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In this paper, a power allocation algorithm of dual-function radar–communication system with limited power is proposed to obtain better overall system performance measured by the weighted summation of radar signal to interference plus noise ratio (SINR) and communication channel capacity. First, a power allocation model is established to maximize the radar SINR and communication channel capacity with limited transmitted power. Then, the Karush–Kuhn–Tucker (KKT) conditions are used to solve the optimal objective function under the condition that only radar SINR or communication channel capacity is considered, respectively. Finally, the optimal value is combined with the original model and transformed into a single objective optimization model, and the optimal power is obtained by solving the model through the iterative optimization algorithm. Simulation results show that, compared with other power allocation algorithms, the proposed algorithm can achieve better radar-communication integration performance under the same transmit power. [ABSTRACT FROM AUTHOR]

This paper proposes a novel Very Large-Scale Integration (VLSI) design for the Turbo decoder, a popular communication tool to achieve optimal data reception with minimal errors. The Turbo decoder includes SISO decoders, interleavers, and deinterleavers, which use the Maximum-a-Posteriori (MAP) algorithm to reduce the number of iterations required for decoding. Additionally, the encoder part uses two Recursive convolutional encoders and a pseudorandom interleaver to enhance the error correction capability of the Turbo code. The paper also suggests using clock gating technology to improve the decoder's performance by selectively activating specific blocks based on the decoding performance. The proposed Turbo decoder is designed in Xilinx Vivado 2018.3 achieves high performance and provides a scalable and efficient solution for implementing Turbo decoders in communication systems. [ABSTRACT FROM AUTHOR]

Network energy resources are limited in communication systems, which may cause energy shortages in mobile devices at the user end. Active Reconfigurable Intelligent Surfaces (A-RIS) not only have phase modulation properties but also enhance the signal strength; thus, they are expected to solve the energy shortage problem experience at the user end in 6G communications. In this paper, a resource allocation algorithm for maximizing the sum of harvested energy is proposed for an active RIS-assisted Simultaneous Wireless Information and Power Transfer (SWIPT) system to solve the problem of low performance of harvested energy for users due to multiplicative fading. First, in the active RIS-assisted SWIPT system using a power splitting architecture to achieve information and energy co-transmission, the joint resource allocation problem is constructed with the objective function of maximizing the sum of the collected energy of all users, under the constraints of signal-to-noise ratio, active RIS and base station transmit power, and power splitting factors. Second, the considered non-convex problem can be turned into a standard convex problem by using alternating optimization, semi-definite relaxation, successive convex approximation, penalty function, etc., and then an alternating iterative algorithm for harvesting energy is proposed. The proposed algorithm splits the problem into two sub-problems and then performs iterative optimization separately, and then the whole is alternately optimized to obtain the optimal solution. Simulation results show that the proposed algorithm improves the performance by 45.2% and 103.7% compared to the passive RIS algorithm and the traditional without-RIS algorithm, respectively, at the maximum permissible transmitting power of 45 dBm at the base station. [ABSTRACT FROM AUTHOR]

Polar codes, as the coding scheme for the control channel in fifth-generation mobile communication technology (5G), have attracted widespread attention since their proposal. As a mainstream decoding algorithm for polar codes, the successive cancellation list (SCL) decoder usually improves the error correction performance by increasing the list size, but this method suffers from the problems of high decoding complexity. To address this problem, this paper proposes a layered-search bit-flipping (LS-SCLF) decoding algorithm based on SCL decoding. Firstly, a new flip-bit metric is proposed, which derives a formula to approximate the probability of an error occurring in an information bit. This formula introduces a perturbation parameter to improve the calculation accuracy. Secondly, a compromise scheme for determining the perturbation parameter is proposed. The scheme uses Monte Carlo simulation to determine an optimized parameter for the precise positioning of the first erroneous decoded bit under different decoding conditions. Finally, a layered search strategy is adopted to sequentially search the erroneous decoded bits from the low order to high order, which can correct up to multiple bits at the same time. Simulation results show that the proposed algorithm achieves improved error correction performance with a slight increase in decoding complexity compared to the generalized SCL-Flip (GSCLF) decoding algorithm. This algorithm also achieves a good balance between the error correction performance and decoding complexity. [ABSTRACT FROM AUTHOR]

Summary Unmanned aerial vehicle operations are quickly gaining ground due to rapid global market penetration. While on one hand, novel technologies that bridge communication networks to aviation industry are yet to be explored, on the other hand, their development requires highly scalable systems to enable beyond visual line‐of‐sight missions. This requirement imposes a big bottleneck in terms of computation complexity. This paper presents a method for fast computation of multiple diffraction of radio waves over knife‐edge obstacles based on the Deygout technique and some offline computation steps, including a ground profile analysis. We prove that this algorithm is equivalent to the original Deygout algorithm for all non‐line‐of‐sight points, show heuristics confirming that it is mostly applicable in the line‐of‐sight case. The computational and memory complexity of our algorithm is approximately O(N)$$ \mathcal{O}\left(\sqrt{N}\right) $$, compared to O(N)$$ \mathcal{O}(N) $$ for the original Deygout algorithm. Finally we discuss how to apply the approach to the Epstein‐Peterson technique and the Giovanelli technique, and how to use it to compute clutter‐loss. [ABSTRACT FROM AUTHOR]

Based on the millimetre-wave time-domain channel detector, this paper conducts channel measurement and modelling for different scenarios and antenna types in typical frequency bands and thus carries out a study on the propagation characteristics of millimetre-wave channels in typical frequency bands and scenarios for 5G. The time-varying characteristics and modelling methods of millimetre-wave clusters are studied, and the time-varying channel simulation strategy and linear regression fitting method are used to establish the time-varying generation and extinction model of clusters by combining the measured data of 26 GHz large-scale antenna channels. The algorithm is based on the correlation dictionary and achieves the efficient and optimal selection of large-scale antenna arrays in the millimetre-wave band. A low-complexity multiuser hybrid precoding design scheme is proposed based on the wideband millimetre-wave large-scale Multiple-Input Multiple-Output (MIMO) system. The scheme aims to maximize the system spectral efficiency and introduces the net spectral efficiency as a bridge to decouple the analogy precoding design from the digital precoding design, thus significantly reducing the computational complexity. In the analogy precoding stage, a Hungarian algorithm-based beam assignment method is proposed to avoid beam conflicts and maximize the net spectral efficiency of the system; in the digital precoding stage, the equivalent channel matrix of each subcarrier is diagonalized to eliminate multiuser interference. Finally, the effectiveness of the scheme is verified by simulation. In this paper, we focus on the radio frequency (RF) link and user selection algorithm of 5G mobile communication system. Through the study of these two aspects, the RF link of our communication system has high stability and reliability, and through the study of the algorithm used for selection, our results also have a strong practical value. [ABSTRACT FROM AUTHOR]

With the rapid growth of demand for wireless data services and the continuous introduction of new air interface technologies, mobile communication systems continue to face new challenges in supporting high-speed multimedia service transmission and achieving seamless coverage. In order to meet the requirements of the IMS system in terms of bandwidth, peak rate, communication throughput, etc., multiantenna enhancement technology and cooperative multipoint transmission technology have become research hotspots as key technologies. In the study of multiuser system, this paper focuses on the precoding technology based on noncode book, based on the minimum mean square error criterion and the maximum letter leakage noise ratio criterion, studies the precoding technology of different multiuser systems, expounds the collaborative multipoint transmission system, and makes a basic classification. The signal leakage-to-noise ratio precoding algorithm and the minimum mean square error precoding algorithm are analyzed in detail. In view of the shortcomings of these two algorithms, this paper takes the minimum sum of the total mean square error of the system as the optimization goal of the combinations of precoding and power allocation. The precoding algorithm of SLNR-MMSE is proposed. The simulation analysis shows that the proposed algorithm has certain advantages over other algorithms in terms of bit error rate and system capacity. It shows that this study is important for optimizing collaborative multipoint communication system. [ABSTRACT FROM AUTHOR]

As Mobile Communication and Internet Systems (MCIS) have rapidly developed, security issues related to MCIS have become increasingly important. Therefore, the development and research of security technologies for mobile communication and internet systems are actively being conducted. Hash-Based Signature (HBS) uses a hash function to construct a digital signature scheme, where its security is guaranteed by the collision resistance of the hash function used. To provide sufficient security in the post-quantum environment, the length of hash should be satisfied for the security requirement. Modern HBS can be classified into stateful and stateless schemes. Two representative stateful and stateless HBS are eXtended Merkle Signature Scheme(XMSS) and SPHINCS + , respectively. In this paper, we propose two HBS schemes: K-XMSS and K-SPHINCS + , which replace internal hash functions of XMSS and SPHINCS + with Korean cryptography algorithms. K-XMSS is a stateful signature, while K-SPHINCS + is its stateless counterpart. We showcase the reference implementation of K-XMSS and K-SPHINCS + employing Lightweight Secure Hash (LSH) and two hash functions based on block ciphers (i.e., CHAM and LEA) as the internal hash function. In addition, K-XMSS and K-SPHINCS + using Advanced Vector Extensions 2 (AVX2) have been provided, demonstrating that they can be optimized for better performance using advanced implementation techniques than previous approaches. [ABSTRACT FROM AUTHOR]

The multimedia applications and mobile communication systems require an efficient reconfigurable finite impulse response (RFIR) filter designs for achieving low area, power, cost, and high speed of system operation. In this paper, an efficient RFIR filter is designed based on the Radix-2 algorithm and Look-up-table Carry Select Adder (Radix 2 – LCSLA). Generally, the RFIR filter is controlled by multiplier and adder, which improves the performances of the filter. Hence, this research work is mostly concentrated on the multiplier and adder design. Here, the radix-2 algorithm is used instead of normal multiplier for multiplication operation in the RFIR filter design. Additionally, CSLA and LCSLA approaches used in the Radix-2 structure for adding partial products. The LCSLA has achieved better performance compared to the normal CSLA approaches. In this paper, both the Radix-2 algorithm and LCSLA approach improved the performances of the proposed RFIR filter design. The proposed RFIR filter design was implemented in the Xilinx and Cadence RTL compiler by using the Verilog code. The RFIR-Radix 2-LCSLA filter design was verified in the Modelsim by utilizing the Verilog code. The experimental result showed that the RFIR-Radix 2-LCSLA methodology has improved the performance of ASIC and FPGA in the RFIR filter design up to 5–15% compared to the existing filter architecture: DA-RFIR and LC-CBA-RFIR methods. [ABSTRACT FROM AUTHOR]

This paper presents an algorithm to optimize the base position of a mobile manipulator to meet the requirements of local painting tasks. Considering the physical limits and singularity of the manipulator, the feasible base positions are first discretely calculated with the given poses of the end effector by inverse kinematics. Then, the joint-level performance criteria are proposed with respect to the requirements of the painting process. The weight coefficients are also determined by the critic method to balance the contribution of every criterion. Thus, the globally near-optimal base position is selected by sorting all feasible positions according to the evaluation criteria. The experimental results show that the planning result is well executed and has an acceptable computation time, thus demonstrating that the algorithm is both practical and effective compared with previous methods. [ABSTRACT FROM AUTHOR]

Train-to-wayside (T2W) and train-to-train (T2T) communication modes may coexist in future train-centric communication-based train control (CBTC) systems. The feasibility of T2T communication in urban rail transit is analyzed first. Referring to the device-to-device (D2D) communication scenario in the general cellular network, this paper establishes a radio resource optimization model for the coexistence of train-to-train communication and train-to-wayside communication. With the aim of more efficient scheduling of radio time-frequency resources in the dedicated frequency band, we propose a Stackelberg game-based radio resource management algorithm based on the consideration of different service priorities of trains. The analysis and simulation results show that the proposed algorithm can effectively guarantee the performance of the system and improve the reliability of the CBTC system. [ABSTRACT FROM AUTHOR]

In 5G/6G mobile communication systems, MIMO or MASSIVE MIMO is the most promising evolving technology for implementation in recent times. Due to this scenario, it is bound to lead drastic interference circumstance, the most common Interference being Self Interference. In 3G/4G base stations, this situation may also arise in the existing mobile communication networks. Our Algorithm will address this severe Interference issue, thereby improving the QOS of the overall system. Each and Every step in our algorithm is being tested and integrated in a single flow, which is supported by Matlab simulation results and hardware implementation using GNU radio with SRSLTE emulation. [ABSTRACT FROM AUTHOR]

Pattern division multiple access (PDMA) is a new non-orthogonal multiple access (NOMA) technology. It is proposed to meet the challenge of 5G large-scale connectivity and high-frequency spectral efficiency. Compared with traditional orthogonal multiple access (OMA), PDMA can support more users through the allocation of non-orthogonal resources. Due to perfect aperiodic correlation, complete complementary sequence (CCS) greatly improves the spectrum efficiency of the system. It has been widely used in wireless communication and radar sensing, and it still has research value in 5G. In order to apply the advantages of CCS to NOMA communication system, this paper proposes a system model of CCS spread spectrum coding based on PDMA. CCS is used as spread spectrum code to improve the performance of PDMA communication system. At the same time, on the basis of spread spectrum technology, this paper analyzes the average power allocation algorithm and water-filling power allocation algorithm, and a dynamic power allocation algorithm based on the transmission rate and practical application is proposed. The simulation results show that the system model can effectively improve the performance of the system. [ABSTRACT FROM AUTHOR]

The importance of vocational efficiency has gradually grown in stature as a result of rapid population expansion, rapid urbanization, rising competitiveness in the labor market, and the growing requirement for specialist workforce. Around the world, there are several overarching trends in vocational education and training, including increased use of technology, increased relevance of information and communications systems and changes in country demographics. The main aim of this paper is to discuss a resource mining algorithm for vocational literacy-oriented civics courses. The exploratory data comes from a nearby vocational database partitioned into three segments: a record database, a data database, and a video database. The data sublibrary stores data like word-related types, collections, characters, archives, and photographs, though the video sublibrary stores general media data from the play. Indexes for both the data and video sublibraries can be found in the index sublibrary. In our proposed strategy for gathering vocational literacy resources on an organization stage, we have consolidated RFID remote sensor innovation with a remote organization convention stack. We utilized QGA to order the vocational literacy resources on the organization stage in light of the discoveries of the resource assortment. Besides, in the stage's vocational literacy materials, we joined the fluffy property highlight ID strategy with the semantic affiliation elements of successive examples. The trial results show that this approach outflanks customary techniques as far as resource mining time, mining result breadth, and mining result exactness, demonstrating that this strategy has useful application esteem. [ABSTRACT FROM AUTHOR]

In intelligent transportation systems (ITSs), the communication between the base station (BS) and the vehicles can form a virtual multiple-input multiple-out put (VMIMO) vehicle communication system. This paper addresses the issue of channel estimation in a virtual MIMO system that simultaneously adopt a smart antenna (SA). First, based on quaternion theory, a novel algorithm named quaternion noncircular MUSIC (QNC-MUSIC) is proposed, and direction of arrival (DOA) estimation is achieved for circular and noncircular signals. Then, a dimension reduction procedure is performed for the parameter search by employing the partial derivative of the spectrum function with respect to the noncircular phase; thus, a novel dimensional reduction noncircular MUSIC (DRNC-MUSIC) algorithm with a low computational complexity is proposed for DOA and polarization estimation of circular signals and noncircular signals. Finally, numerical examples are provided to demonstrate the parameter estimation performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The aim of the presented paper was to verify the impact of Dynamic PUCCH Resource Allocation Algorithm of the LTE cellular system on the maximum uplink cell throughput and call setup success rate - CSSR. Paper includes the laboratory testbed description and presents the results of an experiment confirming the improvement of both key performance indicators KPIs. Apart from the presentation of the Dynamic PUCCH Resource allocation algorithm, the paper also includes a description of legacy LTE uplink (PUCCH and PUSCH) channels dimensioning process thus filling the gap of such a tutorial in the available literature. [ABSTRACT FROM AUTHOR]

Small cells are introduced to cellular systems to enhance coverage and improve capacity. Densely deploying small cells can not only offload the traffic of macrocells but also provide an energy- and cost-efficient way to meet the sharp increase in traffic demands in mobile networks. However, such a cell deployment paradigm also leads to heterogeneous network (HetNet) infrastructure and raises new challenges for cell planning. In this paper, we study the cell planning issue in the HetNet. Our optimization task is to select a subset of candidate sites to deploy macro or small cells to minimize the total cost of ownership (TCO) or the energy consumption of the cellular system while satisfying practical constraints. We introduce approximation algorithms to cope with two different cell-planning cases, which are both NP-hard. First, we discuss the macrocell-only case. Our proposed algorithm achieves an approximation ratio of O(\log R) in this scenario, where R is the maximum achievable capacity of macrocells. Then, we introduce an O(\log \widetildeR)-approximation algorithm to the small-cell scenario, where \widetildeR is the maximum achievable capacity of a macrocell with small cells overlaid on it. Numerical results indicate that the HetNet can significantly reduce the TCO and the energy consumption of the cellular system. [ABSTRACT FROM PUBLISHER]

In this paper, a novel scheme is proposed to optimize the effectiveness of the device-to-device (D2D) enabled vehicular communications (D2D-V), which are underlaid in cellular networks, where the uplink channel allocated to one cellular user (CU) is reused by the multiple D2D-V links. To develop a well-functioning D2D-V system, the sum rate of all D2D-V links is necessary to be maximized, and also the reliability of the co-channel CU to infrastructure has to be guaranteed with the CU interference constraint. Unlike the traditional statical D2D systems, the D2D-V system suffers with high mobility and channel uncertainty. Therefore, the CU interference constraint is formulated as a probabilistic function by the Bernstein approximation, the constraint attempts to address the mobile channel fluctuations. Besides, the tractable approximate constraint is reformulated as two separable structure, this reformulated constraint attempts to determine the near-optimal solutions more efficiently. Since the objective function with a logarithmic form is nonconvex, successive convex approximation is applied to transform the nonconvex problem into the convex problem. The dual decomposition is used to determine the near-optimal solutions. After the problem is reformulated, a distributed robust power control algorithm is proposed to perform the chance-constrained optimization. Numerical simulations are used to evaluate the performance of the proposed scheme. The simulation results show the impacts of system performance when applying the proposed scheme in vehicular environments with high mobility. The proposed optimization schemes are further verified by comparing with the existing methods. [ABSTRACT FROM AUTHOR]

How to stimulate the devices to participate is a key problem in the device-to-device (D2D) communications, especially when there are multiple base stations in practice. On one hand, the base station needs to lower the price to compete with other base stations for attracting more devices. On the other hand, the base station needs to increase the price to obtain more benefit. In this paper, we propose an optimal multiprincipal multiagent contract design to tackle such a challenge. Specifically, we formulate the multiprincipal contract design problem as a game theoretic optimization problem, where the objective of each principle (base station) through contract design is to maximize its overall utility obtaining from the trade with agents (devices) subject to the individual rationality and incentive compatibility constraints. By solving the game theoretic optimization problems, we can obtain the equilibrium contract where the contracts of different principals reach an equilibrium and any deviation from a single principal will lead to the degradation of its own utility. Moreover, under the equilibrium, both the individual rationality and incentive compatibility constraints are satisfied, i.e., all agents will choose the corresponding contract according to their types to reach the optimal nonnegative utilities. Simulation results show that compared with the monoprincipal contract design, both the utilities of devices and the social welfare can be improved with the multiprincipal contract design. [ABSTRACT FROM AUTHOR]

Currently 5G communication networks are envisioned to offer in a near future a wide range of high-quality services and unfaltering user experiences. In order to achieve this, several issues including security, privacy, and trust aspects need to be solved so that the 5G networks can be widely welcomed and accepted. Considering above, in this paper, we take a step towards these requirements by proposing a dedicated SDN-based integrated security framework for the Internet of Radio Light (IoRL) system that is following 5G architecture design. In particular, we present how TCP SYN-based scanning activities and DHCP-related network threats like Denial of Service (DoS), traffic eavesdropping, etc. can be detected and mitigated using such an approach. Enclosed experimental results prove that the proposed security framework is effective and efficient and thus can be considered as a promising defensive solution. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) is a promising scheme for the fifth generation (5G) of mobile communication systems. In this scheme, transmission to multiple users is performed on the same subchannel using superposition coding and successive interference cancellation. In this paper, we focus on a multi-cell network with two users’ data traffic models, namely elastic and streaming. We exploit the NOMA scheme in order to maximize the download elastic traffic rate at cells, without degrading the download streaming traffic rates. Since elastic traffic rates at different cells are interactive, we maximize the total elastic traffic rates assuming either perfect or partial channel state information available at each base station subject to a target rate for streaming users. Because of the interference due to NOMA as well as the interference among different cells, subchannel assignment and power allocation affect the system performance significantly. For this reason, we propose an iterative algorithm to jointly solve the subchannel assignment and the power allocation problem via the Hungarian algorithm and successive convex approximation, respectively. Finally, our simulation results show the efficiency of the proposed algorithm. [ABSTRACT FROM AUTHOR]

With the rapid development of the mobile internet and the internet of things (IoT), the fifth generation (5G) mobile communication system is seeing explosive growth in data traffic. In addition, low-frequency spectrum resources are becoming increasingly scarce and there is now an urgent need to switch to higher frequency bands. Millimeter wave (mmWave) technology has several outstanding features--it is one of the most well-known 5G technologies and has the capacity to fulfil many of the requirements of future wireless networks. Importantly, it has an abundant resource spectrum, which can significantly increase the communication rate of amobile communication system. As such, it is now considered a key technology for future mobile communications. MmWave communication technology also has a more open network architecture; it can deliver varied services and be applied inmany scenarios. By contrast, traditional, all-digital precoding systems have the drawbacks of high computational complexity and higher power consumption. This paper examines the implementation of a new hybrid precoding system that significantly reduces both calculational complexity and energy consumption. The primary idea is to generate several sub-channels with equal gain by dividing the channel by the geometric mean decomposition (GMD). In this process, the objective function of the spectral efficiency is derived, then the basic tracking principle and least square (LS) techniques are deployed to design the proposed hybrid precoding. Simulation results show that the proposed algorithm significantly improves system performance and reduces computational complexity by more than 45% compared to traditional algorithms. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surfaces (IRSs) are considered one of the core technologies in sixth-generation (6G) mobile communication. In this paper, we investigate an aerial IRS (AIRS)-enhanced cell-free (CF) massive multiple-input-multiple-output (MIMO)system where multiple APs serve a high-speed mobile user simultaneously. The mobility of the user leads to fast time-varying and nonnegligible Doppler frequency offsets (DFOs), which cause a serious threat to link performance. To overcome the influence of the Doppler effect and reduce the energy consumption of the system, we propose a Doppler compensation and transmission method by using the AIRS. Specifically, we divide the AIRS reflection phase shift vector into two parts: one part is used for Doppler compensation, and the other is used for transmission. First, we propose an angle-sensing algorithm to obtain the user angle in each coherent time (CT) and use it to design a Doppler compensation vector. Then, we propose an angle information-aided transmission strategy to design the transmission reflecting vector, the beamforming vector, and the power allocation coefficient of each AP to minimize the transmission power of all APs at a required achievable rate. The simulation results show that we can significantly reduce the total transmission power by using the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, the secure transmission for high-speed railway (HSR) communication system is studied. The considered HSR wireless communication system consists of a macro base station, B roadside base stations, and K vehicle stations (VSs) on the top of the train, and the eavesdropping user is a mobile unmanned aerial vehicle (UAV). We consider maximizing the sum of the minimum security rate of each time slot as the objective function, and the constraint conditions contain the quality of service (QoS), switch requirements and the total power constraint. The original optimization problem is mixed-integer and non-convex, it is intractable to solve directly. The block coordinate descent (BCD) method is applied, and the original problem can be decoupled into two sub-problems. The one is the joint BS-VS association problem, and the other is the power control problem. The first sub-problem of optimizing BS-VS association can be solved by the successive convex approximation (SCA) algorithm, and the second one of optimizing transmit power can be solved by the lagrangian dual method. Simulation results show that the proposed algorithms have good convergence. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) applications are connecting several Mobile Stations (MSs) to form the Mobile Communication Network (MCN). MSs are moving through macrocell and picocell recurrently due to the discontinuous deployment of the picocell over the macrocell. Each time they cross the cell boundary, they need to register with the Mobility Management Entity (MME). It incurs a high registration cost and elevates the signaling overhead ratio. To reduce the signaling overhead ratio, earlier techniques were attempted either by forming closed subscriber groups or by delaying the registration process, but that may create inconsistency in user location information. With this motivation, in this paper, MSs with similar mobility pattern which are moving from the picocell to macrocell, are grouped in clusters. A representative MS, called Cluster Representative (CR), performs the location management task on behalf of the whole cluster. The stochastic process has been employed to analyze the model. This study proposes Cluster-Based Location Management (CBLM) scheme and compares it with two state-of-the-art algorithms, named Group Mobility Management (GMM) and Closed Subscriber Group (CSG). On average, the CBLM scheme exhibits approximately 70% better performance than the CSG scheme whereas, 30% better than the GMM algorithm to mitigate the signaling overhead. [ABSTRACT FROM AUTHOR]

In opportunistic mobile networks (OppNets), a large amount of energy is consumed by idle listening, instead of infrequent data exchange. This makes energy saving a challenging and fundamental problem in OppNets since nodes are typically battery powered. Asynchronous duty-cycle operation is a promising approach for energy saving in OppNets; however, if its working schedule is not effectively designed, it may also cause significant network performance degradation. Therefore, it is pressing to design an energy-efficient working schedule for duty-cycle OppNets. In this paper, we first analyze the contact process in duty-cycle OppNets and then propose an adaptive working schedule for duty-cycle OppNets. The proposed adaptive working schedule uses the past recorded contact histories to predict future contact information to adaptively configure the working schedule of each node in the network. Finally, extensive real trace-driven simulations are conducted to evaluate the performance of our proposed adaptive working schedule. Extensive real trace-driven simulation results demonstrate that our proposed adaptive working schedule is superior to the random working schedule and the periodical working schedule algorithms in terms of the number of effect contacts, delivery ratio, and delivery delay. [ABSTRACT FROM AUTHOR]

Passenger trains and especially metro trains have been identified as one of the key scenarios for 5G deployments. The wireless channel inside a train car is reported in the frequency range between 26.5 GHz and 40 GHz. These bands have received a lot of interest for high-density scenarios with a high-traffic demand, two of the most relevant aspects of a 5G network. In this paper we provide a full description of the wideband channel estimating Power-Delay Profiles (PDP), Saleh-Valenzuela model parameters, time-of-arrival (TOA) ranging, and path-loss results. Moreover, the performance of an automatic clustering algorithm is evaluated. The results show a remarkable degree of coherence and general conclusions are obtained. [ABSTRACT FROM AUTHOR]

Electronic travel aids (ETAs) have been in focus since technology allowed designing relatively small, light, and mobile devices for assisting the visually impaired. Since visually impaired persons rely on spatial audio cues as their primary sense of orientation, providing an accurate virtual auditory representation of the environment is essential. This paper gives an overview of the current state of spatial audio technologies that can be incorporated in ETAs, with a focus on user requirements. Most currently available ETAs either fail to address user requirements or underestimate the potential of spatial sound itself, which may explain, among other reasons, why no single ETA has gained a widespread acceptance in the blind community. We believe there is ample space for applying the technologies presented in this paper, with the aim of progressively bridging the gap between accessibility and accuracy of spatial audio in ETAs. [ABSTRACT FROM AUTHOR]

The diffusion of Device-to-Device (D2D) communications opens the door to exploit the contributions of multiple Mobile Devices (MDs) to accomplish collaborative tasks. In this paper a speaker recognition algorithm for MDs based on a multiple-observations approach is presented. We propose various fusion and clustering algorithms aimed at efficiently exploiting data coming from MDs. Numerical results show that in many cases our multiple-observation approach is able to significantly improve the accuracy of the considered speaker recognition algorithm. [ABSTRACT FROM AUTHOR]

It is expected that next-generation wireless networks will provide a plethora of mobile wireless services to users and ubiquitous network coverage at all times. Meeting these expected goals requires that new and existing networks be seamlessly integrated together to form Heterogeneous Wireless Networks (HWNs). Thus, seamless and efficient handover mechanisms are pertinent for optimal network performance in HWNs; so that the mobile user can switch from one access network to another, in search of the best connection for the demanded services. The HWNs' performance can be reduced, if efficient network selection is not achieved. In HWNs, network-selection decisions can be evaluated by using multi-criteria, or a single criterion. However, network selection and decision-making in HWNs often involves taking into account a large number of complex and conflicting network-decision factors, or criteria. Thus multi-criteria decision-making techniques are more efficient than single-criterion techniques. Multi-Criteria Decision-Making (MCDM) techniques comprise of a developed branch of operational research for assisting in the resolution of complex decision-making problems. MCDM is an important tool that has been used to model and analyze handover-decisions and network-selection problems in HWNs. This paper reviews and classifies the most significant MCDM algorithms that have been used to address the network decision-making problems in HWNs in terms of algorithmic approach, the type of calls, the cardinality of decision criteria employed, handover-control points and the types of network utilities. Comprehensive step-wise mathematical implementations of the reviewed MCDM schemes are presented, while pointing out their strengths and limitations. This paper review fills a research gap in the investigation on network-selection criteria's interdependence and interactions, and their effects on criteria's weight of importance. It then provides an insight into the importance of network-criteria weighting and the current research trend in the application of MCDM algorithms to network-selection problems in HWNs. [ABSTRACT FROM AUTHOR]

Random interleavers are the most preferred interleavers utilized in digital and cellular communication systems for burst errors control. Fisher-Yates shuffling algorithm and its several modified versions offer alternate techniques of generating random permutations popularly employed in the areas of computer programming, information theory and cryptography for data security purposes. In this short paper, Modern Fisher-Yates shuffling algorithm, also known as Durstenfeld's algorithm, has been explored to generate random interleavers and further applied in single carrier frequency division multiple access based interleave division multiple access (SCFDMA-IDMA) systems. The results show that random interleavers generated by applying this algorithm are suitable enough to be employed in SCFDMA-IDMA system without compromising its performance. [ABSTRACT FROM AUTHOR]

Because mobile ad hoc networks have characteristics such as lack of center nodes, multi-hop routing and changeable topology, the existing checkpoint technologies for normal mobile networks cannot be applied well to mobile ad hoc networks. Considering the multi-frequency hierarchy structure of ad hoc networks, this paper proposes a hybrid checkpointing strategy which combines the techniques of synchronous checkpointing with asynchronous checkpointing, namely the checkpoints of mobile terminals in the same cluster remain synchronous, and the checkpoints in different clusters remain asynchronous. This strategy could not only avoid cascading rollback among the processes in the same cluster, but also avoid too many message transmissions among the processes in different clusters. What is more, it can reduce the communication delay. In order to assure the consistency of the global states, this paper discusses the correctness criteria of hybrid checkpointing, which includes the criteria of checkpoint taking, rollback recovery and indelibility. Based on the designed Intra-Cluster Checkpoint Dependence Graph and Inter-Cluster Checkpoint Dependence Graph, the elimination rules for different kinds of checkpoints are discussed, and the algorithms for the same cluster checkpoints, different cluster checkpoints, and rollback recovery are also given. Experimental results demonstrate the proposed hybrid checkpointing strategy is a preferable trade-off method, which not only synthetically takes all kinds of resource constraints of Ad hoc networks into account, but also outperforms the existing schemes in terms of the dependence to cluster heads, the recovery time compared to the pure synchronous, and the pure asynchronous checkpoint advantage. [ABSTRACT FROM AUTHOR]

Delay, cost, and loss are low in Low Earth Orbit (LEO) satellite networks, which play a pivotal role in channel allocation in global mobile communication system. Due to nonuniform distribution of users, the existing channel allocation schemes cannot adapt to load differences between beams. On the basis of the satellite resource pool, this paper proposes a network architecture of LEO satellite that utilizes a centralized resource pool and designs a combination allocation of fixed channel preallocation and dynamic channel scheduling. The dynamic channel scheduling can allocate or recycle free channels according to service requirements. The Q-Learning algorithm in reinforcement learning meets channel requirements between beams. Furthermore, the exponential gradient descent and information intensity updating accelerate the convergence speed of the Q-Learning algorithm. The simulation results show that the proposed scheme improves the system supply-demand ratio by 14%, compared with the fixed channel allocation (FCA) scheme and by 18%, compared with the Lagrange algorithm channel allocation (LACA) scheme. The results also demonstrate that our allocation scheme can exploit channel resources effectively. [ABSTRACT FROM AUTHOR]

The 5G mobile communication system is coming with a main objective, known also as IMT-2020, that intends to increase the current data rates up to several gigabits per second. To meet an accompanying demand of the super high-speed encryption, EIA and EEA algorithms face some challenges. The 3GPP standardization organization expects to increase the security level to 256-bit key length, and the international cryptographic field responds actively in cipher designs and standard applications. SNOW-V is such a proposal offered by the SNOW family design team, with a revision of the SNOW 3G architecture in terms of linear feedback shift register (LFSR) and finite state machine (FSM), where the LFSR part is new and operates eight times the speed of the FSM, consisting of two shift registers and each feeding into the other, and the FSM increases to three 128-bit registers and employs two instances of full AES encryption round function for update. It takes a 128-bit IV, employs 896-bit internal state and produces 128-bit keystream blocks. The result is competitive in pure software environment, making use of both AES-NI and AVX acceleration instructions. Thus, the security evaluation of SNOW-V is essential and urgent, since there is scarcely any definite security bound for it. In this paper, we propose a byte-based guess-and-determine attack on SNOW-V with complexity |$2^{406}$| using only seven keystream blocks. We first improve the heuristic guessing-path auto-searching algorithm based on dynamic programming by adding initial guessing set, which is iteratively modified by sieving out the unnecessary guessing variables, in order to correct the guessing path according to the cipher structure and finally launch smaller guessing basis. For the specific design, we split all the computing units into bytes and rewrite all the internal operations correspondingly. We establish a backward-clock linear equation system according to the circular construction of the LFSR part. Then we further simplify the equations to adapt to the input requirements of the heuristic guessing-path auto-searching algorithm. Finally, the derived guessing path needs modification for the pre-simplification and post-reduction. This is the first complete guess-and-determine attack on SNOW-V as well as the first specific security evaluation to the full cipher. [ABSTRACT FROM AUTHOR]

Confidentiality and integrity processes are based on SNOW and ZUC algorithms. These standardized algorithms are designed by the 3rd Generation Partnership Project (3GPP) for advanced mobile communication systems. Each algorithm has two S-boxes in its nonlinear layer structure. This paper proposes three different approaches to enhance the security level of both algorithms. The first approach aims to select the best combination of two S-boxes in the nonlinear part of each algorithm. Results showed that the best randomness properties are achieved by combining the Feistel structure (S1-box) and Rijndael (S2-box) in the SNOW algorithm and New Rijndael (S1-box) and Rijndael (S2-box) in the ZUC algorithm. The second approach aims to increase the nonlinearity and complexity of these algorithms by selecting a strong S-box to cascade the best-existing two S-boxes for both algorithms. The third approach is an extension of the former, based on a dynamic reform of such S-boxes as a function of the "Authentication Token" to increase the computational complexity of the upgraded two algorithms. These proposed upgrades are simulated by C language and tested successfully for their statistical properties using the standard NIST SP 800-22 test suite. [ABSTRACT FROM AUTHOR]

Vehicle-to-everything (V2X) communication has been widely studied in recent years for the rapid development of the vehicular traffic. In this paper, a V2X communication system integrating the probabilistic shaping (PS) bitloading multi-input-multi-output (MIMO) visible light communication (VLC) and the millimeter wave radar is proposed. The PS bitloading algorithm utilizes the full spectrum resource of the LED headlights, and the MIMO configuration enhances the performance of the VLC system. Furthermore, the linear and nonlinear interpolation method makes it possible to calculate the SNR at every point from the SNR measured at several discrete calibration points. The SNR table enables the radar to guide the VLC according to the distance, achieving the highest achievable information rate (AIR) at every point. The system supports the V2X communication beyond 1.1 Gb/s up to 5 m. This is the first VLC based V2X sensing and communication system, and the AIR in the system is 1.8484 Gb/s. As far as we know, it is the highest data rate reported in the LED headlight based VLC system. [ABSTRACT FROM AUTHOR]

In this paper, we study the problem of secure localization in Mobile Wireless Sensor Networks (MWSNs) where beacon nodes are not available. The location reference information is obtained from neighboring nodes within the commination rage of the target node, with the help of a relative location map. A Relative Location Map based Robust Positioning Algorithm (RLMRPA) for MWSNs is presented. The location estimate of the localizing node is formulated by constructing a distance measurement error model. Considering limited resources available, the steepest descent, which is fast and easy to implement, is employed to iteratively find the optimal solution. A 3- Farthest Neighbors Trilateral Localization Algorithm (3FNTLA) is presented to find the initial position. Considering that malicious neighbors tend to cause larger distance measurement errors and the further the neighbor, the larger the measurement error, an attack-resistant distance residue method is developed to neutralize the impact of inconsistent measurements. Our experiments show that the RLMRPA can perform secure location determination, even with some neighbors aiming at making the localization failed. In addition, our simulation results also demonstrate that the RLMRPA is more resistant to attacks and achieves higher localization accuracy than existing methods. [ABSTRACT FROM AUTHOR]

Mobility with high degree of network-facility is a mandatory attribute for better QoS in cellular networks, but it leads to a huge increment in energy consumption, a significant fraction of which related to the base stations within the service area. In this paper, we are introducing a base station cooperation technique for energy efficiency in mobile communication networks, and it is based on nature-inspired computing, especially the Bee system. All serving base stations within a given geographical area will work together to provide a better network experience to the mobile subscriber. In order to achieve this, base stations will check for availability of unutilized (or underutilized) bandwidth and if it is over a certain threshold, all base stations perform a re-reunion procedure to provide a uniform distribution of the consumed bandwidth (bandwidth load), thereby providing better service to users. We have formulated the proposed technique to determine the effectiveness, efficiency and scalability of work. Further we create a simulation setup for proposed algorithm using OPNET to implement a real time cellular networks. It has been observed that results of proposed work have sufficient improvement in energy efficiency at the base station with respect to traditional schemes. [ABSTRACT FROM AUTHOR]

In this paper, we propose a unified framework to generate a pleasant and high-quality street-view panorama by stitching multiple panoramic images captured from the cameras mounted on the mobile platform. Our proposed framework is comprised of four major steps: image warping, color correction, optimal seam line detection and image blending. Since the input images are captured without a precisely common projection center from the scenes with the depth differences with respect to the cameras to different extents, such images cannot be precisely aligned in geometry. Therefore, an efficient image warping method based on the dense optical flow field is proposed to greatly suppress the influence of large geometric misalignment at first. Then, to lessen the influence of photometric inconsistencies caused by the illumination variations and different exposure settings, we propose an efficient color correction algorithm via matching extreme points of histograms to greatly decrease color differences between warped images. After that, the optimal seam lines between adjacent input images are detected via the graph cut energy minimization framework. At last, the Laplacian pyramid blending algorithm is applied to further eliminate the stitching artifacts along the optimal seam lines. Experimental results on a large set of challenging street-view panoramic images captured form the real world illustrate that the proposed system is capable of creating high-quality panoramas. Keywords: panorama stitching; seam line detection; image warping; graph cuts; image parallax; image blending; color correction [ABSTRACT FROM AUTHOR]

In the era of mobile internet, Location Based Services (LBS) have developed dramatically. Seamless Indoor and Outdoor Navigation and Localization (SNAL) has attracted a lot of attention. No single positioning technology was capable of meeting the various positioning requirements in different environments. Selecting different positioning techniques for different environments is an alternative method. Detecting the users' current environment is crucial for this technique. In this paper, we proposed to detect the indoor/outdoor environment automatically without high energy consumption. The basic idea was simple: we applied a machine learning algorithm to classify the neighboring Global System for Mobile (GSM) communication cellular base station's signal strength in different environments, and identified the users' current context by signal pattern recognition. We tested the algorithm in four different environments. The results showed that the proposed algorithm was capable of identifying open outdoors, semi-outdoors, light indoors and deep indoors environments with 100% accuracy using the signal strength of four nearby GSM stations. The required hardware and signal are widely available in our daily lives, implying its high compatibility and availability. [ABSTRACT FROM AUTHOR]

Featured Application: User terminal positioning based on the 5G system or other ground-based wireless systems. Cellular communication systems support mobile phones positioning function for Enhanced-911 (E-911) location requirements, but the positioning accuracy is poor. The fifth-generation (5G) cellular communication system can use indoor distribution systems to provide accurate multiple time-difference-of-arrival (TDOA) and single time-of-arrival (TOA) measurements, which could significantly improve the indoor positioning ability. Unlike iterative localization algorithms for TDOA or TOA, the existing closed-form algorithms, such as the Chan-Ho algorithm, do not have convergence problems, but can only estimate position based on one kind of measurement. This paper proposes a closed-form localization algorithm for multiple TDOAs and single TOA measurements. The proposed algorithm estimates the final position result using three-step weighted least squares (WLSs). The first WLS provides an initial position for the last two steps. Then the algorithm uses two WLSs to estimate position based on heteroscedastic TDOA and TOA measurements. In addition, the geometric dilution of precision (GDOP) of the proposed hybrid TDOA and TOA positioning has been derived. The analysis of GDOP shows that the proposed hybrid positioning has lower GDOP than TDOA-only positioning, which means the proposed hybrid positioning has a higher accuracy limitation than TDOA-only positioning. The simulation shows that the proposed localization algorithm could have better performance than closed-form TDOA-only positioning methods, and the positioning accuracy could approximate Cramer-Rao lower bound (CRLB) when the TDOA measurement errors are small. [ABSTRACT FROM AUTHOR]

Deploying femtocells underlaying macrocells is a promising way to improve the capacity and enhance the coverage of cellular systems. However, such a two-tier network also gives rise to a cross-tier and intratier interference issue that should be properly addressed to acquire the potential performance gain. In this paper, we study the resource-allocation (RA) problem in a two-tier orthogonal frequency-division multiplexing (OFDM) access-based heterogeneous cellular network, where the femtocells that employ a closed access strategy are equipped with a cognitive radio (CR) function to identify radio environment so that they can share subchannels with the macrocells without generating excessive interference to the macrocell users (MUs), which fall into the coverage of the femtocells. We formulate an optimization task to maximize the sum throughput of the femtocell users (FUs) under the consideration of imperfect spectrum sensing and channel uncertainty while controlling the interference to the MUs below their bearable thresholds in the sense of probability. We introduce a conservative convex approximation to the formulated problem and develop a fast algorithm to solve it by exploiting its structure. Simulation results show that our proposal can improve the throughput of the FUs with almost no changes in the infrastructure of the cellular network. [ABSTRACT FROM PUBLISHER]

Spectral efficiency improvement is essential for mobile systems development in the light of growing demand for high data transmission rate. The Time-domain synchronous OFDM transmission system increases bandwidth utilization by time-domain channel estimation without any support from frequency-domain pilot signals. Channel identification methods use a training sequence, added at the beginning of every OFDM symbol. Sparse nature of the channel impulse response, which manifests itself during wireless broadband transmission, enables one to implement compressed sensing techniques for channel identification. Channel sparsity reduces the number of measurement samples required in channel reconstruction procedure, but they should be taken from the inter-block interference (IBI) free part of the received training sequence. If maximum delay spread of the channel is comparable with the length of the training sequence, the number of measurements within the IBI-free region may be insufficient for accurate channel identification. This paper discusses a new iterative approach to sparse channels estimation, which uses the measurements from outside the IBI-free region. The proposed solution is examined for simulated transmission over randomly generated doubly-selective channels when compared with the conventional CS technique and perfect channel state information condition. The experiments reveal an enhancement of the transmission quality in terms of SER for slow-time selective channels when both delays and gains of the channel impulse response are estimated with the orthogonal matching pursuit algorithm. Further improvement, also for transmission over moderate varying channels, is observed when the path delays are found in advance. A suitable frame structure is proposed to do so. [ABSTRACT FROM PUBLISHER]

The introduction of fourth-generation wireless technologies has fueled the rapid development of cellular networks, significantly increasing the energy consumption and the expenditures of mobile network operators (MNOs). In addition, network underutilization during low-traffic periods (e.g., night zone) has motivated a new business model, namely, infrastructure sharing, which allows the MNOs to have their traffic served by other MNOs in the same geographic area, thus enabling them to switch off part of their network. In this paper, we propose a novel infrastructure-sharing algorithm for multioperator environments, which enables the deactivation of underutilized base stations during low-traffic periods. Motivated by the conflicting interests of the MNOs and the necessity for effective solutions, we introduce a game-theoretic framework that enables the MNOs to individually estimate the switching-off probabilities that reduce their expected financial cost. Our approach reaches dominant strategy equilibrium, which is the strategy that minimizes the cost of each player. Finally, we provide extensive analytical and experimental results to estimate the potential energy and cost savings that can be achieved in multioperator environments, incentivizing the MNOs to apply the proposed scheme. [ABSTRACT FROM AUTHOR]

Radio propagation models (RPMs) are generally employed in Vehicular Ad Hoc Networks (VANETs) to predict path loss in multiple operating environments (e.g. modern road infrastructure such as flyovers, underpasses and road tunnels). For example, different RPMs have been developed to predict propagation behaviour in road tunnels. However, most existing RPMs for road tunnels are computationally complex and are based on field measurements in frequency band not suitable for VANET deployment. Furthermore, in tunnel applications, consequences of moving radio obstacles, such as large buses and delivery trucks, are generally not considered in existing RPMs. This paper proposes a computationally inexpensive RPM with minimal set of parameters to predict path loss in an acceptable range for road tunnels. The proposed RPM utilizes geometric properties of the tunnel, such as height and width along with the distance between sender and receiver, to predict the path loss. The proposed RPM also considers the additional attenuation caused by the moving radio obstacles in road tunnels, while requiring a negligible overhead in terms of computational complexity. To demonstrate the utility of our proposed RPM, we conduct a comparative summary and evaluate its performance. Specifically, an extensive data gathering campaign is carried out in order to evaluate the proposed RPM. The field measurements use the 5 GHz frequency band, which is suitable for vehicular communication. The results demonstrate that a close match exists between the predicted values and measured values of path loss. In particular, an average accuracy of 94% is found with R2 = 0.86. [ABSTRACT FROM AUTHOR]

The device-to-device (D2D) communication, as a high-speed communication from device to device, has attracted large researchers' attention recently. Namely, by using the D2D communication in the cellular networks, mobile users can transmit data to the adjacent users at a faster rate. As a result, a large part of cellular data traffic can be diverted, reducing the overhead of data transmission from the base station and saving the energy as well as improving the spectrum efficiency. However, in the heterogeneous networks where cellular and D2D communication coexists when the D2D devices are connected to the network, the network performance is not only affected by the slow and fast fading factors, but also by the access network selection strategy and network switching factors. With the aim to improve the network performance, this paper proposes a game theory-based D2D network access algorithm for heterogeneous networks. The proposed algorithm can adapt to the dynamic changes of the network environment while avoiding unnecessary switching by considering the properties of the user equipment and network utilization, and thus improving the network throughput and reducing the delay. The experimental results demonstrate that the proposed algorithm has better performance than the flow algorithm. [ABSTRACT FROM AUTHOR]

Current anonymity techniques for mobile opportunistic networks typically use obfuscation algorithms to hide node's identity behind other nodes. These algorithms are not well suited to sparse and disconnection prone networks with large number of malicious nodes and new opportunistic, adaptive. So, new, opportunistic, adaptive fully localized mechanisms are needed for improving user anonymity. This paper proposes reputation aware localized adaptive obfuscation for mobile opportunistic networks that comprises of two complementary techniques: opportunistic collaborative testing of nodes' obfuscation behaviour (OCOT) and multidimensional adaptive anonymisation (AA). OCOT-AA is driven by both explicit and implicit reputation building, complex graph connectivity analytics and obfuscation history analyses. We show that OCOT-AA is very efficient in terms of achieving high levels of node identity obfuscation and managing low delays for answering queries between sources and destinations while enabling fast detection and avoidance of malicious nodes typically within the fraction of time within the experiment duration. We perform extensive experiments to compare OCOT-AA with several other competitive and benchmark protocols and show that it outperforms them across a range of metrics over a one month real-life GPS trace. To demonstrate our proposal more clearly, we propose new metrics that include best effort biggest length and diversity of the obfuscation paths, the actual percentage of truly anonymised sources' IDs at the destinations and communication quality of service between source and destination. [ABSTRACT FROM PUBLISHER]

Highlights • We provide computational intelligence method for different levels of the system. • We describe the development direction of the intelligent system. • We introduce the basic state-of-the-art concepts of data mining. • We validate the performance of the model with discussions on applications. Abstract The integration of intelligent system mainly includes the application of intelligent technology, such as artificial intelligence and computational intelligence method, which is used in different levels of the system. This paper introduces the application and technology of several intelligent system integrations, the advantages and disadvantages of learning theory and expert system. Neural network is applied in intelligent systems and we use scope reviewed several new development of intelligent technology, plus this paper describes the development direction of the intelligent system. This paper introduces the basic concepts of data mining, including data mining technology, artificial intelligence, machine learning, statistical analysis, fuzzy logic, pattern recognition and artificial neural networks and other technologies. We analyze the structure of the general algorithm of data mining, and classify the data mining technology in details, including more than 10 techniques of decision tree technology, neural network technology, rough set and fuzzy set. Finally, the research directions of data mining in artificial intelligence, e-commerce applications and mobile communication computing are discussed. [ABSTRACT FROM AUTHOR]

In this paper, we focus on the incentive mechanism design for a vehicle-based, nondeterministic crowdsensing system. In this crowdsensing system, vehicles move along their trajectories and perform corresponding sensing tasks with different probabilities. Each task may be performed by multiple vehicles jointly so as to ensure a high probability of success. Designing an incentive mechanism for such a crowdsensing system is challenging since it contains a non-trivial set cover problem. To solve this problem, we propose a truthful, reverse-auction-based incentive mechanism that includes an approximation algorithm to select winning bids with a nearly minimum social cost and a payment algorithm to determine payments for all participants. Moreover, we extend the problem to a more complex case in which the Quality of sensing Data (QoD) of each vehicle is taken into consideration. For this problem, we propose a QoD-aware incentive mechanism, which consists of a QoD-aware winning-bid selection algorithm and a QoD-aware payment determination algorithm. We prove that the proposed incentive mechanisms have truthfulness, individual rationality, and computational efficiency. Moreover, we analyze the approximation ratios of the winning-bid selection algorithms. The simulations, based on a real vehicle trace, also demonstrate the significant performances of our incentive mechanisms. [ABSTRACT FROM AUTHOR]

The exponential growth of mobile traffic means that operators must upgrade their mobile networks to provide higher capacity to final users. A promising alternative is to deploy heterogeneous networks (HetNets) that combine macro Base Stations (BSs) and SmallCells (SCs), although this increases the complexity and cost of the transport (SCs to Fiber Access Point–FAP). Most of the planning strategies outlined in the literature are aimed at reducing the number of SCs and ignore the impact that the transport segment might have on the total cost of network deployment. In this paper, heuristics are used for the joint planning of radio (i.e., SCs) and transport resources (i.e., point-to-point fiber links). These were compared and examined to determine the advantages and disadvantages of each approach, and in some cases, this led to a 50% reduction in total costs, while still creating a non-scalable network. [ABSTRACT FROM AUTHOR]