This study considers zone‐based registration (ZBR), which is adopted by most mobile cellular networks. In ZBR, a user equipment (UE) registers its location area (or zone) in a network database (DB) whenever it enters a new zone. Even though ZBR is implemented in most networks for a UE to keep only one zone (1ZR), it is also possible for a UE to keep multiple zones. Therefore, a ZBR with two zones (2ZR) is investigated, and some mathematical models for 2ZR are presented. With respect to ZBR with three zones (3ZR), several studies have been reported, but these employed computer simulations owing to the complexity of the cases, and there have been no reports on a mathematical 3ZR model to analyze its performance. In this study, we propose a new mathematical model for 3ZR for the first time, and analyze the performance of 3ZR using this model. The numerical results for various scenarios show that, as the UE frequently enters zones, the proposed 3ZR model outperforms 1ZR and 2ZR. Our results help determine the optimal number of zones that a UE keeps, and minimize the signaling cost for radio channels in mobile cellular networks.

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The location of user equipment (UE) should always be maintained in order to connect any incoming calls within a mobile network. While several methods of location registration have been proposed, most mobile networks have adopted zone-based registration due to its superior performance. Even though recommendations from research on these zone-based systems state that multiple zones can be stored in a zone-based registration system, actual current mobile networks only employ a zone-based registration system that stores a single zone. Therefore, some studies have been conducted on zone-based registration using multiple zones. However, most of these studies consider only two zones. In this study, through the development of a semi-Markov process approach, we present a simple but accurate mathematical model for zone-based registration using three zones. In addition, our research results in zone-based registration systems where one, two and three zones are used to suggest the optimal management scheme for zone-based registration. Given that most mobile networks have already adopted some kind of zone-based registration, these results are able to directly enhance the performance of the actual mobile network in the near future with the minimum of effort required for implementation.

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In this study, we consider zone-based registration (ZBR) in mobile communication networks. In ZBR, when a mobile moves to a new zone, it registers its zone to the network database to keep the mobile’s current zone, and to connect an incoming call to the mobile when it is generated. A mobile can store one zone, or more than one zones. Among various types of ZBR, we focus on two-zone-based registration (TZR), which is known to have good performance. In TZR, a mobile can store two zones that it has recently registered, and does not register when it crosses either zone that it has already kept. In general, in TZR, a mobile registers its zone less often than in single-zone-based registration (SZR). However, TZR increases the paging cost, because the network may not know the exact zone where the mobile is. Mathematical modeling and performance analysis are performed to obtain the exact performance of SZR and TZR, by considering the busy-line effect and implicit registration effect of outgoing calls from a mobile. From numerical results for various circumstances, it is shown that TZR is superior to SZR in most cases.

It is well established that motor action/imagery provokes an event-related desynchronization (ERD) response at specific brain areas with specific frequency ranges, typically the sensory motor rhythm and beta bands. However, there are individual differences in both brain areas and frequency ranges which can be used to identify ERD. This often results in low classification accuracy of ERD, which makes it difficult to implement of BCI application such as the control of external devices and motor rehabilitation. To overcome this problem, an individually optimized solution may be desirable for enhancing the accuracy of detecting motor action/imagery with ERD rather than a global solution for all BCI users. This paper presents a method based on a genetic algorithm to find individually optimized brain areas and frequency ranges for ERD classification. To optimize these two components, we designed a chromosome consisting of 64-bit elements represented by a binary number and another 9-bit elements using 512 pre-defined frequency ranges (2^9). The average value of the significant level is set for the properties of the objective function for use in a t-test, (p < 0.01) depending on the random selection from a concurrent population. As a result, contralateral ERD responses in the spatial domain with individually optimized frequency ranges showed a significant difference between resting and motor action. The ERD responses for motor imagery, on the other hand, led to a bilateral pattern with a narrow frequency band compared to motor action. This study provides the possibility of selecting optimized electrode positions and frequency bands which can lead to high levels of ERD classification accuracy.

In this study, we consider zone-based registration (ZBR). In the ZBR, when a mobile station (MS) enters a new location area (LA), it registers its location. Among various types of ZBR, we focus on two zone-based registration with outgoing call (TZRC) that is an improved version of the two zone-based registration (TZR). In the TZR, an MS can store two LAs that it registers recently not to register when it crosses two LAs stored already. In general, TZR has better performance than single zone-based registration (SZR). However, since the TZR may increase paging cost, TZRC was proposed to decrease paging cost. Mathematical analysis is performed to obtain the exact performance of SZR, TZR, TZRC. From the numerical results for various circumstances, it is shown that TZRC outperforms TZR and SZR in most cases.