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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.