This paper presents new analytical results for evaluating the ALOHA-like multi-class random access wireless network’s performance. The proposed model is motivated by the growth of low-power wireless networks that employ random access protocols. In particular, we compare our analytical formulation with system-level simulations of Long Range (LoRa) technology. We show that the proposed formulation provides an accurate approximation of LoRaWAN performance capturing its main trade-offs. The main contributions are (i) an extensive analysis of the impact of different LoRa spreading factors (SFs) allocation strategies, including area intersection among SFs, which is little explored in the literature and represents the optimal approach under some conditions; and (ii) the optimal proportion of users that maximizes the network throughput for each class and for each allocation strategy considered in the paper.

Telecommunication service providers have to guarantee acceptable speech quality during a phone call to avoid a negative impact on the users’ quality of experience. Currently, there are different speech quality assessment methods. ITU-T Recommendation G.107 describes the E-model algorithm, which is a computational model developed for network planning purposes focused on narrowband (NB) networks. Later, ITU-T Recommendations G.107.1 and G.107.2 were developed for wideband (WB) and fullband (FB) networks. These algorithms use different impairment factors, each one related to different speech communication steps. However, the NB, WB, and FB E-model algorithms do not consider wireless techniques used in these networks, such as Multiple-Input-Multiple-Output (MIMO) systems, which are used to improve the communication system robustness in the presence of different types of wireless channel degradation. In this context, the main objective of this study is to propose a general methodology to incorporate wireless network parameters into the NB and WB E-model algorithms. To accomplish this goal, MIMO and wireless channel parameters are incorporated into the E-model algorithms, specifically into the $I_{e,eff}$ and $I_{e,eff,WB}$ impairment factors. For performance validation, subjective tests were carried out, and the proposed methodology reached a Pearson correlation coefficient (PCC) and a root mean square error (RMSE) of 0.9732 and 0.2351, respectively. It is noteworthy that our proposed methodology does not affect the rest of the E-model input parameters, and it intends to be useful for wireless network planning in speech communication services.

This paper investigates the achievable sum rate and the outage capacity of generalized frequency division multiplexing systems (GFDMs) with minimum mean-square error (MMSE) receivers over frequency-selective Rayleigh fading channels. To this end, a Gamma-based approximation approach for the probability density function of the signal-to-interference-plus-noise ratio is presented, based on which accurate analytical formulations for the achievable sum rate and outage capacity are proposed. The accuracy of our analysis is corroborated through Monte Carlo simulation assuming different GFDM parameters. Illustrative numerical results are depicted in order to reveal the impact of the key system parameters, such as the number of subcarriers, number of subsymbols, and roll-off factors, on the overall system performance.

This paper assesses the performance of a private LTE wireless network in an industrial automation setup. Our goal is to study the impact of communication latency in a robot arm position control application when the position feedback signal is transmitted via a commercial LTE wireless link. An Ethernet link scenario is considered as our benchmark. We show that even under very specific conditions (no network load, high signal power), the wireless link cannot achieve a satisfactory performance. The proposed demonstration provides a simple visualization of how LTE network latency disturbs the robot behavior, leading to undesired overshoots, oscillations and even stopping its movements. These results demonstrate that even a private LTE network is still incapable of providing the low latency required by industry automation applications, which shall be incorporated in the upcoming 5G wireless systems.

Narrowband interference (NBI) is a known problem in wireless communications. However, analyses found in the NBI literature often model the signal of interest as a generic transport channel with all subcarriers conveying information of the same kind, e.g. user plane data. By taking the analysis down to physical channels' level, this paper aims to obtain a deeper understanding of the impact exerted by NBI on both the user and control planes of Long Term Evolution (LTE) systems. First, field measurements are carried out to characterize the narrowband systems operating in the recently standardized LTE Band 31 (450-470 MHz). On the basis of these findings, requirements for NBI suppression in the LTE downlink are established. Some prominent time-frequency distributions (TFDs) are then evaluated via computer simulations with respect to their ability to fulfill such requirements. Among the TFDs considered, wavelets offer the best compromise in terms of complexity and signal distortion regardless the type of physical channel. For those cases where information about the NBI center frequencies is not available a priori, we propose a blind timedomain canceller based on the Wigner-Ville distribution.