INTRODUCTION Smartphones and 3G tablets are becoming a major platform for execution of Internet services as more powerful and less expensive devices are becoming available. From this perspective, a large number of mobile applications are becoming available for end users and corporates [1]. In comparison with home users, corporates require a more stable and reliable network especially for wireless communications. Wireless service providers need to monitor their networks not only for received signal level but also for quality of service (QoS) [2]. Frequently the quality of service is integrated with subjective information and reported as Quality of Experience (QoE) to the end users [3, 4]. Both metrics, QoS and QoE require automated and expensive monitoring tools. As smartphones’ analyzing power is becoming comparable to personal computers, the possibility of using their capabilities for live network monitoring lays ahead an interesting research field [5]. In this work, we present a mobile application exploiting measuring capabilities of modern Android-based smartphones. The developed application makes use of Android Programming Interfaces (API) to extrapolate interesting parameters from the user connected network such as received power and network responding time (latency). We use the applications as live monitoring tool in more critical situations such as in the case of fast moving users. A post-processing of the monitored data is provided via a PHP scripting language and is integrated with Google maps, using their respective programming interfaces. These post-processing results in three new layers; one made of signal quality, the next one of network latency and the last one of user velocity for the surveyed area overimposed to the geographical map. The provided information can be useful for service providers to improve their quality of service for end users. This can be in context, as “you cannot improve what you cannot measure”. The paper is organized as follows: in the first paragraph, we provide some technical equations and concepts of signalreceived power, followed by the second section where the extrapolated parameters are presented together with the application interface. In the third paragraph, measured data are provided and the results are commented and analyzed. At the end some conclusions are drawn.
RF RECEIVED POWER ON MOBILE USER EQUIPMENT In wireless communication, high data rate is proportionally related to the level of Signal to Noise Ratio of the received signal. Received power level in far field region [6, 7] is inversely proportional to the square of the distance between transmitting and receiving antenna. In GSM/UMTS network, the distance from the user mobile station (MS) and base station (BS) is to be considered as far field for practical cases. where GRX and GTX are the gains of the receive and transmit antennas, respectively, λ is the wavelength, d is the relative distance from transmitting and receiving antenna and PTX is the transmit power in dBm. From (1) we see that the received power at a fixed distance d cannot be improve without changing the antennas gain or transmitted power. In (1) only free space loss are considered in respect to other factors as multipath propagation (fading) or propagation loss on different media inserted in optical path from BS and MS. Practically, transmitted power and transmitting antenna gain are the same at any measuring time. The receiving antenna in mobile station is assumed omnidirectional, so its orientation does not influence the measuring procedure. This assumption is coherent with ETSI (European Telecommunications Standards Institute) GSM Technical Specification [8, 9] where equipment with integral antenna may be taken into account assuming a 0 dBi gain antenna. Therefore, at a fixed distance from transmitting antenna the received power must be constant. Inpractical cases, this is not true due to other loss factors as multipath propagation and atmospheric loss. Monitoring received power at a fixed distance from transmitting station will provide information’s of the other loss factors that need to be taken into account for offering high quality of service to end users. In this section, the requirements are given in terms of power levels at the antenna connector of the receiver. This means that the tests on equipment on integral antenna will consider fields strengths (E) related to the power levels (P) specified.
Using smartphones as live probe is possible since normally the received power is automatically evaluated by the device for communication capabilities. From a programming point of view, the signal network strength is provided in Android platform as ASU (Arbitrary Strength Unit) levels. The ASU level is an integer in the [0, 31] range (5 bit discretization) directly related to the Received Signal Strength Indicator-RSSI for GSM network (2G). For UMTS (3G) the same android API reports the level index of CPICH-RSCP (Common Pilot Channel – Received Signal Code Power) defined in TS 25.125. In the UMTS cellular communication system, received signal code power (RSCP) denotes the power measured by a receiver on a particular physical communication channel. It is used as an indication of signal strength. Reporting this information in the more common measuring unit (dBm) as indicated by ETSI.