Real-Time Wireless Sensor Network-Assisted Smart Tourism Environment Suitability Assessment for Tourism IoT

In this paper, we conduct an in-depth study and analysis of the suitability of real-time wireless sensor network-assisted smart tourism environment for tourism IoT and evaluate its suitability. We use nodes in wireless sensor networks as relays and collaborative transmission using mutual information accumulation. Using riteless codes, nodes can accumulate information in advance to decode out the original text. Due to the mobility of mobile robots, the planned routing paths can fail quickly, so we propose a dynamic mutual information accumulation collaborative transmission algorithm. For both cases of information transmission from the cloud to the robot and from the robot to the cloud, we dynamically acquire routing paths using neighbour search and chance transmission, respectively. Experimental results show that our dynamic mutual information accumulation collaborative transfer algorithm has lower time complexity and latency. We use a cooperative transmission algorithm with mutual information accumulation, because wireless transmission has the nature of broadcasting, and all neighbour nodes can receive part of the information when the sender starts to transmit information. Riteless codes are used in single-hop transmissions to improve the probability of successful transmissions. Since transmission failure requires waiting for the next neighbour to wake up, which consumes a lot of energy and time in a low duty cycle environment, using riteless codes to improve the transmission success rate of single-hop transmissions can effectively improve the global transmission efficiency. Experimental results show that the opportunity routing algorithm using riteless codes has lower delay and energy consumption. The two major systems, surface, and underground are used to quantitatively measure 23 indicators in five subsystems, including geological environment, soil and water environment, sensitive geological bodies, groundwater resources, and mineral resources, to evaluate the two-way grade of underground space development suitability, revealing the comprehensive bearing characteristics of the study area with an overall high bearing capacity of underground space resources and environment and an overall surplus of bearing status.

A Novel Cooperative Network Using Down-link Non-orthogonal Multiple Access Scheme

A novel downlink cooperative non-orthogonal multiple access (DC-NOMA) scheme is proposed in this paper to achieve higher performance in the spectral efficiency compared to the classical NOMA schemes. The communication system consists of one base station and two users (e.g., strong user and weak user). In down link phase, the base station transmits a superimposed signal to both users, and in the cooperative phase, the weak user sends its decoded message to the strong user. The main idea is how the weak user can help the strong user to improve the performance of both users. This occurs by enabling the weak user to perform a cooperative transmission with the strong user during the cooperative phase. The outage probability, outage throughput, and diversity order are derived and analyzed. Numerical results are provided to show that the spectral efficiency gain achieved through our proposed scheme is better than the conventional cooperative NOMA schemes.

Contract Theory-Based Incentive Mechanism for Full Duplex Cooperative NOMA with SWIPT Communication Networks

Cooperative Non-Orthogonal Multiple Access (NOMA) with Simultaneous Wireless Information and Power Transfer (SWIPT) communication can effectively improve the spectrum efficiency and energy efficiency of the wireless networks with extend coverage. An important design issue is to incentivize a relaying center user to participate in the cooperative process and achieve a win-win situation to both the BS and the center user. Some private information of the center users are hidden from the BS in the networks. We apply a contract theory-based incentive mechanism under such asymmetric information scenario to incentives center user to join the cooperative communication to maximize the BS profit utility and to guarantee the center user’s expect payoff. A match theory-based Gale-Shapley algorithm is proposed to obtain the optimal strategy with low computation complexity. Simulation results indicated the network performance of our proposed cooperative transmission is much better than the conventional NOMA transmission and the benefit utility of the BS with the stable match strategy is nearly close to the complete channel state information multi-users scenario while the center users get the satisfied expect payoffs.

Improving Physical Layer Security of Cooperative NOMA System with Wireless-Powered Full-Duplex Relaying

Non-orthogonal multiple access (NOMA) and wireless energy harvesting are two promising technologies for improving spectral efficiency and energy efficiency, respectively. In this paper, we study the physical layer security of a wireless-powered full-duplex (FD) relay-aided cooperative NOMA system. In particular, the source is wiretapped by an eavesdropper, and the FD relay assists the transmission from the source to a near user and a far user with self-energy recycling. To enhance the security performance of the system, we propose an artificial noise (AN)-aided cooperative transmission scheme, in which the relay emits a jamming signal to confuse the eavesdropper while receiving the signal from the source. For the proposed scheme, the ergodic secrecy sum rate (ESSR) is derived to characterize the secrecy performance and a lower bound of ESSR is obtained. Finally, numerical results verify the accuracy of the theoretical analysis of the proposed AN-aided secure transmission scheme. The superiority of the proposed scheme is also demonstrated since this scheme can achieve better secrecy performance, compared to the conventional cooperative NOMA scheme.

Performance Analysis and Optimization of a Cooperative Transmission Protocol in NOMA-Assisted Cognitive Radio Networks with Discrete Energy Harvesting

In this paper, we propose a spectrum-sharing protocol for a cooperative cognitive radio network based on non-orthogonal multiple access technology, where the base station (BS) transmits the superimposed signal to the primary user and secondary user with/without the assistance of a relay station (RS) by adopting the decode-and-forward technique. RS performs discrete-time energy harvesting for opportunistically cooperative transmission. If the RS harvests sufficient energy, the system performs cooperative transmission; otherwise, the system performs direct transmission. Moreover, the outage probabilities and outage capacities of both primary and secondary systems are analyzed, and the corresponding closed-form expressions are derived. In addition, one optimization problem is formulated, where our objective is to maximize the energy efficiency of the secondary system while ensuring that of the primary system exceeds or equals a threshold value. A joint optimization algorithm of power allocation at BS and RS is considered to solve the optimization problem and to realize a mutual improvement in the performance of energy efficiency for both the primary and secondary systems. The simulation results demonstrate the validity of the analysis results and prove that the proposed transmission scheme has a higher energy efficiency than the direct transmission scheme and the transmission scheme with simultaneous wireless information and power transfer technology.

Opportunistic Large Array Propagation Models: A Comprehensive Survey

Enabled by the fifth-generation (5G) and beyond 5G communications, large-scale deployments of Internet-of-Things (IoT) networks are expected in various application fields to handle massive machine-type communication (mMTC) services. Device-to-device (D2D) communications can be an effective solution in massive IoT networks to overcome the inherent hardware limitations of small devices. In such D2D scenarios, given that a receiver can benefit from the signal-to-noise-ratio (SNR) advantage through diversity and array gains, cooperative transmission (CT) can be employed, so that multiple IoT nodes can create a virtual antenna array. In particular, Opportunistic Large Array (OLA), which is one type of CT technique, is known to provide fast, energy-efficient, and reliable broadcasting and unicasting without prior coordination, which can be exploited in future mMTC applications. However, OLA-based protocol design and operation are subject to network models to characterize the propagation behavior and evaluate the performance. Further, it has been shown through some experimental studies that the most widely-used model in prior studies on OLA is not accurate for networks with networks with low node density. Therefore, stochastic models using quasi-stationary Markov chain are introduced, which are more complex but more exact to estimate the key performance metrics of the OLA transmissions in practice. Considering the fact that such propagation models should be selected carefully depending on system parameters such as network topology and channel environments, we provide a comprehensive survey on the analytical models and framework of the OLA propagation in the literature, which is not available in the existing survey papers on OLA protocols. In addition, we introduce energy-efficient OLA techniques, which are of paramount importance in energy-limited IoT networks. Furthermore, we discuss future research directions to combine OLA with emerging technologies.

Application of Large-Scale Cognitive Social Networks Based on Cooperative Transmission Mechanisms in Exploration of Flipped Classroom Teaching Strategy

With the deepening of the research on flipped classroom teaching theory, the flipped classroom teaching model has gradually been applied to classroom teaching at all levels and types of schools, and some beneficial results and experiences have been obtained. Due to the relatively low self-learning ability and motivation level of students, in the implementation of flipped classrooms, the quality of preclass self-study links is difficult to guarantee, resulting in unsatisfactory results of flipped classroom teaching in secondary vocational schools. This article aims to solve the current dilemma faced by the optimization of the flipped classroom teaching mode of programming courses by studying the course platform based on the flipped classroom teaching model. The source-destination node distribution is constructed with a model based on node affinity to restore the actual network node distribution architecture. The change in the distribution of source-destination nodes has led to different degrees of aggregation in the overall data flow of the network. After that, the capacity and delay performance of the primary network and the secondary network will change as the degree of data flow aggregation changes. By laying base stations in the main network, we reanalyzed the network. Through the comprehensive analysis of students’ learning status through the scores of students in class and the test situation after class, we modify the specific teaching plan of flipped classroom. Experiments have proved that the in-class flipping model we proposed effectively avoids the inherent shortcomings of students who are not strong in autonomous learning before class, solves the problem that secondary vocational students cannot do well in autonomous learning before class, and improves students to a certain extent. The results show that the flipped classroom teaching model in class can provide more powerful value for vocational teaching to achieve this goal.