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In this paper, we optimize the instantaneous and average throughput when wireless communications uses Reconfigurable Intelligent Surfaces (RIS) and the source harvests power from sun using a Photo-Voltaic (PV) system. Instantaneous throughput optimization offers up to 6 dB gain versus average throughput optimization. Average throughput optimization offers a higher throughput than any packet length. Performance gain is up to 1 dB gain using average throughout optimization versus other values of packet length. [ABSTRACT FROM AUTHOR]

In new wireless network scenarios, such as the future Internet of Things, it is necessary to transmit information and energy simultaneously, and the communication environment is complex and variable, with high maintenance costs for communication equipment. On the one hand, IRS can improve the performance of wireless communication and wireless power transfer by intelligent adjustment of the wireless channel. On the other hand, providing power supply to IRS by wireless power transfer can solve the problem of inconvenient power supply of IRS and reduce the maintenance costs. This paper investigated the throughput optimization of a dual wireless powered IRS-assisted wireless communication system, in which the multi-antenna base station (BS) first transmitted energy to two IRS, and then transmitted information to multiple single-antenna users with the help of the IRS. For the cases without and with channel blocking between the BS and the IRS, this paper proposed two-phase and three-phase transmission modes, respectively. It maximized the throughputs of these modes by optimizing the transmit beamforming of the BS, the reflect beamforming of the IRS, and the time allocation of different phases, subject to the constraints of the maximum transmit power of the BS, the minimum rate of the users, the duration of each phase, and the unit-module reflection coefficients of the IRS. Since the resulting optimization problems were convex and the optimization variables were highly coupled, it was difficult to find their optimal solution directly. This paper proposed two optimization algorithms based on the alternating optimization, successive convex approximation, and semi-definite relaxation techniques to obtain high-quality sub-optimal solutions. Simulation results show that the proposed algorithms achieve significantly better throughput performance compared to some benchmark algorithms and demonstrate the suitable application scenarios of the two-phase and three-phase transmission modes. [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]

Interference management has always been a research hotspot in the field of wireless communications. Currently, researches based on interference management mostly focus on an interference management technology, and few studies have combined multiple interference management technologies. This paper proposes an interference management technology that combines Interference Alignment (IA) and Successive Interference Cancellation (SIC) technologies. First, we determine the routing path of the session with the goal to minimize hops and interference and establish the IA-SIC mathematics model in multi-hop networks. Based on this model, a cross-layer optimization framework for multi-hop networks is developed. The goal is to make full use of the advantages of IA and SIC to improve the end-to-end data transmission rate of multi-hop sessions. To evaluate the performance of our algorithm in multi-hop networks, we compare the performance of the network using IA-SIC with that without SIC. Simulation results show that using IA-SIC can significantly increase the throughput of the communication sessions. [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]

Wireless multihop networks are increasingly used because of their low cost and easy deployment. However, there are still many restrictions that degrade performance. Network coding has been proposed to improve the throughput of a wireless network through the characteristics of overhearing and broadcast. In this paper, we model the network utility maximization problem using a combined intrasession and intersession network coding method to improve the network utility in multiradio, multichannel, and multirate wireless network. And we propose a network throughput optimization scheme with a rate control, resource allocation and congestion control algorithm. We formulate an optimal framework reflecting wireless network environment. Also, we propose a rate selection scheme to choose the transmission rate on each node. We evaluate the proposed algorithms by simulation. The performance evaluation results show that the proposed scheme can improve throughput for network by utility optimization in a multiradio, multichannel, and multirate wireless network. [ABSTRACT FROM AUTHOR]

In order to protect the primary user from being interfered, most of the related works focus only on the restriction of the missed detection probability, which may cause over-protection of the primary user. Thus the interference probability is defined and the interference-aware sensing model is introduced in this paper. The interference-aware sensing model takes the spatial conditions into consideration, and can further improve the network performance with a good spectrum reuse opportunity. Meanwhile, although the detection performance can be further improved by the cooperative spectrum sensing, it also introduces additional reporting time corresponding to the number of cooperative users (CUs), which may decrease the throughput of the CRN. Motivated by the above, in this paper, we study the throughput tradeoff for interference-aware cognitive radio networks. For cooperative spectrum sensing, the Logic-OR fusion rule is used. By jointly optimizing the sensing time and the number of the CUs, the maximum throughput can be achieved. Theoretical analysis is given to prove the feasibility of the optimization and numerical simulations also show that the maximum throughput can be achieved when the sensing time and the number of the CUs are both optimized. [ABSTRACT FROM AUTHOR]

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]

Wireless mesh networks (WMNs) have attracted much attention due to their low up-front cost, easy network deployment, stable topology, robustness, reliable coverage, and so forth. These advantages are suitable for the disaster recovery applications in disaster areas, where WMNs can be advantageously utilized to restore network collapse after the disaster. In this paper, based on a new network infrastructure for WMNs, to guarantee high network performance, we focus on the issue of throughput optimization to improve the performance for WMNs. Owing to selecting different mesh router (MR) as the gateway will lead to different network throughput capacity, we propose a novel gateway selection technique to rapidly select the optimal MR as the gateway, in order to maximize the network throughput. In addition, we take into account the traffic distribution for the MR to eliminate traffic congestion in our method. The performance of our proposed method is evaluated by both numerical and simulated analysis. The simulation results demonstrate that the gateway selection method is effective and efficient to optimize the throughput for WMNs. [ABSTRACT FROM AUTHOR]

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]

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]

Abstract: In this paper, we propose a protocol for dynamic reconfiguration of ad-hoc wireless networks with movable base stations in presence of obstacles. Hosts are assigned to base stations according to a probabilistic throughput function based on both the quality of the signal and the base station load. In order to optimize space coverage, base stations cluster hosts using a distributed clustering algorithm. Obstacles may interfere with transmission and obstruct base stations and hosts movement. To overcome this problem, we perform base stations repositioning making use of a motion planning algorithm on the visibility graph based on an extension of the bottleneck matching technique. We implemented the protocol on top of the NS2 simulator as an extension of the AODV. We tested it using both Random Way Point and Reference Point Group mobility models properly adapted to deal with obstacles. Experimental analysis shows that the protocol ensures the total space coverage together with a good throughput on the realistic model (Reference Point Group) outperforming both the standard AODV and DSR. [ABSTRACT FROM AUTHOR]

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]

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]

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]

In this paper a novel link adaptation algorithm is proposed that is capable of adjusting the transmit power level and the data rate jointly to the radio channel conditions. The proposed method relies solely on link quality information available at the transmitter by employing the reception or non-reception of the acknowledgment frames as a measure of the channel quality with respect to the power level and data rate. The method is fully compatible with the 802.11 wireless LAN standard. In contrast to many other proposals, it neither relies on the RTS/CTS protocol nor requires a feedback channel to transmit link-quality estimates from the receiver to the transmitter. Different strategies for optimizing the data rate and power level are given. These depend on the scenarios considered, the number of active stations, and the service requirements. The two main strategies are either to drive the system towards the highest possible data rate and adjust the rate and power levels accordingly ("high-performance" mode) or to focus on power saving, possibly trading this for other performance criteria such as throughput or delay performance ("low-power" mode). Other special cases, such as power or rate only adaptation, are also discussed. It can be shown that in most cases the best choice for achieving low transfer times, maximizing throughput, and alleviating the hidden terminal problem is to transmit at the highest possible rates and with high power levels. This "high-performance" mode of operation also minimizes the transmission times, which in turn maximizes the time for putting idling components into a sleep mode, thereby minimizing the overall power consumption. [ABSTRACT FROM AUTHOR]