference to/from each other to enhance everyone’s performance. We first show the feasibility of CIM among heterogeneous multi-hop networks by exploiting only channel-ratio information. Then, we establish two tractable models to characterize the CIM behaviors of both networks by using full IC and receiver-side IC only. We propose two bi-criteria optimization problems aiming at maximizing both networks’ throughput, while cooperatively canceling the interference between them based on our two models. Several simulations are carried out to compare the Pareto-optimal throughput curves by using our CIM paradigms and traditional interference-avoidance (IAV) paradigm. By comparing the results from CIM and IAV, we show that CIM could remarkably improve the coexisting networks’ throughput in different network settings. [ABSTRACT FROM PUBLISHER]

Wireless underground sensor networks (WUSNs) present a variety of new research challenges. Recently, a magnetoinductive (MI) waveguide technique has been proposed to cope with the very harsh propagation conditions in WUSNs. This relay-based approach allows for an extension of the transmission range, which can be quite limited if relays are not deployed. In this paper, tree-based WUSNs are considered. The objective of our work is to determine the optimal system parameters, topology, and deployment strategy in order to avoid bottlenecks in the system and achieve optimal network throughput. We compare two different deployment schemes: MI waveguides and direct MI transmission (no relays deployed) based connections between sensors. The two schemes are different in nature and propagation characteristics. Therefore, different optimization techniques are utilized. The optimal set of system parameters is chosen to maximize the channel capacity of the worst link and therefore optimize the available data rate. The bottleneck throughput of the direct MI transmission based network can be then compared with the respective results of the MI waveguides based network. In several cases, we observe a better performance of the direct MI transmission based networks. [ABSTRACT FROM AUTHOR]

We consider the problem of reliable spectrum sensing and opportunistic access on channels with stochastic traffic in batch processing systems such as network coding (NC). We show how a secondary user (SU) can leverage the structure induced by block-based NC on primary users' (PUs) channels to mitigate the effects of channel sensing errors and improve the detection of idle PU spectrum and the throughput. NC is known to improve the transmission efficiency and therefore when applied on a PU channel, it can extend the spectrum availability for the SUs. We refer to the additional gain of spectrum predictability from NC and show that under possible sensing errors the SU can more reliably detect the idle spectrum if the PUs' channels carry network-coded transmissions even when the channel utilization is fixed. We consider two different objectives at the SU. For quickest detection, the SU applies the Cumulative Summation (CUSUM) algorithm to detect idle slots on a PU channel and further improves the detection capability with the Viterbi algorithm, if the PU spectrum dynamics are known. For throughput maximization, the SU tracks the PU spectrum with the Partially Observable Markov Decision Process (POMDP) approach. Our results show that NC renders the spectrum more predictable, which can be used by the SUs to mitigate the effects of sensing errors and improve the throughput. We validate these results with real radio measurements taken in software-defined radio based wireless network tests. [ABSTRACT FROM AUTHOR]

This letter investigates the throughput optimization of multiple description coding multicast (MDCM) in cognitive radio networks (CRNs) by taking into account both statistical channel state information (CSI) and the interference from the primary network. A statistical-CSI-based MDCM scheme with low complexity is proposed, which is shown to be able to approach the perfect-CSI performance with large multicast group size. For comparison, conventional multicast (CM) is also analyzed. A tight upper bound is derived, which decays to zero rapidly when the multicast group size grows. Numerical results are also presented to validate the proposed scheme. [ABSTRACT FROM AUTHOR]

In wireless networks without nodes equipped with multiple antennas, cooperative Multiple Input Multiple Output (MIMO) transmissions may be used to harness diversity gains. In general, diversity gains are larger if more nodes are involved in the transmission. However, a transmission policy that maximizes the diversity gain or throughput need not maximize the stability region, since queues at the nodes may grow while waiting for a sufficient number of nodes to become available. To address this issue, this paper develops a mechanism for maximizing the throughput while reducing the energy consumption and maintaining queue stability. We develop a sufficient condition that ensures the throughput optimality of a stable transmission policy and then use it to design a distributed, dynamic threshold based Medium Access Control (MAC) protocol for cooperative MIMO transmissions. The MAC protocol requires only limited local information for its operation. Simulation results are provided to evaluate the performance of the proposed protocol and compare it against regular point-to-point and existing cooperative MIMO MAC protocols. The results show that the proposed scheme can provide considerable gains in the throughput and energy savings compared to cooperative MIMO based on fixed number of cooperating nodes. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a cross-layer scheduling algorithm that achieves a throughput “\epsilon-close” to the optimal throughput in multihop wireless networks with a tradeoff of O(1\over\epsilon) in average end-to-end delay guarantees. The algorithm guarantees finite buffer sizes and aims to solve a joint congestion control, routing, and scheduling problem in a multihop wireless network while satisfying per-flow average end-to-end delay constraints and minimum data rate requirements. This problem has been solved for both backlogged as well as arbitrary arrival rate systems. Moreover, we discuss the design of a class of low-complexity suboptimal algorithms, effects of delayed feedback on the optimal algorithm, and extensions of the proposed algorithm to different interference models with arbitrary link capacities. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the design of artificial-noise-aided secure multi-antenna transmission in slow fading channels. The primary design concerns include the transmit power allocation and the rate parameters of the wiretap code. We consider two scenarios with different complexity levels: 1) the design parameters are chosen to be fixed for all transmissions; and 2) they are adaptively adjusted based on the instantaneous channel feedback from the intended receiver. In both scenarios, we provide explicit design solutions for achieving the maximal throughput subject to a secrecy constraint, given by a maximum allowable secrecy outage probability. We then derive accurate approximations for the maximal throughput in both scenarios in the high signal-to-noise ratio region, and give new insights into the additional power cost for achieving a higher security level while maintaining a specified target throughput. In the end, the throughput gain of adaptive transmission over non-adaptive transmission is also quantified and analyzed. [ABSTRACT FROM PUBLISHER]

Compared to single-hop networks such as WiFi, multihop infrastructure wireless mesh networks (WMNs) can potentially embrace the broadcast benefits of a wireless medium in a more flexible manner. Rather than being point-to-point, links in the WMNs may originate from a single node and reach more than one other node. Nodes located farther than a one-hop distance and overhearing such transmissions may opportunistically help relay packets for previous hops. This phenomenon is called opportunistic overhearing/listening. With multiple radios, a node can also improve its capacity by transmitting over multiple radios simultaneously using orthogonal channels. Capitalizing on these potential advantages requires effective routing and efficient mapping of channels to radios (channel assignment (CA)). While efficient channel assignment can greatly reduce interference from nearby transmitters, effective routing can potentially relieve congestion on paths to the infrastructure. Routing, however, requires that only packets pertaining to a particular connection be routed on a predetermined route. Random network coding (RNC) breaks this constraint by allowing nodes to randomly mix packets overheard so far before forwarding. A relay node thus only needs to know how many packets, and not which packets, it should send. We mathematically formulate the joint problem of random network coding, channel assignment, and broadcast link scheduling, taking into account opportunistic overhearing, the interference constraints, the coding constraints, the number of orthogonal channels, the number of radios per node, and fairness among unicast connections. Based on this formulation, we develop a suboptimal, auction-based solution for overall network throughput optimization. Performance evaluation results show that our algorithm can effectively exploit multiple radios and channels and can cope with fairness issues arising from auctions. Our algorithm also shows promising gains over traditional routing solutions in which various channel assignment strategies are used. [ABSTRACT FROM PUBLISHER]

In this article, we investigate joint sensing block length and detection threshold optimization to maximize the throughput of a cognitive radio (CR) network with limited interference to the primary user (PU). The CR network operates on a frame-by-frame basis, where the status of the PU can change at any time within one frame. Through theoretical analysis, optimal solution is derived, which is helpful to system design. Numerical results show that higher throughput can be obtained by considering the PU status change than the case without considering it. [ABSTRACT FROM PUBLISHER]

This paper studies joint scheduling and network coding in wireless multicast networks with independent sources. Designing a network coding solution for wireless networks involves scheduling interference-free transmissions and optimizing a performance measure for the predetermined scheduling sets, followed by constructing network codes for the specific solution. In such a design process, the results of prior steps need to provide enough information to the subsequent steps. In this paper, we formulate a linear optimization problem whose results can be used to design a coding solution. We build our work on previous works and present statistics that show the importance of incorporating unequal timeshares in designing network codes. In particular, our statistics show a throughput improvement of about 35% in maximum flow problems and energy savings between 13% and 30%, depending on the network size, in minimum energy problems. We also present the requirements of code construction algorithms for wireless networks that capture the broadcast property of these networks and can design proper codes when timeshares are unequal. In particular, the adaptation of a centralized network coding scheme for wireless networks is discussed. Overall, the work reported here provides a three-step solution to derive network codes that optimize a performance criterion of interest while also solving the scheduling problem in multihop wireless networks. [ABSTRACT FROM PUBLISHER]

The throughput of conventional wireless multicast systems is limited by the multicast user with the lowest channel quality, which leads to a low throughput, particularly if the number of multicast users is large. In this paper, we show that hybrid-automatic repeat request with Chase combining (HARQ-CC) is a promising technique to overcome this problem and optimize the corresponding transmission rate. We analyze the throughput of wireless multicast systems with HARQ-CC under various channel conditions and derive a closed-form approximation for the optimal rate. The numerical evaluation of our analytical expressions reveals that HARQ-aided multicast outperforms conventional multicast in most channel environments. To further improve performance, we propose a dynamic rate-allocation scheme that combines the advantages of conventional multicast and HARQ-aided multicast. [ABSTRACT FROM PUBLISHER]

Single-Rate Data-Flow (SRDF) graphs, also known as Homogeneous Synchronous Data-Flow (HSDF) graphs or Marked Graphs, are often used to model the implementation and do temporal analysis of concurrent DSP and multimedia applications. An important problem in implementing applications expressed as SRDF graphs is the computation of the minimal amount of buffering needed to implement a static periodic schedule (SPS) that is optimal in terms of execution rate, or throughput. Ning and Gao [1] propose a linear-programming-based polynomial algorithm to compute this minimal storage amount, claiming optimality. We show via a counterexample that the proposed algorithm is not optimal. We prove that the problem is, in fact, NP-complete. We give an exact solution, and experimentally evaluate the degree of inaccuracy of the algorithm of Ning and Gao. [ABSTRACT FROM AUTHOR]

Herein, we present a novel approach for decode-forward relay transmissions using multiple antennas. In this approach, multiple independent spatial data streams are sent to the destination directly and/or through different relays simultaneously, where the relays are selected in an opportunistic way. We show the efficiency of the proposed approach through simulations. [ABSTRACT FROM AUTHOR]

This paper describes a fast and accurate technique to predict the steady-state throughput and the corresponding power consumption of a homogeneous multicore processor for a given benchmark workload while accounting for speed reduction due to thermal constraints. The expressions contain several parameters of interest to a system designer, like the static and dynamic-power consumptions (for hottest block and for full chip), the vertical thermal resistance of the hottest block, the leakage sensitivity to temperature, the chip threshold temperature, the ambient temperature, etc. Their computational complexity is independent of the number of cores. These are incorporated in a system-level multicore power/thermal simulator that uses the PTScalar power model and the Hotspot thermal model. The analytical throughput and power predictions were within 1.7 % of that predicted by the system-level simulator. However, the analytical technique takes less than 0.2 s for a given set of design parameters, making it well suited for early design-space exploration. In contrast, the numerical technique takes anywhere from a minute (for 4 cores) up to a few hours (for 25 cores). [ABSTRACT FROM AUTHOR]

Multi-hop ad hoc networks suffer from the "hidden" and "exposed" node problems which diminish aggregate network throughput. While there are various approaches to mitigating these problems, in this work we focus exclusively on the role of physical carrier sensing (PCS). Specifically, tuning the PCS threshold leads to a trade-off between the hidden and exposed cases; reducing one typically increases the other, implying the existence of an optimal PCS threshold setting maximizes the aggregate network throughput. The contributions of this work are two-fold: i. We develop an analytical model to determine the optimal PCS threshold for a homogeneous network with constant link distances and show that setting the carrier sensing range close to the interference range is a robust close-to-optimal setting for network optimization in many scenarios. As an extension to more pragmatic network topologies with non-uniform link distances, a rate-to-link allocation scheme is proposed based on rendering the interference range equal for all links that allows a single carrier sense range to be used for the whole network. ii. The above suggests the need for on-line adaptation of tunable PCS threshold in general. The proposed algorithm is based on the key concept of loss differentiation (LD), which disambiguates the cause of packet loss event due to link layer interference (hidden terminals) and collisions respectively. Extensive simulation results show that the proposed PCS adaptations make the PCS threshold converge to its optimal value and thus outperform schemes without PCS adaptation. [ABSTRACT FROM AUTHOR]

In time-varying faded channels the transmissions are organized into frames where the channel estimation is mainly training-based. The optimal design of the training structure is formulated here by finding the training length (the optimal number of contiguous pilots) and the training interval (the interval among two successive training phases) to maximize system throughput. The optimal balance of training and payload depends on the combination of Doppler frequency and frame length. The level of the signal to noise ratio and the fading dynamics constrain the quality of the estimate from training. It is shown that the length of the training can be conveniently traded for lower training intervals to reduce the estimate out-dating. For fast-varying fading and for high enough signal to noise ratio, there is a definite advantage in fragmenting the frame with dispersed segments of training symbols of smaller length rather than having a highly reliable channel estimate by concentrating all the training symbols at the beginning of the frame. Extensive simulations corroborate the design criteria. System throughput is maximized either for noisy binary transmission and for Gaussian input symbol distribution (i.e., by using information theoretic analysis). [ABSTRACT FROM AUTHOR]

Wireless relays extend coverage, improve spectral efficiency, and enhance reliability and rates of wireless cellular communication systems. In this work, we introduce the fundamental notion of asymmetric cooperation among cooperating relays in cellular downlinks - different relays are party to different but overlapping knowledge about the messages transmitted from the base station. We argue that asymmetric cooperation arises naturally in most two-phase protocols in which the base station first transmits information to multiple relays that then cooperatively forward the information to the recipient mobile stations in the cell. For a system in which two relays are of the decode-and-forward type and cooperate using linear precoding to communicate with two mobile stations, we formulate the general, but complicated, throughput optimization problem and derive several results that considerably simplify the optimization. We show that under different channel configurations and fairness criteria, asymmetric cooperation is often the throughput-maximizing option. Under typical configurations, a 20-30% throughput enhancement is achieved compared to conventional full-cooperation systems. [ABSTRACT FROM PUBLISHER]

Among various Bell Labs layered space-time (BLAST) architectures over multiple input multiple output (MIMO) channels, we focus on the horizontal BLAST (H- BLAST) transmission scheme as it can achieve the channel capacity with a simple receiver, namely the successive cancellation (SC) receiver. The power optimization across layers is considered with a short-term power constraint. In addition, for block- fading channels, the rate optimization across layers is studied to maximize the throughput when the instantaneous channel state information (CSI) is not available. Since the CSI is not available, the rates can be greater than the instantaneous channel capacity and error propagation in the SC receiver is inevitable. Thus, the rate optimization plays a key role in reducing the chance of error propagation to maximize the throughput. It is shown that the optimal rates can be obtained recursively and each optimization can be carried out by a one-dimensional search. [ABSTRACT FROM PUBLISHER]

In wireless networks, throughput optimization is an essential performance objective that cannot be adequately characterized by a single criterion (such as the minimum transmitted or sum-delivered throughput) and should be specified over all source-destination pairs as a rate region. For a simple and yet fundamental model of tandem networks, a cross-layer optimization framework is formulated to derive the maximum throughput region for saturated multicast traffic. The contents of network flows are specified through network coding (or plain routing) in network layer and the throughput rates are jointly optimized in medium access control layer over fixed set of conflict-free transmission schedules (or optimized over transmission probabilities in random access). If the network model incorporates bursty sources and allows packet queues to empty, the objective is to specify the stability region as the set of maximum throughput rates that can be sustained with finite packet delay. Dynamic queue management strategies are used to expand the stability region toward the maximum throughput region. Network coding improves throughput rates over plain routing and achieves the largest gains for broad- cast communication and intermediate network sizes. Throughput optimization imposes fundamental tradeoffs with transmission and processing energy costs such that the throughput-optimal operation is not necessarily energy efficient. [ABSTRACT FROM AUTHOR]

Digital Multimedia Broadcasting (DMB) is one of burgeoning communication technologies, which can provide audio, video, and data services to mobile terminals using broadcasting infrastructures. Data services in Terrestrial—Digital Multimedia Broadcasting (T-DMB) inherently have the disadvantage of retransmitting a lot of data unnecessarily for reliability. This paper proposes a novel optimized transmission policy using segment size and repetition number variability, which maximizes the object-level throughput as well as improves reliability. The theoretical modeling and simulation results demonstrate that our policy provides a throughput gain over the conventional protocol. [ABSTRACT FROM AUTHOR]

The broadcast scheduling problem (BSP) arises in frame design for packet radio networks (PRNs). The frame structure determines the main communication parameters: communication delay and throughput. The BSP is a combinatorial optimization problem which is known to be NP-hard. To solve it, we propose an algorithm with two main steps which naturally arise from the problem structure: the first one tackles the hardest contraints and the second one carries out the throughput optimization. This algorithm combines a Hopfield neural network for the constraints satisfaction and a genetic algorithm for achieving a maximal throughput. The algorithm performance is compared with that of existing algorithms in several benchmark cases; in all of them, our algorithm finds the optimum frame length and outperforms previous algorithms in the resulting throughput. [ABSTRACT FROM PUBLISHER]

This paper describes a method for increasing the batch-processing efficiency of medium and large scale scientific compute, systems with a small main memory. A program-replacement algorithm, RESEP, is defined whose goal is to always keep the CPU busy. RESEP temporarily transfers selected programs from main memory to the secondary storage. Reallocation of such programs is also performed by this algorithm. We will compare throughput using the RESEP strategy with that using the well-known FCFS strategy by means of simple queueing networks. This comparison shows the increase in throughput achieved by RESEP over FCFS as a function of the workload parameters. We will show that a two-disk channel system running under FCFS is less efficient than a one-channel system running under RESEP. [ABSTRACT FROM AUTHOR]

Assuming given production requirements for a set of part types, we examine the question of how these production requirements can be assigned to different, alternative routes through two production systems, a flexible manufacturing system, and a conventional job shop. Several nonlinear optimization models are proposed in order to optimize performance parameters like throughput, work-in-process inventory, utilization, and manufacturing lead time. The models incorporate product form queueing network theory in order to evaluate system performance and extend results based on linear programming formulations. The solution procedures are based on decomposition, fixed point, and classical gradient search techniques. [ABSTRACT FROM PUBLISHER]

Despite significant research efforts in beamforming, the maximum achievable downlink throughput with beamforming in a multi-cell environment is not available due to difficulty in finding optimal downlink beamforming. Thus, to reformulate the problem into a more solvable form, we derive dual uplink throughput optimization problem to multi-cell downlink beam- forming throughput maximization with per-base station (BS) power constraints based on Lagrangian duality. The optimal downlink beamforming is shown to be a minimum mean squared error (MMSE) beamforming in the dual uplink. It is also shown that the dual uplink problem achieves the same optimal throughput as the primal downlink problem. [ABSTRACT FROM PUBLISHER]