To enhance the anti-interference capability of unmanned aerial vehicle (UAV) networks, many UAV nodes are now equipped with directional antennas. However, their narrow beamwidth significantly increases the latency of neighbor discovery. In conventional neighbor discovery protocols, each node scans independently, leading to redundant discoveries as adjacent nodes repeatedly scan the same regions. To optimize this process, we propose Co-ND, a collaborative neighbor discovery protocol that enables a discovering node to offload part of its scanning workload to neighboring collaborators. This protocol not only accelerates the discovery process while preserving discovery completeness. To analyze the performance of Co-ND, we first model neighbor discovery as a state-transition process and derive a recursive expression for the delay. Then, by applying the additive drift principle, we calculate the upper and lower bounds and a closed-form approximation for the delay, theoretically proving its advantages in delay reduction. Finally, we conduct extensive simulations under various settings. The results show that Co-ND significantly outperforms existing schemes in neighbor discovery latency, especially in narrow-beam scenarios.

For massive grant-free access, maximum a posterior (MAP) estimation-based device activity detection is known to achieve superior detection accuracy in the scenario of known activity probabilities. Unfortunately, no comparable Bayesian statistical estimation method exists in the scenario of unknown activity probabilities. This paper investigates MAP estimation-based device activity detection in this scenario. First, we formulate the hierarchical MAP estimation problem for device activities, which is a very challenging non-convex problem. For tractability, we obtain its approximate non-convex problem and prove its equivalence to the MAP estimation problem of device activities and activity probabilities. Next, we propose a block coordinate descent (BCD)-based algorithm to obtain the approximate MAP estimation problem's stationary points. Finally, we numerically show that the proposed algorithm achieves a superior detection accuracy and short computation time tradeoff compared with the state-of-the-art device activity detection methods.

Integrated Sensing and Communications (ISAC) is emerged as one of the key technologies in next generation wireless systems. However, ISAC systems have been commonly explored neglecting mutual coupling. This paper investigates the mutual coupling exploitation to further improve the performance of ISAC systems. We aim to maximize the sensing beampatern gain by optimizing the tunable loads and the dual-functional beamforming while satisfying the minimum signal-to-interference-plus-noise (SINR) per user and the hardware constraint of the tunable loads. To solve the non-convex problem, we propose a penaltybased iterative algorithm to obtain a stationary point. Specifically, in each iteration we adopt the block coordinate descent (BCD) method where the dual-functional beamforming is obtained by using Lagrange duality, and the tunable loads are solved with closed forms. Numerical results demonstrate the notable gains and effectiveness of the proposed algorithms compared to the baseline schemes. To the best of our knowledge, this is the first study utilizing the MC effect to improve system performance in an ISAC system with tunable loads.

With the development of the space-air-ground integration technology, the satellites are armed with a certain on-board computing resource. To fully offload communication tasks to each satellite, we investigate a multiuser multi-satellite cooperative communication system without a central processing unit (CPU), where the satellites are equipped with tunable load antennas leveraging the mutual coupling effect to reconfigure the wireless channel. First, we formulate the sum spectral efficiency (SE) maximization problem with respect to the beamforming and the tunable loads under the power constraint and the constraints of the tunable loads. Afterwards, we propose a cooperative algorithm with closed-form updates to obtain a stationary point based on parallel successive convex approximation (SCA). Furthermore, we propose an efficient information exchange strategy for the satellites based on the ring all-reduce method, which significantly reduces the information exchange overhead of each satellite. Lastly, numerical results verify the proposed design's notable gain over the baselines. As far as we know, this is the first work to study the multi-satellite cooperative communication system with tunable load antennas.

The costs of channel estimation, reflection adjustment, and computation have severe impacts on intelligent reflection surface (IRS)-aided physical layer security (PLS) wireless communication systems in practice but are usually overlooked for simplicity in most existing works. This paper considers a multi-antenna base station serving a single-antenna legitimate user with the assistance of a multi-element IRS under the surveillance of a single-antenna eavesdropper. Firstly, we introduce a partial instantaneous CSI and statistical CSI (PICSI-SCSI)-adaptive beamforming and SCSI-adaptive reflection design. Secondly, we maximize the achievable ergodic secrecy rate (ESR) with respect to the PICSI-SCSI-adaptive beamforming and SCSI-adaptive reflection design, resulting in a two-timescale stochastic non-convex problem. Thirdly, we present two stochastic iterative algorithms to reach stationary and approximate stationary points. Moreover, we show that the two proposed designs achieve lower computational complexities and adjustment costs for reflection than the existing PICSI-SCSI-adaptive beamforming and reflection design. Lastly, we numerically demonstrate the two proposed designs’ notable gains over baselines. To our knowledge, this is the first work providing an optimization-based PICSI-SCSI-adaptive beamforming and SCSI-adaptive reflection design in an IRS-aided PLS wireless communication system, achieving promising secure performance at the minimum adjustment cost for reflection.

The utilization of unmanned aerial vehicles (UAVs) as base stations is an essential case in air-to-ground communication. To balance the equipment cost and performance of directional antennas, the ground terminal can be equipped with a servo phased antenna, which requires the careful design of the access mechanisms. In this paper, we consider the application in which the UAV uses an omnidirectional antenna while the ground terminals use a servo-phased array. We first proposed two access approaches, i.e., stop-and-scan and continuous scan schemes. Then, we established theoretical models for the two schemes and analyzed the performance and the factors impacting it. After that, we conducted a Monte Carlo simulation and compared the performance with numerical results. Results show that the access delay in the stop-and-scan scheme is inversely proportional to the beam width, servo acceleration, and the number of access time slots. The access delay of the continuous scan scheme is significantly lower than the other. However, in the continuous scan scheme, the beam width and the servo acceleration should satisfy a specific constraint to avoid access failure.

Most existing studies on massive grant-free access, proposed to support massive machine-type communications (mMTC) for the Internet of things (IoT), assume Rayleigh fading and perfect synchronization for simplicity. However, in practice, line-of-sight (LoS) components generally exist, and time and frequency synchronization are usually imperfect. This paper systematically investigates maximum likelihood estimation (MLE)-based device activity detection under Rician fading for massive grant-free access with perfect and imperfect synchronization. We assume that the large-scale fading powers, Rician factors, and normalized LoS components can be estimated offline. We formulate device activity detection in the synchronous case and joint device activity and offset detection in three asynchronous cases (i.e., time, frequency, and time and frequency asynchronous cases) as MLE problems. In the synchronous case, we propose an iterative algorithm to obtain a stationary point of the MLE problem. In each asynchronous case, we propose two iterative algorithms with identical detection performance but different computational complexities. In particular, one is computationally efficient for small ranges of offsets, whereas the other one, relying on fast Fourier transform (FFT) and inverse FFT, is computationally efficient for large ranges of offsets. The proposed algorithms generalize the existing MLE-based methods for Rayleigh fading and perfect synchronization. Numerical results show that the proposed algorithm for the synchronous case can reduce the detection error probability by up to 50.4% at a 78.6% computation time increase, compared to the MLE-based state-of-the-art, and the proposed algorithms for the three asynchronous cases can reduce the detection error probabilities and computation times by up to 65.8% and 92.0%, respectively, compared to the MLE-based state-of-the-arts.

The impacts of channel estimation, beamforming adjustment, phase shift adjustment, and computation costs on an intelligent reflecting surface (IRS)-assisted secure wireless communication system are severe in practice but are usually ignored for simplicity. In this paper, we consider a multi-antenna BS serving a single-antenna legitimate user with the help of a multi-element IRS in the presence of an eavesdropper. To maximally reduce the implementation cost, we investigate the no-instantaneous channel state information (ICSI) case with the legitimate user’s and eavesdropper’s statistical CSI (SCSI). First, we present a SCSI-adaptive (quasi-static) beamforming and phase shift design, also referred to as a quasi-static design, which has low channel estimation, beamforming adjustment, and phase shift adjustment costs. Then, we formulate the maximization of the achievable ergodic secrecy rate with respect to the quasi-static design as a challenging stochastic non-convex problem. Next, we propose two parallel iterative algorithms to obtain a stationary point and an approximate stationary point and present their respective quasi-static designs. Furthermore, we show that the quasi-static designs derived from the stationary point and approximate stationary point achieve lower implementation costs than existing designs. Finally, we numerically verify the analytical results and demonstrate notable gains of the two proposed quasi-static designs over existing designs.

The analysis and optimization of single intelligent reflecting surface (IRS)-assisted systems have been extensively studied, whereas little is known regarding multiple-IRS-assisted systems. This paper investigates the analysis and optimization of a double-IRS cooperatively assisted downlink system (D-IRS-C), where a multi-antenna base station (BS) serves a single-antenna user with the help of two multi-element IRSs, connected by an inter-IRS channel. The channel between any two nodes is modeled with Rician fading. The BS adopts the instantaneous CSI-adaptive maximum-ratio transmission (MRT) beamformer, and the two IRSs adopt a cooperative quasi-static phase shift design. The goal is to maximize the average achievable rate, which can be reflected by the average channel power of the equivalent channel between the BS and user at low channel estimation and phase adjustment costs and computational complexity. First, we obtain tractable expressions of the average channel power of the equivalent channel in the general (Rician factor), pure line of sight (LoS), and pure non-line of sight (NLoS) regimes, respectively. Then, we jointly optimize the phase shifts of the two IRSs to maximize the average channel power of the equivalent channel in these regimes. The optimization problems are challenging non-convex problems. We obtain globally optimal closed-form solutions for some cases and propose computationally efficient iterative algorithms to obtain stationary points for the other cases. Next, we compare the computational complexity for optimizing the phase shifts and the optimal average channel power of D-IRS-C with those of a counterpart double-IRS non-cooperatively assisted system (D-IRS-NC) and a counterpart single-IRS-assisted system (S-IRS) at a large number of reflecting elements in the three regimes. Finally, we numerically demonstrate notable gains of the proposed solutions over the existing solutions at different system parameters. To our knowledge, this is the first work that optimizes the quasi-static phase shift design of D-IRS-C and characterizes its advantages over the optimal quasi-static phase shift design of the counterpart D-IRS-NC and S-IRS.

Grant-free access is recently proposed as an essential technique for supporting massive machine-type communications (mMTC) for the Internet of Things (IoT). However, high accuracy and low complexity device activity detection under imperfect frequency synchronization remains open. To address this issue, this paper proposes a maximum likelihood estimation (MLE)- based device activity detection method for the frequency asynchronous case. First, we formulate the estimation of device activities together with the device carrier frequency offsets (CFOs) as an MLE problem. Then, to tackle this challenging nonconvex problem, we propose a computationally efficient iterative algorithm using the block coordinate descent (BCD) method and fast computation enabled by fast Fourier transform (FFT). Analytical and numerical results demonstrate the notable gains of the proposed method over the existing solutions and offer important design insights into practical massive grant-free access for mMTC.

Most existing random access schemes for machine-type communications (MTC) simply adopt a uniform preamble selection distribution, irrespective of the underlying device activity distributions. Hence, they may yield unsatisfactory access efficiency. In this paper, we model device activities for MTC as multiple Bernoulli random variables following an arbitrary multivariate Bernoulli distribution which can reflect both dependent and independent device activities. Then, we optimize preamble selection and access barring for random access in MTC according to the underlying joint device activity distribution. Specifically, we investigate three cases of the joint device activity distribution, i.e., the cases of perfect, imperfect, and unknown joint device activity distributions, and formulate the average, worst-case average, and sample average throughput maximization problems, respectively. The problems in the three cases are challenging nonconvex problems. In the case of perfect joint device activity distribution, we develop an iterative algorithm and a low-complexity iterative algorithm to obtain stationary points of the original problem and an approximate problem, respectively. In the case of imperfect joint device activity distribution, we develop an iterative algorithm and a low-complexity iterative algorithm to obtain a Karush-Kuhn-Tucker (KKT) point of an equivalent problem and a stationary point of an approximate problem, respectively. Finally, in the case of unknown joint device activity distribution, we develop an iterative algorithm to obtain a stationary point. The proposed solutions are widely applicable and outperform existing solutions for dependent and independent device activities.

The broadcast scheme is a basic and important data dissemination mechanism in FANET. In this paper, we propose an efficient neighbor quality based mMultil- Ppoint Rrelay (MPR) broadcast scheme based on local neighbor status. The local neighbor status includes two aspects, i.e., the physical link status and the congestion status. The physical link status is indicated by the expected successful packet delivery ratio and link expiration time calculated from the Received Signal Strength Indication (RSSI). The congestion status is determined by the queue length of each neighboring nodes. Then an efficient MPR set can be selected from one-hop neighbors by local neighbor status. Each node uses its MPR set to rebroadcast messages. We use RSSI to calculate the packet successful expectation and link expiration time, and MAC layer queue length to indicate how busy the node is. Simulation result shows that our method performs better in terms of end-to-end delay and packet delivery rate than probability methods and other deterministic methods.

In this paper, we focus on a dual-functional communication-navigation system. First, we consider the ranging accuracy and take Cramer-Rao lower bound(CRLB) as the metrics. Based on the derived CRLB, we analyze the effect of adding the pulse shaping filter on it and the influence of rolloff factor. Moreover, we compare the CRLB of different single-carrier modulation formats. As for communication performance, we consider a case where the maximum transmitting power is the same, which means lower Peak to Average Power Ratio(PAPR) can achieve higher SNR and channel capacity. On this basis, we analyze the PAPR of pulse shaping filters and modulation formats. Considering these two metrics together, we select appropriate pulse shaping filter and modulation formats.

Industrial Wireless Sensor Networks (IWSNs) are mainly used for critical monitoring and control applications in industrial automation systems. The applications require realtime data delivery within strict delay constraints. Exceeding the required delay bound for emergency traffic could result in economic losses or even safety incidents. In this paper, we propose a Priority-enhanced slot Allocation Medium Access Control protocol (PriAlloc-MAC), which can guarantee the transmission of different traffic categories of IWSNs in given time constraints. In this protocol, the nodes with emergency traffic are allowed to preempt slots to reduce the channel access delay. Multiple nodes with emergency traffic access the channel without conflicts according to their access sequence numbers (ASNs). In addition, the protocol utilizes a short time slot design and allocates a different number of time slots to each node according to the length of the data packet to be transmitted to improve channel utilization. In this paper, the performance of PriAlloc-MAC is evaluated and compared with WirelessHART. Results show that PriAlloc-MAC is significantly better than WirelessHART in terms of traffic delay and channel utilization.

In Aeronautical Ad Hoc Network (AANET), attacks are often diverse, and a lack of preventive measures may cause serious losses. Therefore, compared with traditional MANET, AANET has higher security requirements. In this paper, we propose a trust-based partially distributed key management scheme to consider both capability and integrity trust of network. Capability trust reflects the link state of the routing path and the metric is used to choose reliable intermediate nodes for transmission. The integrity trust distinguishes compromised nodes from well-behaving nodes. The key management scheme only issues certificates to the well-behaving nodes to verify their legitimacy. We perform simulations and compare the proposed scheme with a composite trust-based public key management scheme (CTPKM). The simulation results demonstrate the performance advantages of our scheme in terms of overhead, packet delivery ratio and evaluation accuracy.

The tradeoff between bandwidth efficiency and quality of experience (QoE) is a key issue in 360 video transmission. In this paper, we propose a QoE-oriented saliency-aware 360 video transmission framework to balance this tradeoff. The target is to reduce the bandwidth demand without declining the QoE. Specifically, the proposed model is based on the decision-making process. We use Lyapunov optimization to solve the decisionmaking problem. Furthermore, we integrate saliency information into the model to influence the decision policy, so that the model has the advantage of bandwidth efficiency. The simulation results show that the tradeoff parameter of Lyapunov optimization can balance the tradeoff between QoE and bandwidth efficiency, and 360 video saliency entropy limits the upper and lower bounds of QoE and bandwidth efficiency.

In this paper, we firstly establish the model of inductive power transfer (IPT) through metal barriers by using the electromagnetic model. Then we theoretically analyze the operating frequency range of IPT through metal barriers, which includes the optimal operating frequency. After that, the theoretical results are proved by simulation in MAXWELL and SIMPLORER.

Orthogonal frequency division multiplexing (OFDM) systems suffer from a large peak-to-average power ratio (PAPR), leading to lower power efficiency and nonlinear distortion at the transmit power amplifier. Tone reservation (TR) techniques can effectively reduce PAPR, but may also cause data rate reduction if the TR ratio is not carefully designed. In this paper, we propose a low-complexity TR approach for PAPR reduction in OFDM systems, which is parametrized by the TR ratio. Then, under certain approximations, we characterize the PAPR reduction and the data rate increase of the proposed TR approach using order statistics. Next, we formulate the TR ratio optimization problem to maximize the data rate. The optimization problem is very challenging, as the data rate cannot be explicitly expressed as a function of the TR ratio. To reduce the computation complexity, we propose a near optimal solution by solving an approximate optimization problem of the original one. Finally, numerical results verify the analysis and demonstrate the performance of the proposed near optimal solution.

Caching and multicasting are two promising methods to support massive content delivery in multi-tier wireless networks. In this paper, we consider a random caching and multicasting scheme with caching distributions in the two tiers as design parameters, to achieve efficient content dissemination in a two-tier large-scale cache-enabled wireless multicasting network. First, we derive tractable expressions for the successful transmission probabilities in the general region as well as the high signal-to-noise ratio (SNR) and high user density region, respectively, utilizing tools from stochastic geometry. Then, for the case of a single operator for the two tiers, we formulate the optimal joint caching design problem to maximize the successful transmission probability in the asymptotic region, which is nonconvex in general. By using the block successive approximate optimization technique, we develop an iterative algorithm, which is shown to converge to a stationary point. Next, for the case of two different operators, one for each tier, we formulate the competitive caching design game where each tier maximizes its successful transmission probability in the asymptotic region. We show that the game has a unique Nash equilibrium (NE) and adopt an iterative algorithm, which is shown to converge to the NE under a mild condition. Finally, by numerical simulations, we show that the proposed designs achieve significant gains over existing schemes.

This paper proposes a novel frame rate up-conversion method through high-order model and dynamic filtering (HOMDF) for video pixels. Unlike the constant brightness and linear motion assumptions in traditional methods, the intensity and position of the video pixels are both modeled with high-order polynomials in terms of time. Then, the key problem of our method is to estimate the polynomial coefficients that represent the pixel's intensity variation, velocity, and acceleration. We propose to solve it with two energy objectives: one minimizes the auto-regressive prediction error of intensity variation by its past samples, and the other minimizes video frame's reconstruction error along the motion trajectory. To efficiently address the optimization problem for these coefficients, we propose the dynamic filtering solution inspired by video's temporal coherence. The optimal estimation of these coefficients is reformulated into a dynamic fusion of the prior estimate from pixel's temporal predecessor and the maximum likelihood estimate from current new observation. Finally, frame rate up-conversion is implemented using motion-compensated interpolation by pixel-wise intensity variation and motion trajectory. Benefited from the advanced model and dynamic filtering, the interpolated frame has much better visual quality. Extensive experiments on the natural and synthesized videos demonstrate the superiority of HOMDF over the state-of-the-art methods in both subjective and objective comparisons.

Detection probability is one of the most important criteria in the satellite-based automatic identification system. It represents how many vessels can be detected in the monitoring area of the system. However, existing research often neglects practical factors in S-AIS (satellite-based AIS) and cannot assess the performance of a practical system. In this paper, we propose a much detailed collision model by considering both the effects of SINR (Signal to Interference plus Noise Ratio) caused by antenna patterns and the demodulation performance. Through this model, we can construct much more accurate and reasonable detection probability calculation method. Simulation results show that the detection probability from the proposed practical model is much larger than that from the legacy model.

Space-based Automatic Identification System (AIS) uses Gaussian minimum shift keying modulation (GMSK) as the modulation scheme. Thus, Viterbi Algorithm (VA) is commonly implemented considering the tradeoff between performance and complexity. For the further improvement of the performance of Viterbi decoding, we propose a Soft-Output Viterbi Algorithm for AIS receiver (SOVA-AIS) in this paper. The proposed SOVA-AIS introduces soft values to quantify the error probability of demodulated bits and use them to update the survivor path in VA to get more precise estimation of the signal phase. Simulation results show that, compared with VA, SOVA-AIS can provide 0.5-1.5dB gain in the case with only one AIS signal and 1-3dB gain in the case with two collided AIS signals.

Single Carrier-Frequency Division Multiple Access (SC-FDM) and Tone Reservation (TR) are used independently to reduce Peak to Average Power Ratio (PAPR) in wireless communications. In this paper, we jointly consider TR and SC-FDM to achieve much lower PAPR. We first present the PAPR of SC-FDM system with different DFT/IDFT size, and then theoretically analyze the PAPR gain of TR in SC-FDM. By considering the impact of TR on transmission power, we propose a novel metric, the effective signal power, to measure the performance of TR in SC-FDM. Afterwards, the TR optimization problem is formulated and solved by TR gradient algorithm. Finally, the performance of TR with SC-FDM is evaluated.

Because of the wide field of view (FOV) to monitor vessel movements, satellite-based automatic identification system (S-AIS) has been promoted in recent years. However, synchronization is a tough work in S-AIS receiver because of the large Doppler shift and serious signal collision resulting from simultaneous transmission in the FOV of a satellite. In this paper, we propose a pipelined synchronization approach with good performance and low complexity. It consists of three parts, i.e., packet detection, windowing and timing recovery, and frequency and timing offset estimation, which can be implemented in feedforward structure with low complexity. Simulation results show that the proposed synchronization approach has significant performance gain compared with existing algorithms and provides an acceptable estimation range to cope with large Doppler shift and message collision.

In this paper, we propose a Differential Overlap Decoding (DOD) algorithm to solve the hidden-terminal problems in OFDM based WLAN systems. DOD exploits the retransmission and random-jitter features of WLAN to decode the collided packets as a whole. DOD provides with new methods and views to jointly separate and decode collided packets in OFDM based system. In DOD, we formulate IFFT/FFT, channel influence and packet collision as linear processes. Thus we can express the received collided packets as linear equations, and simplify this problem into solving linear equations. We evaluate the performance of DOD through simulation, and results show that when DOD is applied, hidden-terminal problems can be viewed as a 3-5 dB BER performance degradation rather than network contention.

In this paper, we investigate call admission control (CAC) with opportunistic scheduling and propose a novel CAC algorithm for users with quality of service (QoS) requirements. Our main contribution is threefold. First, we verify that, compared with several other scheduling schemes, cumulative distributed function based scheduling (CS) makes the best tradeoff between efficiency and fairness in full-load scenario and exploits the best opportunism with absolutely fair resource allocation. Then we deduce and validate the multi-user diversity gain (MDG) of CS, which determines its long-term average performance and is used for estimation of resource occupation in CAC algorithm design. After that, we use opportunistic round robin (ORR) method to calculate the statistical low performance bound of CS, and propose CS/ORR based CAC (COCAC) algorithm, which guarantees the heterogeneous minimum rate requirement (MRRs) of both new access users and existing ones. Finally, we evaluate the performance of the proposed COCAC algorithm via simulation. Results show that COCAC can significantly reduce new call block probability, effectively make use of system resources, as well as strictly guarantee all users' MRRs.

In this paper, we investigate load balancing problem in 3GPP Long Term Evolution (LTE) networks and propose our solution which considers users with different Quality-of-Service (QoS) requirements. Load unbalance among neighboring cells often yields negative impacts on user experience and network performance, and it has mainly been considered for only data services without QoS guarantee. However, 3GPP LTE network aims to support multi-class services with different QoS requirements, on which the influence of load unbalance is quite different. For those with minimum rate requirements, it may result in high block probability, while for others without rate requirements, the throughput of boundary users may be degraded. In this paper, we incorporate all the differences into a network utility maximization framework and formulate it as a multi-objective optimization problem. The objectives in the problem are load balancing index of services with QoS requirements and the total utility of other services, and the constraints are physical resource limits and QoS demands. Then we analyze the complexity of the problem, and propose our solution, which includes a QoS guaranteed hybrid scheduling scheme, handover of users with and without QoS requirements, and a call admission control algorithm. Extensive simulation is conducted and the results show that the proposed framework leads to significantly better load balancing, and thus the decrease in call block probability of users with QoS requirements, and the increase in throughput of boundary best effort users.

The total energy minimization in wireless multihop networks using two-way network coding is investigated in this paper. The problem is first formulated as a linear programming problem, then decomposed into two sub-problems using the La grangian decomposition, and finally solved with the subgradient method. After that, the backpressure based algorithm is proposed to solve the problem in a distributed manner. The performance of the algorithm is evaluated first in a simple topology for analysis and then in a random topology with different number of flows for practical consideration. Simulation results show that the convergence time increases as the number of nodes in the network, and the energy cost per packet can be saved up to 30% by using two-way network coding.

This paper deals with lifetime maximization for energy constrained wireless networks with inter-session network coding. The problem of lifetime maximization is first formulated, and then transformed into a linear programming problem. Using Lagrangian dual decomposition, it is further converted into a dual problem that consists of two subproblems: lifetime optimization and network optimization, and then it is solved by utilizing dual subgradient method. Convex combination is used for primary recovery from the dual solutions. Performance of the algorithm is evaluated through simulation. Results illustrate that theoretical analysis matches practical calculation well, and that inter-session network coding can prolong the network lifetime up to 50% compared with the one without network coding.

Load imbalance that deteriorates the system performance is a severe problem existing in 3GPP LTE networks. To deal with this problem, we propose in this paper a load balancing framework, which aims at balancing the load in the entire network, while keeping the network throughput as high as possible. In this framework, the objective is formulated as a network-wide utility function balancing network throughput and load distribution, and then it is transformed to an integer optimization problem under resource allocation constraints. After that, the complexity of the problem is analyzed, network structure constraints are presented, and a practical suboptimal algorithm, called Heaviest-First Load Balancing (HFLB), is proposed. Extensive simulation is made and the results show that using the HFLB algorithm the network can get significantly better load balancing while maintaining the same network throughput at the price of a bit more handovers compared with the traditional signal strength-based handover algorithm.

The poor performance of TCP in multihop ad hoc networks is mainly attributed to the inefficient interaction among different protocol layers in previous literature, while the heavy load caused by end-to-end TCP acknowledgements (ACKs) with limited information is usually ignored. In this paper, we propose a novel incorporating ACK transfer scheme, IACK, to alleviate its impact. In IACK, TCP acknowledgements are incorporated in the control packets at the MAC layer and are transferred hop by hop from the sink node to the source node. To meet the requirement of IACK, we enhance the packet queuing policy at the routing layer, and propose a new rate-based TCP transfer scheme, TCP-AP+. Then, we implement IACK in ns-2, evaluate it over comprehensive scenarios and compare it with TCP-AP and TCP-Newreno. Simulation results show that IACK improves both the TCP throughput and goodput significantly.

In most wireless relay networks, the source and relay nodes transmit successively via fixed time division (FTD) and each relay forwards a packet immediately upon receiving. In this paper we enable the buffering capability of relay nodes and propose a framework for joint scheduling and relay selection. The goal is to maximize the system long-term throughput by fully exploiting multi-user diversity in the network. We develop two joint scheduling and relay selection (JSRS) algorithms for unidirectional and bidirectional traffic, respectively. The novel cross-layer relay selection metrics which our algorithms are based upon take into account both instantaneous channel conditions and the queuing status. We also demonstrate that the proposed JSRS can be realized in a distributed way without explicit coordination among the network nodes. Extensive simulation is carried out to evaluate the performance of the proposed JSRS with buffering in comparison with traditional FTD without buffering. Typical throughput enhancements up to 101% and 110% are observed in one-way and two-way relay networks respectively, at low signal-to-noise ratio (0 dB).

The performance of TCP-Vegas is not satisfactory in multihop ad hoc networks over IEEE 802.11 MAC protocol. We analyze the problem with a unified network model and simulation results. We observe that the aggregate throughput of all traffics decreases as the load of the network increases. The main reasons lie in Vegas's large minimum congestion window, large reset slow start threshold and aggressive window increase policy. To fix these problems, we propose a modified TCP protocol based on TCP-Vegas for multihop ad hoc networks, called Vegas- W. We extend the congestion window to fraction; change the probing mechanisms of legacy TCP-Vegas in both slow start and congestion avoidance and update slow start threshold tracking the stable window. We evaluate the performance of Vegas-W through ns-2. Extensive simulation results under a variety of scenarios show that Vegas-W can improve the throughput up to 87% over legacy TCP-Vegas and up to 27% over FeW, which is another improved algorithm based on TCP-Newreno scenarios.