As a key infrastructure of Industry 4.0, Industrial Internet-of-Things (IIoT) promises the opportunity to build powerful industrial environments by leveraging the growing ubiquity of wired and wireless communication technologies. Designing a data delivery scheme in the future IIoT networks is undoubtedly a challenging task, as it should satisfy several conflicting requirements: massive-scale, data-intensive, and mission-critical, the requirements of which have motivated the desired need for feasible IIoT network architecture. In particular, the traffic characteristics of certain IIoT applications feature small-data patterns especially in typical automation control scenarios such as robot control on the downlink. In order to reduce the huge overhead associated with each individual unicast transmission of the small-data message, we propose a novel “multipoint-to-multipoint” and/or “point-to-multipoint with different contents” communication paradigm-Uni-Multi-Unicast (UMUcast), which is based-on traditional 4G technologies such as evolved Multimedia Broadcast Multicast Service (eMBMS) and Group Communication System Enablers (GCSE), and novel 5G technologies such as Multi-Access Edge Computing (MEC). For the downlink, the UMUcast transmitter can jointly encode multiple-sources' small-data messages into a single chunk at MEC equipment in conjoint with a gNB, where chunk can be one-off transmission to multiple receivers simultaneously through an eMBMS frame, whereas the chunk is decoded into multiple small-data by each individual IIoT devices separately and respectively. The simulation results show that UMUcast has remarkable improvements over conventional point-to-point unicasting in handling multi-source, multi-destination, and massive small-data delivery with characteristics of low-overhead, high-throughput, and ultra-low-latency for future 5G-based IIoT networks.

For ultra wideband communications, interferences from existing communication systems are unavoidable. In this paper, the effect of interference on impulse radio is analyzed and an interference cancellation scheme based on template design for software defined impulse radio is proposed. Simulation results show that the scheme can suppress the interference effectively. The scheme is applicable to both wideband and narrowband interference cancellation for software defined impulse radio.

For ultra-wideband positioning using impulse radio, intersymbol interference (ISI) is unavoidable, which affects the positioning accuracy. In this paper, a novel ISI cancellation scheme based on wavelet transformation for impulse positioning is proposed. Analog-to-digital conversion of the ultra-wideband signal is not needed, and knowledge of the channel is not required. The desired signal pulse can be distinguished from the interference pulse and precisely located. Instead of using the traditional received pulse, wavelet transformation is applied to generate a new spike signal for detection. A detailed theoretical analysis is presented and closed-form expressions are derived. Simulation results show that the proposed positioning scheme can cancel ISI effectively and achieve significantly lower average positioning error than the original TDOA system without ISI cancellation.

Visible light positioning has become a new research hotspot in recent years. In this study, a new Gaussian model of hybrid noise and multipath reflection is established for noise interference in line‐of‐sight (LOS) communication and multipath reflection in non‐LOS (NLOS) communication. First, the likelihood function of the ranging error is established according to the Gaussian hybrid model, and the analytical expression of Cramer–Rao lower bound is derived. Second, the novel adaptive parameter particle swarm optimisation (AP‐PSO) algorithm is proposed to calculate the three‐dimensional (3D) coordinates of the target. In order to avoid falling into the local optimal solution, a novel particle adaptive mutation algorithm, namely AP‐PSO‐M algorithm is also proposed. Simulation results show that if the NLOS propagation probability is 0.3 and the swarm size is 20, compared with Newton–Raphson (NR), particle swarm optimisation (PSO), dissipative PSO (DPSO) and simulated annealing PSO (SA‐PSO) algorithms, the average positioning error based on AP‐PSO‐M algorithm can be reduced by 45.43, 38.98, 25.37 and 26.42%, respectively. If similar positioning accuracy is obtained, compared with PSO, DPSO and SA‐PSO algorithms, the average calculation time required by the AP‐PSO‐M algorithm can be reduced by 48.16, 30.24 and 26.14%, respectively.

WiFi networks are playing an increasingly important role in the current networks towards the future 5G heterogeneous networks. The pertinence and effectiveness of WiFi network planning and construction, however, is demanding. To solve this problem, a novel positioning system for the potential WiFi hotspots is presented in this paper. The system can analyze the scale of the WiFi users for each site and then locate the potential WiFi hotspots accurately through detecting WiFi network card signals without contact. Accordingly, the WiFi network planning, especially software defined WiFi network planning can be refined and optimized.

A preprocessor for ultra-wideband (UWB) communications using impulse radio is proposed. The received UWB signal is divided into subband signals, which can be individually processed and recombined before demodulation of the signal. Perfect reconstruction of the pulses via analog subband processing is achieved. The division of subbands is flexible and the number depends on the number of frequency bands that requires processing. Only the subbands that require processing need to be digitized. The application of the preprocessor to interference cancellation is also demonstrated.