To mitigate the interference caused by frequency reuse between inter-layer and intra-layer users for Non-Orthogonal Multiple Access (NOMA) based device-to-device (D2D) communication underlaying cellular systems, this paper proposes a joint optimization strategy that combines user grouping and resource allocation. Specifically, the optimization problem is formulated to maximize the sum rate while ensuring the minimum rate of cellular users, considering three optimization parameters: user grouping, sub channel allocation and power allocation. However, this problem is a mixed integer nonlinear programming (MINLP) problem and is hard to solve directly. To address this issue, we divide the problem into two sub-problems: user grouping and resource allocation. First, we classify D2D users into D2D pairs or D2D NOMA groups based on the greedy algorithm. Then, in terms of resource allocation, we allocate the sub-channel to D2D users by swap matching algorithm to reduce the co-channel interference, and optimize the transmission power of D2D by the local search algorithm. Simulation results show that, compared to other schemes, the proposed algorithm significantly improves the system sum rate and spectral utilization.

Device-to-device (D2D) communication allows user terminals to directly communicate with each other without the need for any base stations (BSs). Since the D2D communication underlaying a cellular system shares frequency channels with BSs, co-channel interference may occur. Successive interference cancellation (SIC), which is also called the serial interference canceler, detects and subtracts user signals from received signals in descending order of received power, can cope with the above interference and has already been applied to fog nodes that manage communications among machine-to-machine (M2M) devices besides direct communications with BSs. When differences among received power levels of user signals are negligible, however, SIC cannot work well and thus causes degradation in bit error rate (BER) performance. To solve such a problem, this paper proposes to apply parallel interference cancellation (PIC), which can simultaneously detect both desired and interfering signals under the maximum likelihood criterion and can maintain good BER performance even when power level differences among users are small. When channel coding is employed, however, SIC can be superior to PIC in terms of BER under some channel conditions. Considering the superiority, this paper also proposes to select the proper cancellation scheme and modulation and coding scheme (MCS) that can maximize the throughput of D2D under a constraint of BER, in which the canceler selection is referred to as adaptive interference cancellation. Computer simulations show that PIC outperforms SIC under almost all channel conditions and thus the adaptive selection from PIC and SIC can achieve a marginal gain over PIC, while PIC can achieve 10% higher average system throughput than that of SIC. As for transmission delay time, it is demonstrated that the adaptive selection and PIC can shorten the delay time more than any other schemes, although the fog node causes the delay time of 1ms at least.

In this paper, a hybrid electromagnetic simulation method of two-dimensional FDTD and ray-tracing methods suitable for an airport surface was proposed. The power variation due to ground reflection, refraction and creeping is calculated by two-dimensional FDTD method and ray-tracing method is used to calculate the reflecting and diffracted powers from buildings. The proposed approach was validated by measurement using a 1/50 scale-model of an airport model with a building model in various positions at 5 GHz. The proposed method allowed measured power distributions to correlate with simulated figures to within 4.8 dB and their null positions were also estimated to an error tolerance of within 0.01 m.

Device-to-device (D2D) relay enhances the capacity of a mobile network. If the channel quality of a user equipment (UE) is bad, the UE asks a neighbor to get its data from the base station and forward the data to it by using D2D communication. Since cellular and D2D communication can share spectrum resources, the spectral efficiency will rise. As UEs are owned by self-interested users, they may not provide relay services gratis. Thus, some incentive methods let UEs exchange tokens to buy and sell relay services. However, they assume that each relay service is worth one token and offers a fixed data rate, which lacks flexibility. Through the law of supply and demand, this paper proposes an economy aware token-based incentive (EAT-BI) strategy. A supplier (i.e., the service provider) charges different prices for its relay service with different rates. A consumer (i.e., the service requestor) takes different policies to choose a supplier based on its tokens and may bargain with suppliers to avoid starvation. Simulation results show that EAT-BI can efficiently promote D2D relay use and increase throughput under different mobility models of UEs.

In this paper, for improving the robustness of D2D-based SNS by avoiding the cascading failure, we propose an autonomous decentralized friendship management called virtual temporal friendship creation. In our proposed virtual temporal friendship creation, some virtual temporal friendships are created among users based on an optimization problem to improve the robustness although these friendships cannot be used to perform the message exchange in SNS. We investigate the impact of creating a new friendship on the node resilience for the optimization problem. Then we consider an autonomous decentralized algorithm based on the obtained results for the optimization problem of virtual temporal friendship creation. We evaluate the performance of the virtual temporal friendship creation with simulation and investigate the effectiveness of this method by comparing with the performance of a method with meta-heuristic algorithm. From numerical examples, we show that the virtual temporal friendship creation can improve the robustness quickly in an autonomous and decentralized way.

Estimating the spatial parameters of the signals by using the effective data of a single snapshot is essential in the field of reconnaissance and confrontation. Major drawback of existing algorithms is that its constructed covariance matrix has a great degree of rank loss. The performance of existing algorithms gets degraded with low signal-to-noise ratio. In this paper, a three-parallel linear array based algorithm is proposed to achieve two-dimensional direction of arrival estimates in a single snapshot scenario. The key points of the proposed algorithm are: 1) construct three pseudo matrices with full rank and no rank loss by using the single snapshot data from the received signal model; 2) by using the rotation relation between pseudo matrices, the matched 2D-DOA is obtained with an efficient parameter matching method. Main objective of this work is on improving the angle estimation accuracy and reducing the loss of degree of freedom in single snapshot 2D-DOA estimation.

In this study, we propose a mechanism called adaptive failsoft control to address peak traffic in mobile live streaming, using a chasing playback function. Although a cache system is avaliable to support the chasing playback function for live streaming in a base station and device-to-device communication, the request concentration by highlight scenes influences the traffic load owing to data unavailability. To avoid data unavailability, we adapted two live streaming features: (1) streaming data while switching the video quality, and (2) time variability of the number of requests. The second feature enables a fallback mechanism for the cache system by prioritizing cache eviction and terminating the transfer of cache-missed requests. This paper discusses the simulation results of the proposed mechanism, which adopts a request model appropriate for (a) avoiding peak traffic and (b) maintaining continuity of service.

In this letter, a method for the construction of polar codes based on the mutual information approximation (MIA) is proposed for the 4Tb/in2 two-dimensional inter-symbol interference (2D-ISI) channels, such as the bit-patterned magnetic recording (BPMR) and two-dimensional magnetic recording (TDMR). The basic idea is to exploit the MIA between the input and output of a 2D detector to establish a log-likelihood ratio (LLR) distribution model based on the MIA results, which compensates the gap caused by the 2D ISI channel. Consequently, the polar codes obtained by the optimization techniques previously developed for the additive white Gaussian noise (AWGN) channels can also have satisfactory performances over 2D-ISI channels. Simulated results show that the proposed polar codes can outperform the polar codes constructed by the traditional methods over 4Tb/in2 2D-ISI channels.

In this paper, in order to avoid the cascading failure by increasing the number of links in the physical network in D2D-based SNS, we propose an autonomous device placement algorithm. In this method, some relay devices are placed so as to increase the number of links in the physical network. Here, relay devices can be used only for relaying data and those are not SNS users. For example, unmanned aerial vehicles (UAV) with D2D communication capability and base stations with D2D communication capability are used as the relay devices. In the proposed method, at first, an optimization problem for minimizing node resilience which is a performance metric in order to place relay devices. Then, we investigate how relay devices should be placed based on some approximate optimal solutions. From this investigation, we propose an autonomous relay device placement in the physical network. In our proposed algorithm, relay devices can be placed without the complete information on network topology. We evaluate the performance of the proposed method with simulation, and investigate the effectiveness of the proposed method. From numerical examples, we show the effectiveness of our proposed algorithm.

Device-to-device (D2D) content delivery reduces the energy consumption of frequent content retrieval in future content-centric cellular networks based on proximal content delivery. Compared with unicast, multicast may be more efficient since it serves the content requests of multiple users simultaneously. The serving efficiency mainly depends on the selection of multicast transmitter, which has not been well addressed. In this letter, we consider the match degree between the multicast content of transmitter and the required content of receiver based on social relationship between transceivers. By integrating the effects of communication environments and match degree into the selection procedure, a multicast UE selection scheme is proposed to improve the number of benefited receivers from D2D multicast. Simulation results show that the proposed scheme can efficiently improve the performance of D2D multicast content delivery under different communication environments.

This paper presents a two-dimensional (2D) DOA algorithm for double L-shaped arrays. The algorithm is applied to the underwater environment for eliminating the performance error caused by the sound speed uncertainty factor. By introducing the third dimensional array, the algorithm eliminates the sound velocity variable in the depression angle expression, so that the DOA estimation no longer considering the true value of unknown sound velocity. In order to determine the parameters of a three-dimensional array, a parameter matching method with the double L-shaped array is also proposed. Simulations show that the proposed algorithm outperforms the conventional 2D-DOA estimation algorithm in unknown sound velocity environment.

To estimate angle, velocity, and range information of multiple targets jointly in FMCW MIMO radar, two-dimensional (2D) MUSIC with matched filtering and FFT algorithm is proposed. By reformulating the received FMCW signal of the colocated MIMO radar, we exploit 2D MUSIC to estimate the angle and Doppler frequency of multiple targets. Then by using a matched filter together with the estimated angle and Doppler frequency and FFT operation, the range of the target is estimated. To effectively estimate the parameters of multiple targets with large distance differences, we also propose a successive interference cancellation method that uses the orthogonal projection. That is, rather than estimating the multiple target parameters simultaneously using 2D MUSIC, we estimate the target parameters sequentially, in which the parameters of the target having strongest reflected power are estimated first and then, their effect on the received signal is canceled out by using the orthogonal projection. Simulations verify the performance of the proposed algorithm.

This paper addresses the problem of developing an efficient fault-tolerant routing method for 2D mesh Network-on-Chips (NoCs) to realize dependable and high performance many core systems. Existing fault-tolerant routing methods have two critical problems of high communication latency and low node utilization. Unlike almost all existing methods where packets always detour faulty nodes, we propose a novel and unique approach that packets can pass through faulty nodes. For this approach, we enhance the common NoC architecture by adding switches and links around each node and propose a fault-tolerant routing method with no virtual channels based on the well-known simple XY routing method. Simulation results show that the proposed method reduces average communication latency by about 97.1% compared with the existing method, without sacrificing fault-free nodes.

When the track density of two-dimensional magnetic recording (TDMR) systems is increased, intertrack interference (ITI) inevitably grows, resulting in the extreme degradation of an overall system performance. In this work, we present coding, writing, and reading techniques which allow TDMR systems with multi-readers to overcome severe ITI. A rate-5/6 two-dimensional (2D) modulation code is adopted to protect middle-track data from ITI based on cross-track data dependence. Since the rate-5/6 2D modulation code greatly improves the reliability of the middle-track, there is a bit-error rate gap between middle-track and sidetracks. Therefore, we propose the different track width writing technique to optimize the reliability of all three data tracks. In addition, we also evaluate the TDMR system performance using an user areal density capability (UADC) as a main key parameter. Here, an areal density capability (ADC) can be measured by finding the bit-error rate of the system with sweeping track and linear densities. The UADC is then obtained by removing redundancy from the ADC. Simulation results show that a system with our proposed techniques gains the UADC of about 4.66% over the conventional TDMR systems.

We design a new oblivious routing algorithm for two-dimensional mesh-based Networks-on-Chip (NoCs) called LEF (Long Edge First) which offers high throughput with low design complexity. LEF's basic idea comes from conventional wisdom in choosing the appropriate dimension-order routing (DOR) algorithm for supercomputers with asymmetric mesh or torus interconnects: routing longest dimensions first provides better performance than other strategies. In LEF, we combine the XY DOR and the YX DOR. When routing a packet, which DOR algorithm is chosen depends on the relative position between the source node and the destination node. Decisions of selecting the appropriate DOR algorithm are not fixed to the network shape but instead made on a per-packet basis. We also propose an efficient deadlock avoidance method for LEF in which the use of virtual channels is more flexible than in the conventional method. We evaluate LEF against O1TURN, another effective oblivious routing algorithm, and a minimal adaptive routing algorithm based on the odd-even turn model. The evaluation results show that LEF is particularly effective when the communication is within an asymmetric mesh. In a 16×8 NoC, LEF even outperforms the adaptive routing algorithm in some cases and delivers from around 4% up to around 64.5% higher throughput than O1TURN. Our results also show that the proposed deadlock avoidance method helps to improve LEF's performance significantly and can be used to improve O1TURN's performance. We also examine LEF in large-scale NoCs with thousands of nodes. Our results show that, as the NoC size increases, the performance of the routing algorithms becomes more strongly influenced by the resource allocation policy in the network and the effect is different for each algorithm. This is evident in that results of middle-scale NoCs with around 100 nodes cannot be applied directly to large-scale NoCs.

In this paper, we investigate different power allocation optimization problems with interferences for distributed antenna systems (DAS) with and without D2D communication, respectively. The first objective problem is maximizing spectral efficiency (SE) of the DAS with D2D communication under the constraints of the minimum SE requirements of user equipment (UE) and D2D pair, maximum transmit power of each remote access unit (RAU) and maximum transmit power of D2D transmitter. We transform this non-convex objective function into a difference of convex functions (D.C.) then using the concave-convex procedure (CCCP) algorithm to solve the optimization problem. The second objective is maximizing energy efficiency (EE) of the DAS with D2D communication under the same constraints. We first exploit fractional programming theory to obtain the equivalent objective function of the second problem with subtract form, and then transform it into a D.C. problem and use CCCP algorithm to obtain the optimal power allocation. In each part, we summarize the corresponding optimal power allocation algorithms and also use similar method to obtain optimal solutions of the same optimization problems in DAS. Simulation results are provided to demonstrate the effectiveness of the designed power allocation algorithms and illustrate the SE and EE of the DAS by using D2D communication are much better than DAS without D2D communication.

Large-scale distributed antenna systems (LS-DASs) are gaining increasing interest and emerging as highly promising candidates for future wireless communications. To improve the user's quality of service (QoS) in these systems, this study proposes a user cooperation aided clustering approach based on device-centric architectures; it enables multi-user multiple-input multiple-output transmissions with non-reciprocal setups. We actively use device-to-device communication techniques to achieve the sharing of user information and try to form clusters on user side instead of the traditional way that performs clustering on base station (BS) side in data offloading. We further adopt a device-centric architecture to break the limits of the classical BS-centric cellular structure. Moreover, we derive an approximate expression to calculate the user rate for LS-DASs with employment of zero-forcing precoding and consideration of inter-cluster interference. Numerical results indicate that the approximate expression predicts the user rate with a lower computational cost than is indicated by computer simulation, and the proposed approach provides better user experience for, in particular, the users who have unacceptable QoS.

Intensity modulated radiation therapy (IMRT), which irradiates doses to a target organ, calculates the irradiation dose using the radiation treatment planning system (RTPS). The irradiation quality is ensured by verifying that the dose distribution planned by RTPS is the same as the data measured by two-dimensional (2D) detectors. Since an actual three-dimensional (3D) distribution of irradiated dose spreads complicatedly, it is different from that of RTPS. Therefore, it is preferable to evaluate by using not only RTPS, but also actual irradiation dose distribution. In this paper, in order to perform a dose-volume histogram (DVH) evaluation of the irradiation dose distribution, we propose a method of correcting the dose distribution of RTPS by using sparsely measured radial data from 2D dose detectors. And we perform a DVH evaluation of irradiation dose distribution and we show that the proposed method contributes to high-precision DVH evaluation. The experimental results show that the estimates are in good agreement with the measured data from the 2D detectors and that the peak signal to noise ratio and the structural similarity indexes of the estimates are more accurate than those of RTPS. Therefore, we present the possibility of an evaluation of the actual irradiation dose distribution using measured data in a limited observation direction.

We consider a device-to-device (D2D) underlaid cellular network where D2D communications are allowed to share the same radio spectrum with cellular uplink communications for improving spectral efficiency. However, to protect the cellular uplink communications, the interference level received at a base station (BS) from the D2D communications needs to be carefully maintained below a certain threshold, and thus the BS coordinates the transmit power of the D2D links. In this paper, we investigate on-off power control for the D2D links, which is known as a simple but effective technique due to its low signaling overhead. We first investigate the optimal on-off power control algorithm to maximize the sum-rate of the D2D links, while satisfying the interference constraint imposed by the BS. The computational complexity of the optimal algorithm drastically increases with D2D link number. Thus, we also propose an on-off power control algorithm to significantly reduce the computational complexity, compared to the optimal on-off power control algorithm. Extensive simulations validate that the proposed algorithm significantly reduces the computational complexity with a marginal sum-rate offset from the optimal algorithm.

Sparse representation has been widely applied to visual tracking for several years. In the sparse representation framework, tracking problem is transferred into solving an L1 minimization issue. However, during the tracking procedure, the appearance of target was affected by external environment. Therefore, we proposed a robust tracking algorithm based on the traditional sparse representation jointly particle filter framework. First, we obtained the observation image set from particle filter. Furthermore, we introduced a 2D transformation on the observation image set, which enables the tracking target candidates set more robust to handle misalignment problem in complex scene. Moreover, we adopt the occlusion detection mechanism before template updating, reducing the drift problem effectively. Experimental evaluations on five public challenging sequences, which exhibit occlusions, illuminating variations, scale changes, motion blur, and our tracker demonstrate accuracy and robustness in comparisons with the state-of-the-arts.