To improve the positioning accuracy without reference stations, in this paper, we propose a multi-antenna and geometry based differential GNSS positioning system. Multiple independent antennas which simultaneously track the same satellites are connected to the receiver by cables and form a given geometry. Carrier phases of the signals received by those antennas are measured and differenced at the receiver. The single differences of phase cycle integer ambiguities are solved by exploiting the geometry formed by the antennas. Then the positions of multiple antennas are estimated firstly by using the differenced phase measurements and the geometric relationship between antennas. To further improve the antenna position accuracy, with multiple antennas and satellites available, the matrix of single differences of phase cycle integers is considered as a fingerprint to search and identify the final antenna positions. Taking advantage of the firstly estimated positions of antennas being in a regular geometric shape, the searching space for the antenna positions will be compressed and the searching process is simplified. Regularization method is employed to solve the ill-conditioned problem. Positioning error performance is evaluated by simulations. The proposed system can achieve lane level positioning accuracy without extra facilities. When the standard deviation of phase measurement error is less than 0.025 cycles, the proposed system can achieve high positioning accuracy. If the receiver can track satellites of more GNSS systems such as Global Positioning System (GPS) and BeiDou Navigation Satellite System (BDS) simultaneously, with eight or more satellites visible, the robustness of this system will be improved.

The Device-to-Device (D2D) communication underlaying cellular networks has advantages of improving the spectral utilization and throughput. This paper studies mode selection and resource allocation scheme for D2D communications underlaying cellular networks aiming to achieve a tradeoff of throughput and user satisfaction. An offline channel state information model based on geographic location is proposed to store offline channel state data which are used to estimate the SINR and data rate of the users. A resource assignment priority is defined by jointly considering the service priority, subscriber priority, and the distance between D2D users. The user’s achieved data rate and the resource assignment priority are combined to evaluate the user’s satisfaction with the revised Mean Opinion Score (MOS) index. A multi-objective optimization problem is formulated to maximize the sum rate and satisfaction of all users with resource assignment priority considered. The differential evolution algorithm is employed to solve this problem and the user satisfaction is measured by two defined metrics. Simulation results show that the proposed scheme can obtain a higher user satisfaction level at the cost of slightly reduced overall throughput of the system.

In this paper, we propose a bottom-up saliency model based on absorbing Markov chain (AMC). First, a sparsely connected graph is constructed to capture the local context information of each node. All image boundary nodes and other nodes are, respectively, treated as the absorbing nodes and transient nodes in the absorbing Markov chain. Then, the expected number of times from each transient node to all other transient nodes can be used to represent the saliency value of this node. The absorbed time depends on the weights on the path and their spatial coordinates, which are completely encoded in the transition probability matrix. Considering the importance of this matrix, we adopt different hierarchies of deep features extracted from fully convolutional networks and learn a transition probability matrix, which is called learnt transition probability matrix. Although the performance is significantly promoted, salient objects are not uniformly highlighted very well. To solve this problem, an angular embedding technique is investigated to refine the saliency results. Based on pairwise local orderings, which are produced by the saliency maps of AMC and boundary maps, we rearrange the global orderings (saliency value) of all nodes. Extensive experiments demonstrate that the proposed algorithm outperforms the state-of-the-art methods on six publicly available benchmark data sets.

In an emergency situation, cognitive radio nodes can be deployed temporarily to form an ad hoc network for data transmission by exploiting available spectrum. Based on some criteria, cognitive radio nodes can form multiple clusters which are connected to form the network. For emergency cognitive radio networks, the number of clusters is an important metric for the network performance evaluation. Hence, in this study, after a clustering scheme is presented briefly, the number of clusters that deployed cognitive radio nodes can form is analysed. First, the maximal number of clusters that can be formed in the given area is studied based on the strict arrangement of nodes. Second, the average number of clusters formed is analysed as the expected value of the number of clusters formed, for which the probability that M clusters are formed is investigated. Thirdly, the upper bound of network simultaneous transmission capacity is derived based on the result of the average number of clusters formed. Finally, simulations are conducted to verify the analytical results.

Cognitive radio nodes can form a wireless network automatically based on the “group” concept: In a given area, cognitive radio nodes are assumed to be activated randomly. Activated cognitive radio nodes form multiple “groups”. Each group consists of a leader node, some bridge nodes and regular nodes. Leader node is capable of communicating with any group member node, and bridge nodes connect different groups to form a scalable network. With this concept, incorporating the available spectrum, cognitive radio nodes can form a network without the constraint of common channel availability. This paper first proposes a scheme for the node communication, and then based on this scheme, analyzes the numbers of nodes and channels required to maintain full connectivity of the cognitive radio network formed for emergency situation. Finally, this paper investigates the connectivity of the group-based cognitive radio network with arbitrary topology.

The rapid growth of wireless industry and continuous emergence of new applications increase the demand for wireless spectrum. However, currently the spectrum assigned to different organisations is not utilised efficiently. Particularly, when an infrastructure of a service provider is overloaded and cannot accommodate more users because of the channel scarcity, the infrastructures of other service providers operating in the same area might be in under-loaded status. However, without a proper spectrum sharing scheme, the overloaded infrastructure cannot use the channels licensed to other service providers. This leads to low spectrum utilisation efficiency and higher call blocking rate of service providers. Significant research has been conducted to study sharing channels between cells within one service provider; however, sharing spectrum across different service providers is still under investigation. This paper proposes deploying a network of fixed cognitive radio (CR) nodes to maintain spectrum sharing across multiple service providers operating in the same geographical area. These CR nodes estimate the spectrum utilisation in a given area, and cooperate to provide the spectrum usage information for the overloaded infrastructures of service providers. This work discusses the implementation of the proposed CR-based spectrum sharing technique, and studies the impact of spectrum sharing on the service provider's performance. It is shown that the proposed technique reduces the call blocking rate and improves the spectrum utilisation efficiency. This technique removes the need of sensing spectrum in each user. Thus, it reduces the cost, complexity and battery power consumption of user devices.

Considering an ad hoc cognitive radio network, this paper presents channel assignment methods that can be used by a cognitive radio node to select a channel for communication. The proposed channel assignment methods aim to maximize spectral efficiency, minimize transmit power, or maximize data rate. When a number of available channels are detected, based on the proposed methods, a cognitive radio node can decide a suitable channel to use. These methods are executed distributively in cognitive radio nodes without using central controllers. This reduces the complexity of spectrum sharing in cognitive radio networks.

This paper presents a scheme for cognitive radio network construction. Incorporating the available spectrum, cognitive radio nodes automatically construct a local area network. The active cognitive radio nodes in an area form groups. Each group consists of a leader node, inter-group nodes and regular nodes. Inter-group nodes connect different groups to construct a network. Furthermore, the group leaders of different groups form virtual groups to facilitate the network management. The proposed scheme can also be used to construct large scale cognitive radio networks. Its applications include temporal network deployment in emergency situations and home appliance network construction.

In this paper, we propose a technique for predicting the traffic pattern of primary users in cognitive radio systems. Cognitive radios enable sharing the frequency bands that are licensed to primary users. By forecasting the traffic pattern of primary users, secondary users can estimate the utilization of frequency bands and select one for radio transmission to reduce the frequency hopping rate (the rate of switching from one frequency band to another) and the interference effects, while maintaining a reasonable blocking rate. In this work, we propose an algorithm for the prediction of call arrival rate which exploits the periodicity of the traffic process. In addition, we present an approach for call holding time estimation. The results are incorporated to evaluate the probability of the availability of a frequency band within a time period. Setting a threshold on this probability maintains a tradeoff between the blocking rate of secondary users, interference effects on primary users and spectrum efficiency. Simulations are conducted to investigate the performance of cognitive radio systems with and without traffic prediction.