This paper proposes recurrent neural networks (RNNs) for WiFi fingerprinting indoor localization. Instead of locating a mobile user’s position one at a time as in the cases of conventional algorithms, our RNN solution aims at trajectory positioning and takes into account the correlation among the received signal strength indicator (RSSI) measurements in a trajectory. To enhance the accuracy among the temporal fluctuations of RSSI, a weighted average filter is proposed for both input RSSI data and sequential output locations. The results using different types of RNN including vanilla RNN, long short-term memory (LSTM), gated recurrent unit (GRU), bidirectional RNN (BiRNN), bidirectional LSTM (BiLSTM) and bidirectional GRU (BiGRU) are presented. On-site experiments demonstrate that the proposed structure achieves an average localization error of 0.75 m with 80% of the errors under one meter, which outperforms KNN algorithms and probabilistic algorithms by approximately 30% under the same test environment.

Research and development on the next generation wireless systems, namely 5G, has experienced explosive growth in recent years. In the physical layer, the massive multiple-input-multiple output (MIMO) technique and the use of high GHz frequency bands are two promising trends for adoption. Millimeter-wave (mmWave) bands, such as 28, 38, 64, and 71 GHz, which were previously considered not suitable for commercial cellular networks, will play an important role in 5G. Currently, most 5G research deals with the algorithms and implementations of modulation and coding schemes, new spatial signal processing technologies, new spectrum opportunities, channel modeling, 5G proof of concept systems, and other system-level enabling technologies. In this paper, we first investigate the contemporary wireless user equipment (UE) hardware design, and unveil the critical 5G UE hardware design constraints on circuits and systems. On top of the said investigation and design tradeoff analysis, a new, highly reconfigurable system architecture for 5G cellular user equipment, namely distributed phased arrays based MIMO (DPA-MIMO) is proposed. Finally, the link budget calculation and data throughput numerical results are presented for the evaluation of the proposed architecture.

This paper proposes a soft range limited K nearest neighbours (SRL-KNN) localization fingerprinting algorithm. The conventional KNN determines the neighbours of a user by calculating and ranking the fingerprint distance measured at the unknown user location and the reference locations in the database. Different from that method, SRL-KNN scales the fingerprint distance by a range factor related to the physical distance between the user’s previous position and the reference location in the database to reduce the spatial ambiguity in localization. Although utilizing the prior locations, SRL-KNN does not require knowledge of the exact moving speed and direction of the user. Moreover, to take into account of the temporal fluctuations of the received signal strength indicator (RSSI), RSSI histogram is incorporated into the distance calculation. Actual on-site experiments demonstrate that the new algorithm achieves an average localization error of 0:66 m with 80% of the errors under 0:89 m, which outperforms conventional KNN algorithms by 45% under the same test environment.

The rapid advancement of Internet of Things (IoT) and 5G and beyond technologies are transforming the marine industry and research. Our understanding of the vast sea that covers 71% of the Earth’s surface is being enhanced by the various ocean sensor networks equipped with effective communications technologies. In this paper, we begin with a review of the research and development status-quo of maritime IoT (MIoT) enabled by multiple wireless communication technologies. Then we study the impact of sea waves to radio propagation and the communications link quality. Due to the severe attenuation of sea water to radio frequency electromagnetic waves propagation, large ocean waves can easily block the communications link between a buoy sensor and a cell tower near shore. This paper for the first time uses the ocean wave modeling of coastal and oceanic waters to examine the line of sight communications condition. Real wave measurement data parameters are applied in the numerical evaluation of the developed model. Finally, the critical antenna design taking into account the wave impact is numerically studied with implementation solutions proposed, and the system hardware and protocol aspects are discussed.

Unmanned aerial vehicles (UAVs) for wireless communications have rapidly grown into a research hotspot as the mass production of high-performance, low-cost, intelligent UAVs become practical. In the meantime, the fifth generation (5G) wireless communication and internet of things (IoT) technologies are being standardized and planned for global deployment. During this process, UAVs are becoming an important part of 5G and IoT, and expected to play a crucial role in enabling more functional diversity for wireless communications. In this paper, we first present a summary of mainstream UAVs and their use in wireless communications. Then, we propose a hierarchical architecture of UAVs with multi-layer and distributed features to facilitate the integration of different UAVs into the next-generation wireless communication networks. Finally, we unveil the design trade-offs with the consideration of power transfer, wireless communication and aerodynamic principles. In particular, empirical models and published measurement data are used to analyze power transfer efficiency, and meteorological impacts on UAVs enabled next-generation wireless communications.

The fifth generation (5G) research and development has been fueled by many new breakthroughs in various areas. The recent progress in carrier aggregation (CA), licensed assisted access (LAA), massive MIMO (MaMi), beamforming techniques, cooperative spectrum sensing (CSS), compressive sensing (CS), machine learning, etc., has provided inspiring and promising approaches to address 5G and beyond challenges. However, at the user equipment (UE) end, limited design budget and hardware resources bring along a series of challenging implementation issues when delivering multi-standard and multi-functional wireless communications. In this paper, we first review recent advances in technical standards and critical enabling techniques, accompanied with several case studies of product developments. After the classification of typical 5G application and deployment scenarios, we propose and analyze a novel hardware reuse and multiplexing solution to facilitate cost-effective and energy-efficient UE design, followed by an investigation of state-of-the-art hardware development from the systems and circuits standpoint. Moreover, wireless UE hardware solutions, UE proof-of-concept (PoC) implementation and field test are proposed and discussed. Finally, the new trends of UE design and terahertz technologies for 5G and beyond applications are investigated and envisioned.