Mobile User Speed Research Articles

Handover management procedures for future generations mobile heterogeneous networks

Handover (HO) management in Heterogeneous Networks (HetNets) poses challenges arising from network densification and dynamic environmental behaviors. Existing HO decision algorithms struggle to efficiently utilize network resources and ensure a high-quality user experience amidst the complexity of HetNets and the burgeoning growth of mobile users. This paper introduces a robust and data-driven HO decision model designed to enhance HO performance in HetNets. Initially, a conventional HO decision algorithm is developed based on users' Reference Signal Received Power (RSRP) values in MATLAB. Various simulation cases explore different HO parameters to observe their impact on handover performance. To address these challenges, a data-driven HO decision model leveraging Long Short-Term Memory (LSTM), a deep learning technique, is proposed for the regression task. The LSTM model is trained and tested using obtained RSRP values, and the future RSRP values predicted by the model are employed to trigger HO decisions in the proposed algorithm. Results from the traditional HO decision algorithm are compared with those of the proposed machine learning-based approach across various simulation runs, considering average Signal-to-Interference-plus-Noise Ratio (SINR), RSRP, user throughput values, the number of HOs and the Radio Link Failure (RLF) ratio. Different user speeds are also considered to establish a relationship between HO frequency and mobile user speed. The proposed model achieved reducing the rate of radio link failure to levels that are deemed acceptable in order to ensure a continuous connection.

Map-Matching on Low Sampling Rate Trajectories through Frequent Pattern Mining

Map-matching, an important preprocessing task in many location-based services (LBS), projects each point of the global positioning system (GPS) within a trajectory dataset onto a digital map. The state-of-the-art map-matching algorithms typically employ Hidden Markov model (HMM) via shortest path computation. But the computation of the shortest path might not work well on low-sampling-rate trajectory data (e.g., one GPS point every 1–5 min), leading to low matching precision and high running time. To solve the problem, this paper firstly identifies frequent patterns (FPs) in historical trajectories to capture meaningful mobility behaviors, and then extracts mobile behavior criterion (MBC) of mobile users. Such a criterion generally represents the route choice of mobile users on road networks. Moreover, the temporal information within trajectory data was employed to estimate the speed of mobile users on road segments. The identified FPs, coupled with MBC and moving speed, help to improve the map-matching precision of low-sampling-rate trajectories. In addition, an FP-forest structure was proposed to index the identified FPs. The structure could greatly speed up the lookup of frequent paths for shorter running time. Furthermore, the FP-forest structure was pruned to reduce redundancy with smaller space cost. Finally, experiments were carried out on real-world datasets. The results confirm that our FP-matching method outperforms state-of-the-art in terms of effectiveness and efficiency.

Two-Tier Cellular Networks for Throughput Maximization of Static and Mobile Users

In small cell networks, high mobility of users results in frequent handoff and thus severely restricts the data rate for mobile users. To alleviate this problem, we propose to use heterogeneous, two-tier network structure where static users are served by both macro and micro base stations, whereas the mobile (i.e., moving) users are served only by macro base stations having larger cells; the idea is to prevent frequent data outage for mobile users due to handoff. We use the classical two-tier Poisson network model with different transmit powers (cf [1]), assume independent Poisson process of static users and doubly stochastic Poisson process of mobile users moving at a constant speed along infinite straight lines generated by a Poisson line process. Using stochastic geometry, we calculate the average downlink data rate of the typical static and mobile (i.e., moving) users, the latter accounted for handoff outage periods. We consider also the average throughput of these two types of users defined as their average data rates divided by the mean total number of users co-served by the same base station. We find that if the density of a homogeneous network and/or the speed of mobile users is high, it is advantageous to let the mobile users connect only to some optimal fraction of BSs to reduce the frequency of handoffs during which the connection is not assured. If a heterogeneous structure of the network is allowed, one can further jointly optimize the mean throughput of mobile and static users by appropriately tuning the powers of micro and macro base stations subject to some aggregate power constraint ensuring unchanged mean data rates of static users via the network equivalence property (see [2]).

Speed-Sensitive Handover Scheme over IEEE 802.16 Multi-Relay Networks

Abstract —Multi-Relay Networks should accommodate mobile users of various speeds. The cellular system should meet the minimum residency time requirements for handover calls while considering an efficient use of available channels. In this paper, we design speed-sensitive handover under dynamic hierarchical cellular systems, in which mobile users are classified according to the mean speed of mobile users and each class has its cellular layer. In order to meet the minimum residency time, the cell size of each cellular layer is dynamically determined depending on the distributions of mean speeds of mobile users. Since the speed-dependent non-preferred cell can provide a secondary resource, overflow and take-back schemes are adopted in the system. We develop analytical models to study the performance of the proposed system, and show that the optimal cell size improves the blocking probability. Keywords —Multi-Relay Networks, Handover 1. I NTRODUCTION The existing IEEE 802.16 is a series of Wireless Broadband standards known as WiMAX as an important technology for providing high-speed Internet access to home and business sub-scribers in a wide area cellular network[1]. Handover is a key factor for the quality of wireless communication services. Due to the geographical problem, significant data loss occurrs, the coverage region for high data rates is decreased, and even dead spot areas in the coverage region occurr. IEEE 802.16j adopts multihop or relay technologies in order to eliminate dead spot areas and extend the coverage region. In IEEE 802.16j networks, the Relay Stations (RSs) relay sig-naling and data messages between the Multihop Relay BS (MR-BS) and the Mobile Station (MS)[2, 3]. Therefore, handover issues for the RS on IEEE 802.16j have been carried out[4]. The increasing demands for mobile communications are proceeding with a strong tendency toward increasing need for high traffic capacity and mobility in the access links within the wire-less links[5, 6]. Since the micro-cell of the micro-cellular systems makes an efficient use of available channels by using low-power transmitters to allow channel reuse at much smaller dis-tances, the micro-cellular systems with an extremely small cell radius can meet the traffic de-mand[7, 8]. However, the micro-cell increases the number of cell boundary crossings for high-mobility users, and the increasing handover rates of ongoing calls may cause an excessive proc-essing load in the network. Furthermore, the handover calls of fast-moving users cannot meet

Cell Stay Time Analysis under Random Way Point Mobility Model in WLAN

This letter presents an analytical framework of the cell stay time (CST) in wireless LAN environment. CST is an important parameter that can be used to estimate how long a mobile user will stay in a particular cell and how many cells he will probably visit during his call holding time. CST can be also used to make predictive advanced reservations. A probability density function (p.d.f.) of the CST is obtained and an analytical expression of its main parameters such as the average and standard deviation values is outlined as a function of the average mobile user speed and cell radius

A Novel Adaptive Channel Estimation Scheme for DS-CDMA

This paper proposes an adaptive channel estimation scheme, which uses different moving average length and pilot gain for different mobile environments. It is based on MSE method and extensive simulations under various environments for WCDMA physical layer. The scheme applies a computationally efficient and easily implemented pilot filter on WCDMA forward channel. For different mobile channel environments, the optimal combination of moving average length and pilot gain for low SNR is achieved. The simulation results illustrate that the adaptive scheme can achieve much lower BER compared with two other adaptive schemes, especially when the speed of mobile user is high. And the BER performance of the proposed scheme is insensible to the mobile speed.