查看更多>>摘要：Abstract With the support of GIS spatial analysis technology, based on an in-depth study of the wireless propagation environment of a city, combined with the analysis of project requirements, it proposes to use the SPM model to correct the propagation model parameters, using SPM. The wireless propagation model, and research and analysis of the SPM wireless propagation model correction algorithm, further corrected the parameters of a city's SPM wireless propagation model. On this basis, the propagation loss of several classic propagation models in different environments is compared, and the SPM propagation model suitable for the signal frequency band and propagation environment of this study is selected. The correction of the SPM propagation model is based on the designed correction principle and correction process, that is, the weighted least square method is used to fit and analyze the measured level data to obtain an SPM prediction improvement model with local characteristics, and according to the designed verification link. Evaluation of the correction results shows that the accuracy requirements are met. Based on the corrected SPM prediction model, link loss calculations were performed on the 13 test base stations studied in the experiment, and the effective coverage radius of each base station community was obtained. In combination with GIS technology, model parameters and workers of each base station participated in the electronic map loading of the area Go to the network planning software to get the wireless signal coverage prediction map of each base station. Finally, according to the technical requirements of the TD-LTE system network planning and network optimization engineering, the objectiveness and rationality of the site selection and number of base stations in the area were verified, and specific problems regarding poor coverage and overlapping coverage in the area were proposed.
查看更多>>摘要：Abstract In order to realize the automation of transport equipment, according to the automatic guided vehicle (AGV) kinematics model, the trajectory tracking control of AGV with front wheel steering and rear wheel drive is studied. Lyapunov function is used to ensure the global stability of the system. Time-varying state feedback method based on integral backstepping is adopted, introducing virtual feedback, a trajectory tracking controller for AGV with nonholonomic constraints is proposed. In order to ensure the smooth motion of AGV, the speed and acceleration limited strategy of AGV is introduced into the controller. Simulation results show that the algorithm is fast, accurate and globally stable for different paths.
查看更多>>摘要：Abstract Machine learning is a branch of the field of artificial intelligence. Deep learning is a complex machine learning algorithm that has unique advantages in image recognition, speech recognition, natural language processing, and industrial process control. Deep learning has It is widely used in the field of wireless communication. Prediction of geological disasters (such as landslides) is currently a difficult problem. Because landslides are difficult to detect in the early stage, this paper proposes a GPS-based wireless communication continuous detection system and applies it to landslide deformation monitoring to achieve early treatment and prevention. This article introduces the GPS multi-antenna detection system based on deep learning wireless communication, and introduces the time series analysis method and its application. The test results show that the GPS multi-antenna detection system of the wireless communication network has great advantages in response time, with high accuracy and small error. The horizontal accuracy is controlled at 0–2?mm and the vertical accuracy is about 1?mm. The analysis method is simple and efficient, and can obtain good results for short-term deformation prediction.
查看更多>>摘要：Abstract With the development and wide applications of wireless communication technology, the limited spectrum resources and the fixed spectrum allocation policy could no longer satisfy the demand for wireless communication. Just for this reason, many spectrum resources become spectrum holes because they are allocated but not used. Cognitive radio is now becoming one of the most important techniques for high utility of these spectrum holes. If the holes available to cognitive users are abundant over a certain time, it is a worth consideration to increase network throughputs by orthogonal multiplexing as many as spectrum holes. A multi-transceiver configuration is one of the possible solutions for this purpose. With such a schema, all transceivers within a cognitive user work in a concurrent or parallel mode, by which the throughput of the network can be increased. However, co-site working cognitive radios may incur electromagnetic interference between each other. When more cognitive radios are equipped, much electromagnetic interference may be incurred. Many techniques are proposed to mitigate such so-siting interference; however, none of them have addressed the probability that the interference will happen. If the probability could be estimated in advance, the user will make a better planning on the configurations of the co-siting working radios. Based on an elaborated n-fold multiple integral model, we propose a novel method to decide how many cognitive radios can be installed for one cognitive user at most. This is our main contribution with this work, providing an enhanced ability to determine the optimal number of cognitive radios installed within each cognitive user. We make a strict deduction on electromagnetic compatibility probability with various parameters of cognitive radios. Simulations are performed and the results show that the electromagnetic compatibility of the simulated cognitive radio system meets the deducted probability by this method very well.
查看更多>>摘要：Abstract Network slicing, as a key technique of 5G, provides a way that network operators can segment multiple virtual logic on the same physical network and each customer can order specific slicing which can meet his requirement of 5G service. The service level agreement of network slicing (NS-SLA) of 5G, as a business agreement signed between the network operators and the customers, specifies the relevant requirements for the 5G services provided by the network operators. However, the authenticity of auditing results may not be guaranteed and the customer’s data may be leaked in the existing NS-SLA audit scheme. In this paper, a blockchain-based 5G network slicing NS-SLA audit model is proposed to address the above problems. The blockchain is applied as a public platform and all the dual monitored service parameters will be stored on the blockchain to ensure the authenticity of data. A trapdoor order-revealing encryption algorithm is introduced to audit strategy, which can encrypt the monitored parameters, realize the comparison over ciphertexts and prevent the privacy of data from leaking. Besides, an NS-SLA audit smart contract is designed to implement the audit task and execute corresponding punishment strategies automatically. We make experiments to exam the cost of the blockchain-based system and the results found clear support for the feasibility of the proposed model.
查看更多>>摘要：Abstract The pervasive cooperation of a group of UAVs has attracted increasing attention due to the reduced cost and widespread availability. When working in an untrusted or adversarial environment, the mutual authentication of UAVs in the cooperative process is imperative. However, there are some major challenges, including changes in the network environment before and during task performing, and the weak connection network state faced by UAVs. Therefore, a novel task-oriented authentication model for UAVs based on blockchain (ToAM) is proposed, which divides UAVs authentication into group building authentication and intra-group authentication with a two-stage authentication framework. And two lightweight authentication protocols are presented, respectively, corresponding to two stages. Finally, analyses demonstrate that our model realizes secure and lightweight authentication function for the whole process of UAVs requisition and task performing.
查看更多>>摘要：Abstract Energy efficiency is a key requirement for future network design, and user-centric (UC) cell-free (CF) massive multi-input multi-output (MIMO) networks can achieve over ten times the energy efficiency. Based on this, this paper studies a CF MIMO simultaneous wireless information and power transmission system and proposes a UC access point (AP) selection method and a trade-off performance optimization scheme for spectral efficiency and energy efficiency. In this system, users have both energy recovery and information transmission functions. According to the difference between the interference in the energy harvesting and information transmission process, a flexible AP selection scheme is designed. Blindly pursuing high spectral efficiency will result in waste of resources. This paper proposes an evaluation index that takes into account both energy efficiency and spectral efficiency, analyses the trade-off between energy efficiency and spectral efficiency, and jointly optimizes the AP selection scheme and the uplink (UL) and downlink (DL) time switching ratio to maximize the trade-off performance. Then, the non-convex problem is converted to a geometric planning problem to solve. The simulation results show that by implementing a suitable AP selection scheme and UL and DL time allocation, the information processing scheme on the AP side has a slight loss in spectral efficiency, but the energy efficiency is close to the performance of global processing on the central processing unit.
查看更多>>摘要：Abstract Blockchain technology has attracted considerable attention due to the boom of cryptocurrencies and decentralized applications. Among them, the emerging blockchain-based crowdsourcing is a typical paradigm, which gets rid of centralized cloud-servers and leverages smart contracts to realize task recommendation and reward distribution. However, there are still two critical issues yet to be solved urgently. First, malicious evaluation from crowdsourcing requesters will result in honest workers not getting the rewards they deserve even if they have provided valuable solutions. Second, unfair evaluation and reward distribution can lead to low enthusiasm for work. Therefore, the above problems will seriously hinder the development of blockchain-based crowdsourcing platforms. In this paper, we propose a new blockchain-based crowdsourcing framework with enhanced trustworthiness and fairness, named TFCrowd. The core idea of TFCrowd is utilizing a smart contract of blockchain as a trusted authority to fairly evaluate contributions and allocate rewards. To this end, we devise a reputation-based evaluation mechanism to punish the requester who behaves as “false-reporting” and a Shapley value-based method to distribute rewards fairly. By using our proposed schemes, TFCrowd can prevent malicious requesters from making unfair comments and reward honest workers according to their contributions. Extensive simulations and the experiment results demonstrate that TFCrowd can protect the interests of workers and distribute rewards fairly.
查看更多>>摘要：Abstract The explosive growth of big data is pushing forward the paradigm of cloud-based data store today. Among other, distributed storage systems are widely adopted due to their superior performance and continuous availability. However, due to the potentially wide attacking surfaces of the public cloud, outsourcing data store inevitably raises new concerns on user privacy exposure and unauthorized data access. Besides, directly introducing a centralized third-party authority for query authorization management does not work because it still can be compromised. In this paper, we propose a blockchain-assisted framework that can support trustworthy data sharing services. In particular, data owners allow to outsource their sensitive data to distributed systems in encrypted form. By leveraging smart contracts of blockchain, a data owner can distribute secret keys for authorized users without extra round interaction to generate the permitted search tokens. Meanwhile, such blockchain-assisted framework naturally solves the trust issues of query authorization. Besides, we devise a secure local index framework to support encrypted keyword search with forward privacy and mitigate blockchain overhead. To validate our design, we implement the prototype and deploy it at Amazon Cloud. Extensive experiments demonstrate the security, efficiency, and effectiveness of the blockchain-assisted design.
查看更多>>摘要：Abstract In this research, we study soft-output decoding of polar codes. Two representative soft-output decoding algorithms are belief propagation (BP) and soft cancellation (SCAN). The BP algorithm has low latency but suffers from high computational complexity. On the other hand, the SCAN algorithm, which is proposed for reduced complexity of soft-output decoding, achieves good decoding performance but suffers from long latency. These two algorithms are suitable only for two extreme cases that need very low latency (but with high complexity) or very low complexity (but with high latency). However, many practical systems may need to work for the moderate cases (i.e., not too high latency and not too high complexity) rather than two extremes. To adapt to the various needs of the systems, we propose a very flexible soft-output decoding framework of polar codes. Depending on which system requirement is most crucial, the proposed scheme can adapt to the systems by controlling the level of parallelism. Numerical results demonstrate that the proposed scheme can effectively adapt to various system requirements by changing the level of parallelism.
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