Search

Wireless networks are facing various challenges that demand continuous and rapid improvement. Long-Term Evolution (LTE) is a preferred wireless technology because of its satisfactory performance. Owing to an exponential increase in demand and new potential applications, the core network of LTE, which is known as the Evolved Packet Core (EPC), is affected by a surge in signaling caused by a variety of control functions. The signaling overhead decreases the users’ Quality of Experience (QoE). The current study attempts to improve the intelligence of location management techniques. As an extension of our previous study , a Self-Organizing Network (SON) that enables dynamic reconfiguration of cell-to-TAL/MME is introduced. Both centralized and distributed pooling schemes are tested in terms of signaling overhead and user power consumption. A decomposition model that reduces the original formulated problem to two sub-problems is proposed, each of which is solved optimally. In addition, a smart cell-to-TAL selection scheme is proposed to prioritize potential cells that might be visited by a user equipment (UE). Our method is shown to outperform several state-of-the-art methods presented in the literature. Finally, a heuristic algorithm is presented to obtain a less complex solution than the optimal one. [ABSTRACT FROM AUTHOR]

Machine Type Communications (MTC) is one of the major drivers for the future growth of the Third Generation Partnership Project (3GPP) Long Term Evolution (LTE)/LTE-Advanced (LTE-A) standards. A primary challenge associated with MTC using LTE/LTE-A is to cater to varied requirements of the User Equipment (UE) like coverage enhancement, low complexity, low power consumption, etc. The current LTE/LTE-A standards incorporate the Discontinuous Reception (DRX) mechanism for reduced energy consumption where the UE wakes up periodically to check for a paging message from the base-station. On each wake-up occasion, the UE has to decode the paging information, which requires accurate timing resynchronization. In the case of the MTC UEs, especially when the devices are deployed in low coverage areas, the resynchronization consumes a significant amount of time which increases the ON time of the UE leading to higher energy consumption. In this paper, we introduce the Enhanced Primary Synchronization Signal (ePSS) within the LTE/LTE-A standardization framework and propose a novel DRX mechanism which uses our ePSS for faster resynchronization and reduced energy consumption. We demonstrate that our mechanisms are more energy efficient than the legacy DRX mechanism for the MTC UEs with coverage enhancement. [ABSTRACT FROM AUTHOR]

In Machine-to-Machine (M2M) communications, devices can automatically communicate with each other without any intervention by humans. However, LTE-A is primarily designed and optimized for Human-to-Human (H2H) communications. Even though LTE-A has defined Machine-Type Communications (MTC), several parts are still undefined or follow the existing H2H standards. Specifically, the existing paging mechanism in LTE-A will substantially increase the computational load and signaling overhead of the system when there are many M2M devices. Therefore, we propose an effective solution to mitigate this problem. Compared with the traditional paging mechanism defined in LTE-A, the proposed solution can save more energy for M2M devices, reduce signaling overhead and alleviate the network's load significantly. [ABSTRACT FROM AUTHOR]

Existing location management (LM) methods for macrocells in LTE-Advanced have tracking area list (TAL) granularity. Therefore, a user equipment (UE) triggers a location update (LU) whenever it leaves its current TAL, and it is searched through paging (PG) with TAL accuracy. However, these procedures are not well-suited for small cells (SCs). The reasons are twofold. First, dense deployments of SCs imply that paging has a low probability to be successful in the first attempt, increasing the signaling overhead in the core network (CN). Second, smaller coverage areas lead to a higher mobility among cells, increasing the signaling overhead in the CN due to LUs. In this work, two LM schemes with fine granularity are proposed. These schemes update UE's location to a local anchor (LA) in a SC or tracking area (TA) basis, respectively. By increasing the accuracy of UE's location, a significant reduction of signaling overhead in the CN due to PG is achieved. Moreover, LUs to the LA are performed through direct X2-interface links to avoid signaling overhead in the CN. A versatile mobility model is developed and closed-form expressions for UEs’ mobility metrics are found to validate the proposed schemes through variations of critical parameters such as TA/TAL configuration, UE's mobility patterns and cell residence times. [ABSTRACT FROM PUBLISHER]

Mobility management in Long Term Evolution (LTE) is different from that in the third generation mobile telecom networks. In LTE, the Mobility Management Entity (MME) is responsible for the mobility management function. The MME is connected to a large number of evolved Node Bs (cells) that are grouped into the Tracking Areas (TAs). The TAs are further grouped into TA Lists (TALs). When a User Equipment (UE) moves out of the current TAL, it reports its new location to the MME. If the LTE network attempts to connect to the UE, the MME asks the cells in the TAL to page the UE. In LTE paging, the MME may sequentially page a cell, the TA of the cell, and/or the TAL of the cell. This paper investigates the performance of LTE paging, and provides the guidelines for the best paging sequence of cells. [ABSTRACT FROM PUBLISHER]

The problem of searching for mobile users in cellular networks is addressed in this study. Previous studies addressing this issue have focused on the problem of searching for a single user. The underlying assumption for this approach is that some straightforward strategy of searching for multiple users can be easily derived from a single user search strategy. Unfortunately, this assumption is violated very often in practice, and a direct extension of an optimal single-user (OSU) search scheme to multiple users often fails due to the inherent correlation and dependence among the movements of the mobile users. As shown in this study, the problem of maximizing the expected rate of successful searches under delay and bandwidth constraints is NP-hard. When the potential locations of different users overlap, the derivation of an optimal concurrent search for many independent users from a set of OSU searches is NP-hard. Unfortunately, very often, the potential locations of different users overlap. In reality, a cellular network has to serve many competing search requests sharing a limited bandwidth. Since the problem of maximizing the expected rate of successful searches under delay and bandwidth constraints is NP-hard, this study proposes a heuristic algorithm that is optimal for most probable cases, and its worst case runtime complexity is O(n(log n + Clog C)), where n is the number of mobile users that must be found, and C is the number of their potential locations. The approximation ratio of the proposed search algorithm is less than 2. That is, the expected number of searches is always less than twice the number of searches expected from an optimal search algorithm. Even under the worst case condition, the proposed method can potentially increase the expected rate of successful searches by 100 percent in comparison to the existing search strategy currently used by cellular networks. Moreover, the proposed search strategy outperforms a greedy search strategy that considers only the users' location probabilities and ignores their deadline constraints. Under certain conditions, the expected rate of successful searches generated by the proposed method is twice the equivalent rate generated by the greedy search strategy. In addition, the proposed search strategy outperforms a heuristic algorithm that searches around the user last known location. [ABSTRACT FROM AUTHOR]

In this paper, we propose two information-theoretic techniques for efficiently trading off the location update and paging costs associated with mobility management in wireless cellular networks. Previous approaches always attempt to accurately convey a mobile's movement sequence and hence cannot reduce the signaling cost below the entropy bound. Our proposed techniques, however, exploit the rate distortion theory to arbitrarily reduce the update cost at the expense of an increase in the corresponding paging overhead. To this end, we describe two location tracking algorithms based on spatial quantization and temporal quantization, which first quantize the movement sequence into a smaller set of codewords and then report a compressed representation of the codeword sequence. Although the spatial quantization algorithm clusters individual cells into registration areas, the more powerful temporal quantization algorithm groups sets of consecutive movement patterns. The quantizers themselves are adaptive and periodically reconfigure to accommodate changes in the mobile's movement pattern. Simulation study with synthetic and real movement traces for both single-system and multisystem cellular networks demonstrate that the proposed algorithms can reduce the mobile's update frequency to 3-4 updates/day with reasonable paging cost, low computational complexity, storage overhead, and codebook updates. [ABSTRACT FROM AUTHOR]

In this paper, we present a simple pipeline paging (PP) scheme, in which multiple paging requests (PRs) can be served in a pipeline manner in different paging areas. We analytically model the blanket paging (BP) scheme, the sequential paging (SP) scheme, and the PP scheme so that discovery rate, total delay, paging delay, and cost are derived analytically as functions of traffic load. Extensive simulations are carried out to verify our analytical results. Our study shows that the PP scheme outperforms both the BP and SP schemes in terms of discover rate while maintaining the same cost as the SP scheme. The PP scheme outperforms the SP scheme in terms of total delay and has a lower total delay than the BP scheme when traffic load is high. We also show that, when the paging delay constraint D is large enough, the PP scheme achieves almost 200 percent of discovery rate and 50 percent of cost of the BP scheme, whereas discovery rate of the SP scheme is far less than that of the BP scheme. Furthermore, we solve the following two-optimization problems for the PP scheme: 1) the minimization of discovery rate with a bound on total delay and 2) the minimization of cost with a bound on total delay. In case the cost factor is not considered but total delay is important, we propose an adaptive scheme: When the traffic is lower than a threshold, the BP scheme is adopted; otherwise, the PP scheme is used. In this case, the threshold value is explicitly derived. [ABSTRACT FROM AUTHOR]

In this paper, we propose concurrently searching for correlated mobile users in mobile communications networks. Previous work either focuses on locating a single mobile user or assumes that the locations of mobile users are statistically independent. We first propose a mobility model in which the movements of mobile users are statistically correlated. Next, we use the theory of Markov chain to derive the joint probability density function of the locations of mobile users. In addition, we propose a novel approach to discover the correlations among the locations of mobile users without explicitly calculating the joint probability density function. Our simulation results indicate that exploring the correlations among the locations of mobile users could significantly reduce the average paging delay and increase the maximum stable throughput. [ABSTRACT FROM AUTHOR]