This paper introduces a weighted context-based step length estimation algorithm for pedestrian dead reckoning. Six pedestrian contexts are considered: stationary, walking, walking sideways, climbing and descending stairs, and running. Instead of computing the step length based on a single context, the step lengths computed for different contexts are weighted by the context probabilities. This provides more robust performance when the context is uncertain. The proposed step length estimation algorithm is part of a pedestrian dead reckoning system which includes the procedures of step detection and context classification. The step detection algorithm detects the step time boundaries using continuous wavelet transform analysis, while the context classification algorithm determines the pedestrian context probabilities using a relevance vector machine. In order to assess the performance of the pedestrian dead reckoning system, a dataset of pedestrian activities and actions has been collected. Fifteen subjects have been equipped with a waist-belt smartphone and traveled along a predefined path. Acceleration, angular rate and magnetic field data were recorded. The results show that the traveled distance is more accurate using step lengths weighted by the context probabilities compared to using step lengths based on the highest probability context.
Recently, the availability of innovative and affordable COTS (Commercial Off-The-Shelf) technological solutions and the ever-improving results of microelectronics and microsystems technologies have enabled the design of ever smaller yet ever more powerful satellites. The emergence of very capable small satellites heralds an era of new opportunities in the commercial space market. Initially applied only to scientific missions, Earth observation and remote sensing, small satellites are now being deployed to support telecommunications services. This review paper examines the operational features of small satellites that contribute to their success. An overview of recent advances and development trends in the field of small satellites is provided, with a special focus on telecommunication aspects such as the use of higher frequency bands, optical communications, new protocols, and advanced architectures.
This paper deals with a modified version of a blind adaptive multiuser detector for direct sequence code-division multiple-access (DS-CDMA) wireless communication systems which is named precombining blind adaptive multiuser detector (PBA-MUD). The main properties of this receiver are low complexity, multiple-access interference mitigation and remarkable near-far resistance in time-varying multipath fading scenarios. In particular, the PBA-MUD is based on a blind adaptive algorithm that allows the detector to avoid deep fading impairments and the cancellation of the desired signal due to signature sequence mismatch. Nevertheless, such a receiver experiences a performance degradation in fast fading channels. In order to overcome this problem, a window reprocessing technique (Del Re et al. 2001) was introduced which yielded a new blind detection algorithm. It will be shown that this receiver, together with this new algorithm [precombining reprocessing window blind adaptive multiuser detector (PWBA-MUD)] allows a high performance without requiring training sequences or the knowledge of the interfering signature waveforms in multipath fast fading channels.
Abstract-Energy efficiency is one of the main challenges to be faced by mobile communications in the near future. The growth of the mobile communications market which is boosted by the increasing penetration of smartphones and laptops requires an increase of the network capacity and, consequently, a great leap forward also for the infrastructures. In this scenario, in order to reduce the operative expenditures, the network operators pay attention to energy saving strategies that may also contribute to the reduction of greenhouse emissions. In this paper the exponential smoothing technique is applied to forecast traffic in a given area considering daily and weekly variations. The availability of a reliable prediction of the future traffic values allows the adaptation of macro base station transmission power and the introduction of a sleep mode for micro base stations and permits to guarantee the requested network capacity while saving energy consumption. Results show the effectiveness of traffic forecast technique for capacity prediction and the usefulness of the proposed algorithms for energy efficiency maximization, affording very good performance, very close to the optimum one.
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