While the telecommunications landscape is undergoing a significant transformation with the advent of 5G technology, the continued importance of Long Term Evolution (LTE) is also emphasized due to its widespread adoption and reliability. In this circumstance, mobile network operators must continue to uphold their obligation to ensure Quality of Service (QoS) for LTE users. The actual LTE Base Station (BS) signal measurement data can be effectively exploited in the evaluation of user-perceived QoS. In this work, we utilize Downlink Control Information (DCI) data obtained from LTE BSs through a recently developed platform. The DCI data contains downlink information experienced by all users within the cell, but to assess user-perceived performance, it is necessary to distinguish each active session. We call the grouping of DCI messages that correspond to a continuous service in one active session ‘bundling’. While previous bundling methods have mostly focused on the time gap between DCI messages, we extract features based on the LTE standard that DCI can exhibit at the start of an active session. By combining these features with a probabilistic approach , we establish criteria for implementing bundling. In addition, through the proposed bundling methodology, we analyze the active session duration, number of active sessions, cell edge user performance, etc. The results validate the effectiveness of our bundling approach.

This poster presents a method to cluster LTE base stations based on their locations to diagnose the usage of fragmented spectrum resources. The growing demand for low-frequency spectrum in next-generation networks highlights the need to evaluate the adequacy of LTE spectrum utilization. We analyze resource block usage data from a congested area in Korea, provided monthly by mobile network operators. Density-based clustering and Voronoi diagrams are applied to divide regions and assess total spectrum utilization. Probabilistic modeling using the areas of the regions provides an indicator of spectrum utilization.

The benefits of dedicated spectrum for Private 5G(P5G) networks are driving demand for it. Implementing dedicated spectrum requires accurate estimates of system capacity for the envisioned deployment scenario. Industrial automation applications have stringent service requirements for latency and availability. In a time division duplex system, the satisfaction of these requirements should be considered based on the link configuration. We present a novel analytical framework based on a non-stationary queuing model that carefully accounts for these features in the calculation of appropriate system capacity for P5G. We provide example calculations for some device deployment scenarios.

Efficient sharing of the network spectrum is required to meet the exponentially growing demand of wireless communications, and the role of the MAC protocols has been becoming more important. In this regard, a novel MAC protocol called the Renewal Access Protocol (RAP) was recently proposed. It was shown that the RAP achieves optimal throughput, high short-term fairness, and near-optimal delay performances when the number of nodes in the network is known to all nodes. However, it is not easy for a node to know the number of nodes in the network and the number of nodes is time varying. So we propose an adaptive version of the RAP called the Adaptive Renewal Access Protocol (A-RAP) in this paper. A node equipped with the A-RAP estimates the number of nodes utilizing two dimensional Backoff Selection State (BSS), the Estimated Number of Nodes (ENN) and phase, based on its transmission results. For an efficient design of the A-RAP, we analyze the performance of the A-RAP and carefully determine two key parameters, the adjustment probabilities and the numbers of phases. Numerical and simulation results are provided to verify that the proposed A-RAP achieves good throughput and short-term fairness as the RAP. The results also show that the A-RAP achieves better short-term fairness than other MAC protocols proposed in the open literature.

As a promising solution for handling super dense wireless networks, wireless local area networks (WLANs) have been intensively considered due to their wide availability. However, the contention-based MAC protocol in WLANs should be modified because of its inefficiency. To this end, we consider a recently proposed novel MAC protocol called the renewal access protocol (RAP). With the RAP, we analyze two strategies for resolving collisions efficiently and achieving optimal throughput performance in super dense WLANs: strategies without and with grouping. First, we analyze the asymptotic behavior of the RAP itself (i.e., without grouping) as the number of terminals goes to infinity. We show that the RAP can achieve optimal throughput even in super dense WLANs and the relevant optimal access probability can be derived in a closed form. Second, we propose a grouping strategy in the RAP called the grouped RAP (G-RAP). While a grouping strategy in the IEEE 802.11ah standard is based on time division, our G-RAP is based on transmission attempts. So the G-RAP does not waste channel resources. We show that the G-RAP achieves the optimal network throughput for any group structure if terminals use the optimal access probability that we derive. Our analytical results are validated by simulation.

We consider a simple MAC protocol, called the renewal access protocol (RAP), that adopts all of the legacy 802.11 standard but the backoff stage feature. To meet two objectives in the design of the RAP—optimal throughput and high short-term fairness—we develop a mathematical model of the RAP and rigorously analyze the performance of the RAP. First, we show that the throughput performance of the RAP depends only on the expectation of the selection distribution where the backoff counter is selected, provided that the number of terminals is fixed, which is in accordance with a well-known result. Second, with the help of renewal and reliability theories, we analyze the short-term fairness of the RAP. We also show that if the RAP has a selection distribution of the New Better than Used in Expectation (NBUE) type, the RAP can guarantee high short-term fairness. Third, we construct a special binomial distribution that is obviously of the NBUE type that can achieve high short-term fairness as well as optimal throughput when used as the selection distribution of the RAP. Furthermore, by the Poisson approximation for binomial distributions, we propose to use in practice a Poisson distribution corresponding to the special binomial distribution. Numerical and simulation results are provided to validate our analysis.