Global navigation satellite system (GNSS) is not suitable for the dense urban or indoor environments as the satellite signals are very weak. Meanwhile, positioning is an important application of the fifth-generation (5G) communication system. GNSS/5G integrated positioning system becomes a promising research topic with the development of 5G standard. This paper focuses on the integrated methodology of GNSS and device to device (D2D) measurements in 5G communication system. We analyze the characteristics of this type of integrated system and propose a high-efficiency D2D positioning measure protocol, named crossover multiple-way ranging, which consumes less communication resources. Then, to deal with the high-dimensional state space in the integrated system, a state dimension reduction method is proposed to overcome the particle degeneracy problem of particle filter which is used to fusion GNSS and 5G D2D measurements. Three integrated algorithms in different scenarios have been proposed: the first one is the integrated algorithm when the range measurements can be measured directly. The second one is the integrated algorithm with unknown time skew and offset of each mobile terminal. The third one is the integrated algorithm in GNSS-denied environment which is prevalent in urban and indoor applications. The simulation and experimental results show that our proposed integrated methodology outperforms the nonintegrated one.

Indoor positioning and navigation is an essential field of location-based service. Non-line of sight (NLOS) error restricts the accuracy of indoor positioning. Many researchers have studied the localization problem in indoor NLOS environments, but there is still a problem that NLOS error cannot be mitigated in unknown areas. To solve the above problems, this paper proposes a method of constructing virtual base stations in unknown areas (UA-VBS), and presents the corresponding positioning algorithm to calculate the location of the user equipment. Firstly, the base stations are selected and the initial positioning is carried out. Then, multiple virtual base stations are constructed according to the user equipment positions in the first three steps. The LOS base stations and virtual base stations participate in the TDOA calculation together, and calculate the base stations’ combination with the minimum residual and the corresponding positioning result. Finally, the pedestrian dead reckoning fusion weight is updated by the residual value, and the accurate positioning result in NLOS environment is obtained. Simulation and experimental results show that the proposed algorithm has high positioning accuracy and stability in NLOS environment.

We propose a novel positioning-communication integrated signal, which superposes the configurable positioning signal on the communication one to achieve a sub-meter range measurement accuracy. Different from other positioning schemes, there are multi positioning signals on different sub-carriers for different positioning users. The powers and bandwidths of these positioning signals are controllable, which reduces the near-far effect, and improves the range measurement accuracy. Other major contributions are: We analyze the interference of the positioning signal to the communication one; We give the lower-bound and measurement accuracy of the range estimation in both flat and fading channels, and derive their simple expressions. The results show the interaction between the communication and positioning signals is limited, and it is feasible to use the proposed signal for high accuracy positioning.

The fifth generation (5G) cellular communication system is designed to support Time Difference of Arrival (TDOA), Round-Trip Time (RTT), and Direction of Arrival (DOA) measurements for indoor positioning. To mitigate the positioning error caused by non-line-of-sight (NLOS), existing base station selection methods identify channel conditions and only use line-of-sight (LOS) signals for positioning. However, different selected base station combination would lead to a different geometric dilution of precision (GDOP), base station selection based only on channel condition is not fully applicable for the hybrid positioning. This paper derives the GDOP for the hybrid TDOA, RTT, and DOA positioning, and proposes a GDOP-assisted base station selection method, which is based on both channel conditions and GDOP value changes. The simulation shows that using the proposed base station selection method could lead to higher positioning accuracy than base station selection based only on channel condition. In the simulation, in the side region of the scenario, where the change of selected base station combination causes a notable increment in GDOP value, the positioning accuracy improvement caused by the proposed method is greater than that in the center region.

This paper presents a feasibility study of a novel multiple access technique called Multi-Scale Non-Orthogonal Multiple Access (MS-NOMA) for the next generation communication-positioning integration system. Different from the traditional positioning signals which are mostly Time Division Multiple Access with communication signals and are broadcast to all users, MS-NOMA supports continuous positioning waveform and flexible configurations for different positioning users to obtain higher ranging accuracy, lower positioning latency, less resource consumption and better signal coverage. Our major contributions are: Firstly, we present the MS-NOMA waveform and evaluate its performances by theoretical and simulation analyses. The results show it is feasible to use the MS-NOMA waveform to achieve high positioning accuracy and low Bit Error Rate with little resource consumption simultaneously. Secondly, to achieve optimal positioning accuracy and signal coverage, we model the power allocation problem for MS-NOMA as a convex optimization problem satisfying the Quality of Services requirement and other constraints. Then, we propose a novel Communication and Positioning Performances constrained Positioning Power Allocation (CP4A) algorithm which allocates the power of all P-Users iteratively. The theoretical and numerical results show our proposed MS-NOMA waveform with CP4A algorithm has great improvements of ranging/positioning accuracy than traditional Positioning Reference Signal in cellular network.

Localization plays a key role in Internet of Things. This paper proposes a novel intelligent cooperative multisensor localization method called the edge cloud cooperative localization (ECCL) which has the range and angle observations from the neighbor nodes along with the location observations from an absolute coordinate localization system like global positioning system. The edge cloud structure is proposed which employs several distributed Kalman filters in sensor nodes edge and a centralized cooperative fusion unit in the cloud. For a robust fusion, a cooperative redundancy validation method is proposed to detect the outliers. The proposed ECCL scheme has the advantages of both the distributed and centralized localization, which satisfies the needs of high reliability and high accuracy, especially when sensor nodes have limited computational resources. The simulation and experimental results show that our proposed ECCL algorithm outperforms the other schemes both in outlier detection and localization accuracy.