Towards Environmental RF-EMF Assessment of mmWave High-Node Density Complex Heterogeneous Environments

The densification of multiple wireless communication systems that coexist nowadays, as well as the 5G new generation cellular systems advent towards the millimeter wave (mmWave) frequency range, give rise to complex context-aware scenarios with high-node density heterogeneous networks. In this work, a radiofrequency electromagnetic field (RF-EMF) exposure assessment from an empirical and modeling approach for a large, complex indoor setting with high node density and traffic is presented. For that purpose, an intensive and comprehensive in-depth RF-EMF E-field characterization study is provided in a public library study case, considering dense personal mobile communications (5G FR2 @28 GHz) and wireless 802.11ay (@60 GHz) data access services on the mmWave frequency range. By means of an enhanced in-house deterministic 3D ray launching (3D-RL) simulation tool for RF-EMF exposure assessment, different complex heterogenous scenarios of high complexity are assessed in realistic operation conditions, considering different user distributions and densities. The use of directive antennas and MIMO beamforming techniques, as well as all the corresponding features in terms of radio wave propagation, such as the body shielding effect, dispersive material properties of obstacles, the impact of the distribution of scatterers and the associated electromagnetic propagation phenomena, are considered for simulation. Discussion regarding the contribution and impact of the coexistence of multiple heterogeneous networks and services is presented, verifying compliance with the current established international regulation limits with exposure levels far below the aforementioned limits. Finally, the proposed simulation technique is validated with a complete empirical campaign of measurements, showing good agreement. In consequence, the obtained datasets and simulation estimations, along with the proposed RF-EMF simulation tool, could be a reference approach for the design, deployment and exposure assessment of the current and future wireless communication technologies on the mmWave spectrum, where massive high-node density heterogeneous networks are expected.

Wireless Sensor Network Node Localization Algorithm Based on PSO-MA

Aiming at the large error and low accuracy of wireless sensor node location, this paper proposes a node location method based on the fusion of Particle Swarm Optimization and Monkey Algorithm (PSO-MA). Firstly, this article describes the node location model based on DV-HOP algorithm; secondly, this article uses PSO in node location, uses place Laplace distribution for population initialization, improves population diversity, and optimizes particle weights to avoid algorithm falling into local optimality. In this paper, dynamic guidance factors are used to update individual positions to improve individual optimization capabilities, and Monkey Algorithm is used to select individuals to improve the quality of optimal solutions. In the simulation experiment, the algorithm PSO and MA of this paper are compared to achieve better positioning results in the reference node ratio, node density and communication radius indicators.

Impact of Examined Lymph Node Count and Lymph Node Density on Overall Survival of Penile Cancer

BackgroundFew studies have explored the optimal examined lymph node count and lymph node density cutoff values that could be used to predict the survival of patients with penile cancer. We further clarify the prognostic value of lymph node density and examined lymph node count in penile cancer.MethodsThe Surveillance, Epidemiology, and End Results (SEER) database was explored to recruit penile cancer patients from 2010 to 2015. A retrospective analysis of penile cancer patients’ data from the First Affiliated Hospital of Anhui Medical University was performed for verification (2006–2016). The cutoff values of examined lymph node count and lymph node density were performed according to the ROC curve. Kaplan-Meier survival analysis was used to compare survival differences among different groups. Univariate and multivariate Cox proportional hazard regression analyses were used to determine the significant variables. On the basis of Cox proportional hazards regression model, a nomogram was established and validated by calibration plot diagrams and concordance index (C-index).ResultsA total of 528 patients in the Surveillance, Epidemiology, and End Results cohort and 156 patients in the Chinese cohort were included in this study. Using the ROC curve, we found that the recommended cutoff values of ELN and LND were 13 and 9.3%, respectively (P <0.001). Kaplan–Meier curves suggested the significant differences of overall survival among different examined lymph nodes and lymph node density. Multivariate analysis indicated ELN and LND were independent prognostic factor for OS of penile cancer patients. Nomogram showed the contribution of ELN and LND to predicting OS was large. The C-index at 3-, and 5-year were 0.744 for overall survival (95% CI 0.711–0.777).ConclusionsThe more lymph nodes examined, the lower the density of lymph nodes, and the higher the long-term survival rate of penile cancer. We recommended 13 examined lymph nodes and lymph node density >9.3% as the cutoff value for evaluating the prognosis of penile cancer patients.

PERFORMANCE EVALUATION OF DATA TRANSPORT OVER DIFFERENT-NODE DENSITY OF ZIGBEE SENSOR NETWORK – AN OPNET SIMULATION STUDY

In this paper, we analyze the performance of different node density of Wireless Sensor Network (WSN) operating under the IEEE Standard 802.15.4 in the beacon-enabled mode. The motivation for evaluating the beacon-enabled mode is due to its flexibility for WSN applications as compared to the non-beacon enabled mode. The analysis is based on an accurate OPNET simulation model which supports slotted Carrier Sense Multiple Access Mechanism with Collision Avoidance (CSMA/CA) mechanism and Guaranteed Time Slot (GTS). The performance of the slotted CSMA/CA sensor network is evaluated and analyzed for different network settings to understand the impact of the protocol attributes, including super-frame order (SO), beacon order (BO), data packet size and maximum back-off number. Through the simulation results, high SO provides better network throughput, otherwise results in lower average latency. We also found that the MAC overheads on small MAC Service Data Unit (MSDU) are more significant than the overheads on large MSDU. And the back-off mechanism results in longer delays when the network traffic is heavy.

Self-Pruning based Probabilistic Approach to Minimize Redundancy Overhead for Performance Improvement in MANET

The Broadcast storm problem causes severe interference, intense collision and channel contention, which greatly degrades the QoS performance metrics of the routing protocols. So, we suggest a neighbourhood coverage knowledge probabilistic broadcasting model (NCKPB) integrating with AODV protocol with knowledge on 2-hop neighbourhood coverage; a connectivity function to control a node’s forwarding probability of retransmission to alleviate significant overhead redundancy. Our objective is to minimize the broadcast RREQ overhead while ensuring fair retransmission bandwidth. We considered two more important measures called Saved Rebroadcast and Reachability. The outcomes of NCKPB, Fixed probability (FP) and Flooding (FL) routing schemes are examined under three major operating conditions, such as node density, mobility and traffic load. The NS-2 results demonstrate the efficacy of the proposed NCKPB model by illustrating its performance superiority over all key metrics such as redundancy overhead, end to end latency, throughput, reachability, saved rebroadcast and collision contrast to FP and FL.

A Novel Location Source Optimization Algorithm for Low Anchor Node Density Wireless Sensor Networks

Location information is one of the basic elements of the Internet of Things (IoT), which is also an important research direction in the application of wireless sensor networks (WSNs). Aiming at addressing the TOA positioning problem in the low anchor node density deployment environment, the traditional cooperative localization method will reduce the positioning accuracy due to excessive redundant information. In this regard, this paper proposes a location source optimization algorithm based on fuzzy comprehensive evaluation. First, each node calculates its own time-position distribute conditional posterior Cramer-Rao lower bound (DCPCRLB) and transfers it to neighbor nodes. Then collect the DCPCRLB, distance measurement, azimuth angle and other information from neighboring nodes to form a fuzzy evaluation factor set and determine the final preferred location source after fuzzy change. The simulation results show that the method proposed in this paper has better positioning accuracy about 33.9% with the compared method in low anchor node density scenarios when the computational complexity is comparable.