LTE RSRP, RSRQ, RSSNR and local topography profile data for RF propagation planning and network optimization in an urban propagation environment

In the design of 5G cellular communication to guarantee quality signal reception at every point within a coverage area, fundamental knowledge of the channel propagation characteristics is vital. A correct knowledge of electromagnetic wave propagation is required for efficient radio network planning and optimization. Propagation data are used extensively in network planning, particularly for conducting feasibility studies. Hence, measurement of accurate propagation models that predict how the channel varies as people move about is crucial. However, these measured data are often not widely available for channel characterization and propagation model development. In this data article, the Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ) and Reference Signal Signal to Noise Ratio (RSSNR) at various points in space which is covered by a Long-Term Evolution (LTE) marco base station operating at 2100 MHz located in Hatfield, Hertfordshire, United Kingdom were measured. Further, local topography profile data of the study area were extracted from a digital elevation model (DEM) to account for the features of the propagation environment. Correlation matrix and descriptive statistics of the measured LTE data along different routes are analyzed. The RSRP, RSRQ and RSSNR variation with transmitter (Tx) – receiver (Rx) separation distance along the routes are presented. The probability distribution and the DEM of LTE data measurement are likewise presented. The data provided in this article will facilitate research advancement in wireless channel characterization that accounts for local topography features in an urban propagation environment. Moreover, the data sets provided in this article can be extended using simulation-based analysis to extract spatial and temporal channel model parameters in urban cellular environments in the development of 5G channel propagation models.Peer reviewedFinal Published versio

A semi-deterministic channel model for VANETs simulations

International audienceIn this paper we propose a semi-deterministic channel propagation model for VANETs (Vehicular Ad-hoc NETworks) called UM-CRT. It is based on CRT (Communication Ray Tracer) and SCME-UM (Spatial Channel Model Extended - Urban Micro) which are respectively a deterministic channel simulator and a statistical channel model. It uses a process which adjusts the SCME-UM model using relevant parameters extracted from CRT. In order to evaluate this new model, we incorporate it into the NS-2 network simulator. Our results show that UM-CRT is adapted to VANETs simulations as it approximates in a realistic manner channel propagation mechanisms while improving simulation time

ns-3 Implementation of the 3GPP MIMO Channel Model for Frequency Spectrum above 6 GHz

Communications at mmWave frequencies will be a key enabler of the next generation of cellular networks, due to the multi-Gbps rate that can be achieved. However, there are still several problems that must be solved before this technology can be widely adopted, primarily associated with the interplay between the variability of mmWave links and the complexity of mobile networks. An end-to-end network simulator represents a great tool to assess the performance of any proposed solution to meet the stringent 5G requirements. Given the criticality of channel propagation characteristics at higher frequencies, we present our implementation of the 3GPP channel model for the 6-100 GHz band for the ns-3 end-to-end 5G mmWave module, and detail its associated MIMO beamforming architecture

Feasibility Study of OFDM-MFSK Modulation Scheme for Smart Metering Technology

The Orthogonal Frequency Division Multiplexing based M-ary Frequency Shift Keying (OFDM-MFSK) is a noncoherent modulation scheme which merges MFSK with the OFDM waveform. It is designed to improve the receiver sensitivity in the hard environments where channel estimation is very difficult to perform. In this paper, the OFDM-MFSK is suggested for the smart metering technology and its performance is measured and compared with the ordinary OFDM-BPSK. Our results show that, depending on the MFSK size value (M), the Packet Error Rate (PER) has dramatically improved for OFDM-MFSK. Additionally, the adaptive OFDM-MFSK, which selects the best M value that gives the minimum PER and higher throughput for each Smart Meter (SM), has better coverage than OFDM-BPSK. Although its throughput and capacity are lower than OFDMBPSK, the connected SMs per sector are higher. Based on the smart metering technology requirements which imply the need for high coverage and low amount of data exchanged between the network and the SMs, The OFDM-MFSK can be efficiently used in this technology.Comment: 6 pages, 11 figures, ISGT Europe 201