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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]

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]

Computation offloading technology in an FEC (Fog/Edge Computing) environment requires the process of transmitting code/data and execution results from a mobile device (MD) to an edge server (ES). In this case, a mobile agent may be used for efficient transmission of code/data. However, the mobile agent migrates with task processing commands and execution results at the time of migration, which can cause time delays and reliability degradation problems due to increased size. This paper proposes a method of securing the applicability and reliability of the mobile agent system by implementing migration algorithm and a method of reducing the weight of the mobile agent for computation offloading. In addition, we demonstrate the legitimacy of the proposed method based on the results of the migration and mounting module execution experiment of the mobile agent equipped with code/data in the FEC environment and the comparative analysis experiment of the migration time according to the size of the mobile agent. [ABSTRACT FROM AUTHOR]

With the rapid growth in cellular user quantity and quality of service demand, the resource allocation in device-to-device communication system significantly affects the overall efficiency and user experience. In this study, the resource allocation for large-scale device-to-device communication system is modelled as a constrained optimization problem with thousands of dimensionalities. Then, the variable-coupling relationship of the developed model is analysed and the mathematical proof is firstly provided, and a novel algorithm namely multi-modal mutation cooperatively coevolving particle swarm optimization is developed to optimize the ultra-high dimensional model. Finally, efficacy of the developed method is verified by a comprehensive set of case studies, some famous algorithms for the specialized literature are also employed for comparison. Experimental results shown that the developed algorithm can obtain accurate and robust optimization performance for different system scales. In addition, when the system scale increases to 1000 cellular users and 300 D2D-pair users, the developed method can still outperform the compared algorithms and output accurate resource allocation solution. [ABSTRACT FROM AUTHOR]

Signal modulation recognition is often reliant on clustering algorithms. The fuzzy c-means (FCM) algorithm, which is commonly used for such tasks, often converges to local optima. This presents a challenge, particularly in low-signal-to-noise-ratio (SNR) environments. We propose an enhanced FCM algorithm that incorporates particle swarm optimization (PSO) to improve the accuracy of recognizing M-ary quadrature amplitude modulation (MQAM) signal orders. The process is a two-step clustering process. First, the constellation diagram of the received signal is used by a subtractive clustering algorithm based on SNR to figure out the initial number of clustering centers. The PSO-FCM algorithm then refines these centers to improve precision. Accurate signal classification and identification are achieved by evaluating the relative sizes of the radii around the cluster centers within the MQAM constellation diagram and determining the modulation order. The results indicate that the SC-based PSO-FCM algorithm outperforms the conventional FCM in clustering effectiveness, notably enhancing modulation recognition rates in low-SNR conditions, when evaluated against a variety of QAM signals ranging from 4QAM to 64QAM. [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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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 UWAC (underwater acoustic communication), UWA (underwater acoustic) channels change rapidly due to varying environment conditions. AMC (adaptive modulation and coding) is an efficient technique to improve system efficiency by changing transmission parameters according to channel conditions in UWA channels. In this paper, we propose an environmental cognition orthogonal frequency division multiplexing (OFDM) UWAC system and compare it with AMC algorithm with six transmission modes together with three threshold detection algorithms. Simulation and experimental results show the effectiveness of the proposed system. The system will play an important role in future communication networks which can significantly improve the efficiency of the system. [ABSTRACT FROM AUTHOR]

In order to solve the problems of low-risk assessment accuracy and long time-consuming assessment of current wireless mobile communication systems, a wireless mobile communication system based on artificial intelligence algorithms is proposed. First, the research status of risk assessment of wireless mobile communication system at home and abroad is analyzed, and the risk assessment index system of wireless mobile communication system is established; then, the learning samples are collected according to the risk assessment index system of wireless mobile communication system, and artificial intelligence algorithm is used to optimize the neural network. Build the wireless mobile communication system risk assessment model; finally, carry out the wireless mobile communication system risk assessment simulation comparison test. The experimental results show that the accuracy rate of the risk assessment of the wireless mobile communication system by the artificial intelligence algorithm is over 95%, and the assessment error is smaller than in other models. The risk assessment time of the wireless mobile communication system is significantly reduced, the real-time performance is better, and it has a higher practical application value. [ABSTRACT FROM AUTHOR]

One of the major challenges in developing various practical communication systems is reducing device complexity and development costs. In this study, a linear sparse array antenna design problem is addressed and a new approach for density taper element spacing by using the spacing coefficient algorithm is proposed. This method is a mathematical approach to obtain the distance between array elements by developing a spacing coefficient d n for each element to achieve radiation performances with a minimum number of antenna elements. The simulation and measurement results show a significant improvement in array performance compared to other sparse array design methods, such as the CDS sparse array method in our previous work. [ABSTRACT FROM AUTHOR]

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 mobile communication systems, various mobile convergence services are appearing and data traffic is exploding accordingly. Because the number of base stations to support these surging devices is also increasing, from a network provider's point of view, reducing energy consumption through these mobile communication networks is one of the most important issues. Therefore, in this paper, we apply the DBSCAN (density-based spatial clustering of applications with noise) algorithm, one of the representative user-density based clustering algorithms, in order to extract the dense area with user density and apply the thinning process to each extracted sub-network to efficiently control the mode of the base stations. Extensive simulations show that the proposed algorithm has better performance results than the conventional algorithms with respect to area throughput and energy efficiency. [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]

In this paper, we propose a deep learning-based scheduling scheme for user selection in multi-user multi-antenna networks which is considered one of key technologies for the next generation mobile communication systems. We obtained 90,000 data samples from the conventional optimal scheme to train the proposed neural network and verified the trained neural network to check if the trained neural network is over-fitted. Although the proposed neural network-based scheduling algorithm requires considerable complexity and time for training in the initial stage, it does not cause any extra complexity once it has been trained successfully. On the other hand, the conventional optimal scheme continuously requires the same complexity of computations for every scheduling. According to extensive computer-simulations, the proposed deep learning-based scheduling algorithm yields about 88~96% average sum-rates of the conventional scheme for SNRs lower than 10dB, while it can achieve optimal average sum-rates for SNRs higher than 10dB. [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]

In order to extend fair queueing algorithms to wireless networks, we propose a channel error and handoff compensation scheme. A compensation is performed by a compensation server and a priority swapping mechanism. The proposed compensation scheme provides a short-term fairness guarantee for an error-free session, long-term fairness guarantee for an erroneous session, fast handoff and traffic-specific quality of service control. Copyright 2002 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Massive MIMO(Multiple-Input Multiple-Output) technology is one of the most important physical layer technologies in 5 g and even 6G. In the process of wireless transmission, due to the complexity of the propagation environment, the signal is vulnerable to thousands of interference, resulting in the final received synthetic signal composed of standard signal and interference signal. With the development of science and technology, artificial intelligence has penetrated into signal processing and achieved good results. Multi user game theory in artificial intelligence algorithm is considered to be one of the most important theoretical achievements of Applied Mathematics in this century. The devices in the communication network interfere with each other and have a competitive relationship. To solve this problem, combined with the game theory of artificial intelligence algorithm, the equipment in the communication network is modeled as the players participating in the competition in the game theory, and the array factor of the base station transmitting antenna array is adjusted according to the channel conditions and service requirements of different equipment. In order to make the Nash equilibrium point converge, an array factor update algorithm is designed. Finally, the performance of the algorithm is verified in simulation. [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]

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]

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]

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Application Research of Computers / Jisuanji Yingyong Yanjiu is the property of Application Research of Computers Edition and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

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]