To solve the problem that network services provided by ships can’t distinguish different users and the Quality of Service (QoS) is poor, an intelligent shipborne terminal system which combines advanced positioning technology and wireless communication technology is designed in this paper. The overall design of the system including hardware design and software design is proposed. The test results show that the system can distinguish between different users’ Wi-Fi connection, intelligentize the management of system users, realizes the function of GPS positioning navigation and has a rich local resource storage, which all proved its good application value.

Platoon-based Vehicular Ad-hoc Networks (VANETs) can significantly improve the road capacity and facilitate the potential cooperative communication applications. However, the communication links between platoon-based vehicles and the roadside unit (RSU) are unstable, which decrease the throughput and increase the delay, and cause the infotainment resources cannot be downloaded quickly. In this paper, we propose a collaborative download strategy in platoon-based VANETs to solve the problems. On the basis of RSUs support simultaneous communication with multiple vehicles, when a demand vehicle need to download multimedia files, we use the collaborative download request management mechanism to request other vehicles in the same RSU coverage area to participate in the collaborative download process. Besides, to decrease the download time, we divide the required multimedia files into multiple data packets. After the RSUs encode the data packets via linear network coding, the cooperative vehicles forward the received encoded packets to the demand vehicle. We also research the impact of speed and file size on the performance of cooperative download strategy. The simulation results show that the proposed cooperative download strategy can effectively increase throughput and reduce the downloading completion time when download multimedia files, especially when the size of multimedia files is large and the speed of platoon-based vehicles is fast.

Millimeter Wave (mmWave) combined with massive multiple-input multiple-output (MIMO) can provide wider bandwidth and higher spectrum efficiency. It has been considered as a key technique for future 5G wireless communications. However, hardware costs and power consumption make traditional MIMO processing impractical in such systems, because a large number of radio frequency (RF) chains are needed. To solve this problem, the beamspace MIMO concept is proposed in mmWave multiuser MIMO (MU-MIMO) systems, which utilizes beam selection algorithm based on the sparsity of beamspace channel to reduce the required RF chains without obvious performance loss. The existing beam selection algorithms mainly select the beam with the strongest gain, but ignore the inter-beam interference and the complexity. Thus, a novel algorithm based on the minimum interference (MI) criterion is proposed. Specifically, the performance of the beams is measured by defining the beamspace signal-to-interference ratio (SIR). When choosing beams, not only the gain of beams but also the interference to other users is considered. The simulation results demonstrate that the proposed algorithm can substantial reduce the complexity while ensuring better system performance.

In this paper, an energy-aware routing protocol based on network coding (NCEAR) is presented for wireless sensor networks which the energy is constrained. First, considering the rate matching problem of data flows, NCEAR adopts the distributed network coding to calculate the transmission cost of nodes, which reduces the energy consumption. In addition, NCEAR is capable of predicting the congestion degree of nodes through the energy consumption speed, thus balancing the network traffic. What’s more, in order to reduce the probability of link failure and the number of routing maintenance, the protocol takes nodes with the minimum residual energy into consideration and sets the minimum threshold. The simulation results show that compared with other protocols, NCEAR can effectively reduce energy consumption of the transmission, balance the network energy and traffic, prolong the network lifetime and improve the throughput.

In this paper, we deliberate on multiuser massive multiple-input multiple-output (MU-MIMO) system in designing optimal zero forcing (ZF) precoder under per antenna power constraint. MU massive MIMO with non-square matrix is restrained by the large channel matrix dimension, conjugate beamforming maximization approach is developed to align the channel matrix for the optimal ZF precoder. We further introduced complex lattice reduction (CLR) to transform the lattice bases of the channel matrix and shorten the basis vector, thus meliorates the orthogonality of the conjugate beamforming. Simulation results show LR-based optimal ZF precoder outperforms other precoding schemas. The LR-based optimal ZF precoder improved the beamforming for the base station (BS) to focus on the users, thus improving spatial multiplexing gain and diversity order. As BS antennas and users turn large, the sum rate over the subchannels depends on the dominance of users (that is BS antennas to user antennas ratio) for the channel gain. Thus performance of the LR-based precoder schema under per antenna power can help save power in practical massive MIMO implementation.

Detection of hierarchical and overlapping community structures for social networks is crucial in social network analysis. Previous strategies were focused on a two-stage strategy for separately detecting hierarchical and overlapping community structures. This paper develops a one-stage memetic algorithm for concurrently detecting hierarchical and overlapping community structures in social networks, where quality evaluation functions, community capacity, and hierarchical levels are taken into account to increase the solution quality. This algorithm includes a local search scheme to improve the solution searching ability. Through simulation, this algorithm shows pleasing quality.

In this paper, a novel efficient transmission scheduling algorithm for multihop mobile ad hoc networks (MANETs) with unidirectional links (ULs) is introduced. We propose an algorithm employing topology-transparent scheduling and erasure coding to support throughput guarantee over ULs in multihop MANATs. Our proposed algorithm can work over both unidirectional and bidirectional links, for both unicast and broadcast scenarios. We analytically study the performance of the proposed algorithm and achieve the maximum guaranteed throughput, for both unicast and broadcast scenarios. Simulations show that the proposed algorithm performs better than other topology-transparent algorithms over unidirectional links.

Coverage problem is essential to Wireless Sensor Networks on energy efficient deployment and monitoring. In this paper, we propose a distributed Čech complex algorithm for coverage hole detection in WSNs. Based on our algorithm, each node takes only local information to build Čech sub-complex. Simulations on randomly deployed nodes show that the algorithm achieves a comparable accuracy and a much lower communication cost than a centralized Čech complex construction. Furthermore, it can be combined with distributed Rips complex algorithm to gain an even better performance.

For low-density parity-check (LDPC) codes decoding by alternating direction method of multipliers (ADMM), the layered scheduling sequentially updates the messages of check nodes one by one. Though the layered scheduling can speed up the convergence rates, it may limit the throughput when implementing the ADMM decoder with multi-core systems due to its serial style. To circumvent this problem, a group-based layered scheduling is proposed by updating a group of check node messages at one time. Extensive simulation results for the proposed scheme over two typical LDPC codes with the ADMM penalized decoding algorithm are provided.

Most existing works on barrier coverage assume that sensors are deployed in a two-dimensional (2D) long thin belt region, where a barrier is a chain of sensors from one end of the region to the other end with overlapping sensing zones of adjacent sensors. However, 2D sensor barrier construction mechanism cannot be directly applied to three-dimensional (3D) sensor barrier construction problem, such as underwater sensor barrier construction, where sensors are finally distributed over a 3D space. In this paper, we investigate how to efficiently construct an underwater sensor barrier with minimum mobile sensors while reducing energy consumption. We first determine the minimum number of sensors needed for an underwater sensor barrier construction. Furthermore, we analyse the relationship between the initial locations of sensors and the optimal location of the underwater sensor barrier, based on which we derive the optimal final locations for all sensors. Finally, we propose an efficient algorithm to move sensors from their initial locations to final locations. Extensive simulations show that, compared with HungarianK approach, the proposed algorithm costs shorter running time and similar maximum movement distance of any one sensor.