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Wireless Conference - Sustainable Wireless Technologies , European 

About: Wireless Conference - Sustainable Wireless Technologies , European is an academic conference. The conference publishes majorly in the area(s): Wireless network & Communication channel. Over the lifetime, 100 publication(s) have been published by the conference receiving 1281 citation(s).

Papers published on a yearly basis

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Proceedings Article
27 Apr 2011
TL;DR: Three cell selection methods associated with ICIC in heterogeneous networks in the LTE-Advanced downlink are investigated: signal-to-interference plus noise power ratio (SINR)-based cell selection, reference signal received power (RSRP)-basedcell selection, andreference signal received quality (RSRQ)-based Cell selection.
Abstract: In LTE-Advanced, a heterogeneous network where femtocells and picocells overlaid onto macrocells is extensively discussed in addition to traditional well-planned macrocell deployment to improve further the system throughput. In heterogeneous network deployment, cell selection as well as intercell interference coordination (ICIC) is very important to improve the system and cell-edge throughput. Therefore, this paper investigates three cell selection methods associated with ICIC in heterogeneous networks in the LTE-Advanced downlink: signal-to-interference plus noise power ratio (SINR)-based cell selection, reference signal received power (RSRP)-based cell selection, and reference signal received quality (RSRQ)-based cell selection. Simulation results (4 pico eNodeBs and 25 set of user equipment are uniformly located within 1 macro eNodeB) assuming full buffer model show that the downlink cell and cell-edge user throughput levels of RSRP-based cell selection are degraded by approximately 3% and 10% compared to those of SINR-based cell selection under the condition of the maximizing the cell-edge user throughput due to the impairment of the interference level. Furthermore, it is shown that the downlink cell-edge user throughput of RSRQ-based cell selection is improved approximately 5%, although the cell throughput is degraded approximately 5% compared to that for SINR-based cell selection under the condition of the maximizing the cell-edge user throughput.

97 citations

Proceedings Article
27 Apr 2011
TL;DR: Numerical results confirm that there exists an optimal pico-macro density ratio that maximizes the overall energy efficiency of such a two-tier network and provide essential understanding for successful deployment of green heterogeneous networks.
Abstract: With the exponential increase in data traffic driven by a new generation of wireless devices, data is expected to overwhelm cellular network capacity in the next few years. To address this issue, heterogeneous networks have recently being considered as a comprehensive approach to provide high cellular network capacity and coverage. However, the dense and random deployment of small cells and their uncoordinated operation raise important questions about the energy efficiency implications of multi-tier networks. In this paper, we analyze the energy efficiency of downlink two-tier heterogeneous networks, i.e. a network of macrocell base stations overlaid by randomly distributed picocell base stations, where each tier serves a disjoint set of users. Using tools from stochastic geometry, we first derive analytical expressions of success probabilities for each tier when a disjoint set of subchannels is employed. In addition, we evaluate the performance of two-tier networks in terms of energy efficiency and fairness of resource allocation. Numerical results confirm that there exists an optimal pico-macro density ratio that maximizes the overall energy efficiency of such a two-tier network. This work provides essential understanding for successful deployment of green heterogeneous networks.

77 citations

Proceedings Article
27 Apr 2011
TL;DR: This paper aims to improve the KNN algorithm by enhancing the neighboring point selection by applying k-means clustering approach, and indicates that the performance of clustered KNN is closely tied to the number of clusters, number of neighbors to be clustered and the initiation of the center points in k-mean algorithm.
Abstract: Advances in mobile technologies and devices has changed the way users interact with devices and other users. These new interaction methods and services are offered by the help of intelligent sensing capabilities, using context, location and motion sensors. However, indoor location sensing is mostly achieved by utilizing radio signal (Wi-Fi, Bluetooth, GSM etc.) and nearest neighbor identification. The most common algorithm adopted for Received Signal Strength (RSS)-based location sensing is K Nearest Neighbor (KNN), which calculates K nearest neighboring points to mobile users (MUs). Accordingly, in this paper, we aim to improve the KNN algorithm by enhancing the neighboring point selection by applying k-means clustering approach. In the proposed method, k-means clustering algorithm groups nearest neighbors according to their distance to mobile user. Then the closest group to the mobile user is used to calculate the MU's location. The evaluation results indicate that the performance of clustered KNN is closely tied to the number of clusters, number of neighbors to be clustered and the initiation of the center points in k-mean algorithm.

76 citations

Proceedings Article
27 Apr 2011
TL;DR: This paper presents a M2M system architecture based on LTE/LTE-A and highlights the delays associated with each part of the system and proposals on how the latency can be further reduced are described.
Abstract: Machine-to-machine communication has attracted a lot of interest in the mobile communication industry and is under standardization process in 3GPP. Of particular interest is LTE-Advanced support for various M2M service requirements and efficient management and handling of a huge number of machines as mobile subscribers. In addition to the higher throughput, one of the main advantages of LTE/LTE-A in comparison with the previous cellular networks is the reduced transmission latency, which makes this type of networks very attractive for real-time mobile M2M communication scenarios. This paper presents a M2M system architecture based on LTE/LTE-A and highlights the delays associated with each part of the system. Three real-time M2M applications are analyzed and the main latency bottlenecks are identified. Proposals on how the latency can be further reduced are described.

74 citations

Proceedings Article
27 Apr 2011
TL;DR: A channel estimation ASIC, which handles the real-time channel estimation, is presented, which boosts the throughput at feasible silicon cost by adopting a recently proposed estimation method named Approximate Linear Minimum Mean Square Error (ALMMSE).
Abstract: In this paper, hardware implementation aspects of the channel estimator in 3GPP LTE terminals are investigated. A channel estimation ASIC, which handles the real-time channel estimation, is presented. Compared to traditional correlator-based channel estimators, the channel estimator presented boosts the throughput at feasible silicon cost by adopting a recently proposed estimation method named Approximate Linear Minimum Mean Square Error (ALMMSE). In this paper, both the architecture and VLSI implementation of the estimator are elaborated. Implemented using a 65nm CMOS process, the channel estimator supports the full 20MHz bandwidth of 3GPP LTE and consumes only 49 kgates.

70 citations

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Performance
Metrics
No. of papers from the Conference in previous years
YearPapers
2011100