Michal Vondra

Optimization of SINR-based Neighbor Cell List for networks with small cells

In this paper, we propose an optimization of Neighbor Cell List (NCL) management algorithm. The goal is to minimize a number of scanned cells for handover purposes while a call drop rate is not increased. To that end, the NCL is dynamically optimized according to the SINR observed by a User Equipment (UE) from its serving cell. If a UE is in the cell center, only the serving cell is scanned. Contrary, if the UE moves closer to the cell edge, also other cells are inserted to the list of scanned cells. The cells are included in the list based on the probability of handover to these cells. The optimization presented in this paper consists in derivation of the optimal value of the parameters that describes a relation between a handover probability threshold for scanning and SINR measured by the UE. First, we provide analytical analysis of the problem and then we confirm the derived optimal values by means of simulations. The results show the proposed optimization of the NCL management is able to reduce the number of scanned cells significantly while the call drops due to NCL can be eliminated.

Self-optimizing neighbor cell list with dynamic threshold for handover purposes in networks with small cells

To select a proper target cell for handover of mobile users, signal level of cells in users neighborhood is scanned by a user equipment UE. Cells assumed to be scanned are included in the so-called neighbor cell list NCL. Conventionally, the NCL is managed according to the probability of handover of users to a target cell with fixed threshold. Nevertheless, the size of NCL could be significant if this approach is applied to networks with small cells. In this paper, we exploit knowledge of handover probability among cells derived from a handover history to reduce the amount of scanned cells. We introduce dynamic adaptation of the amount of cells to be scanned according to the quality of signal of a serving cell, measured by the UE. We also investigate impact of relation between the handover probability and the signal level to maximize efficiency of this approach. Further, the NCL management considering either summarized handover history of all UE or individual history of each user is compared in our evaluations. As the results show, both methods notably reduce the amount of cells to be scanned, while call drop rate and outage of the users are still negligible as in the conventional way. Copyright

Self-configured Neighbor Cell List of macro cells in network with Small Cells

To ensure faultless handover procedure of mobile users, each cell in the network must establish a Neighbor Cell List (NCL). The NCL contains adjacent cells to which handover can be performed. A problem related to the handover from a Macro/Micro cell (MeNB) appears with the rising density of cells with the limited coverage, so-called Small Cells (SCeNBs). By using method of the NCL creation described in standards or literature, the number of neighboring cells suitable for handover from the MeNB can be extensive. Therefore, we propose an algorithm for automatic creation of the NCL with reduced number of included cells. The proposed algorithm exploits knowledge of the last visited cell in combination with the statistical information on performed handovers in the past to determine the possibility of transition to the neighboring cells. As the results show, the proposed algorithm significantly reduces the number of cells in the NCL while the probability of missing handover target cell in the NCL is kept negligible.

Connection cost based handover decision for offloading macrocells by femtocells

Femtocells can offload macrocells and reduce a cost of transmitted data in wireless networks. If a connection via the femtocell is of a lower cost than via the macrocell, a time spent by users connected to the femtocells should be maximized. This leads to a reduction of the overall cost of users connection. Besides, a prolongation of the time spent by users in the femtocells reduces load of the macrocells. Therefore, an extension of handover is presented in this paper. The extension consists in consideration of the connection cost together with users requirements on a service quality. To that end, a conventional handover decision is modified to achieve higher efficiency in prolongation of the time spent by the users in the femtocells. As the results show, the user who does not require high quality of service spent more time connected to the femtocells and thus the macrocell can be offloaded.

Vehicular Network-Aware Route Selection Considering Communication Requirements of Users for ITS

Increasing demands of mobile users on communication and new types of devices, such as sensors, machines, and vehicles, impose high load on cellular networks. Since requirements are expected to rise in a near future, new ways for cellular network offloading are needed. A promising solution for vehicles and vehicular users is to offload data to vehicular networks. To maximize offloading of the cellular networks, the vehicles can be navigated through areas characterized with more available communication capacity. Hence, we propose a novel scalable traveling route selection algorithm determining the route according to a traveling time and available throughput of both cellular and vehicular networks. While the maximum tolerated traveling time is defined by the vehicular users, an estimation of available throughput is based on a vehicular movement prediction. The proposed route selection algorithm is able to offload cellular network by up to 17% and time spent without required quality of connection can be reduced by 65%. At the same time, the traveling time is prolonged only negligibly in comparison with state-of-the-art algorithms.

Assessment of Speech Quality in VoIP

In VoIP (Voice over Internet Protocol), the voice is transmitted over the IP networks in the form of packets. This way of voice transmission is highly cost effective since the communication circuit need not to be permanently dedicated for one connection; however, the communication band is shared by several connections. On the other hand, the utilization of IP networks causes some drawbacks that can result to the drop of the Quality of Service (QoS). The QoS is defined by ITU-T E.800 recommendation (ITU-T E.800, 1994) as a group of characteristics of a telecommunication service which are related to the ability to satisfy assumed requirements of end users. The overall QoS of the telecommunication chain (denoted as end-to-end QoS) depends on contributions of all individual parts of the telecommunication chain including users, end devices, access networks, and core network. Each part of the chain can introduce some effects which lead to the degradation of overall speech quality. Lower speech quality causes user’s dissatisfaction and consequently shorter duration of calls (Holub et al., 2004) which reduces profit of telecommunication operators. Therefore, both sides (users as well as operators or providers) are discontented. The end device decreases speech quality by coding and/or compression of the speech signal. The speech quality can be also influenced by a distortion of the speech by its processing in the end device e.g. in the manner of filtering. It can lead to the saturation of the speech, insertion of a noise, etc. The processed speech is carried in packets via routers in the networks. Individual packets are routed to the destination as conventional data packets. Therefore, the packets can be delayed or lost. According to ITU-T G.114 recommendation (ITU-T G.114, 2003), the delay of speech should be lower than 150 ms to ensure high quality of the speech. Each packet is routed independently; therefore the delay of packets can vary in time. The variation of packet delay is usually denoted jitter. The impact of all above mentioned effects on the speech quality can be evaluated either by subjective or objective tests. The first group, subjective tests, uses real assessments of the speeches by users. Therefore it cannot be performed in real-time. The second set of tests, objective tests, tries to estimate the speech quality by speech processing and evaluation. The rest of chapter is organized as follows. The next section gives an overview on the related work in the field of VoIP speech quality. The third one describes basic principles of the speech quality assessment. The speech processing for all performed tests are described in section four. Section five presents the results of realized assessments of the speech quality. Last section sums up the chapter and provides major conclusions.