Mobile Signal Strength Research Articles

Network Coverage Mapping

Mobile signal strength (coverage) maps are of great importance to cellular operators for network planning and operation are expensive to obtain, imperfectly reflective of call quality outcomes, and potentially constructed from biased samples. Users of smartphones utilize high-speed network services while commuting on public transit and hope to have a consistent, high-quality connection. Measuring and monitoring coverage and quality of service mean being able to assess reality and its representation. Data collection is a vital ingredient in this process. Finding Mobile signal strength and Mapping the Coverage areas using GIS through differentiating the Network. Due to the massive load demand on cellular networks and frequent changes in the underlying radio channel, users often experience sudden unexpected variations in the connection quality. To overcome variations, we create a Map to differentiate the signal strength with a regular update through the Received Signal Strength Indicator (RSSI) in QGIS Software using Python and XML plugins.

Low-cost System with Handheld Analyzer for Optimizing the Position of Indoor Base Stations

In this paper, an automatic system of locating the indoor area with weak or no mobile signal was proposed and demonstrated experimentally by using the Internet of Things (IoT) technology. Nowadays, the technicians of mobile services providers need to go along with numerous heavy equipment to measure and record the mobile signal strength at outside environment. Recently, there are systems proposed to do such measurement at outdoor area by using the IoT technology automatically. However, these works could not be applied in the indoor area since there are difficulties to do the indoor mapping and positioning. In this work, the Bluetooth Low Energy (BLE) was used to tackle these two difficulties. After a proper placement of BLE in the testing site, while the technician walk around with a handheld analyzer, the data can be obtained accordingly for further analysis in the proposed system which includes the construction of floor plan, detection of mobile signal strength and suggestion of indoor base stations. The gift wrapping and centroid algorithms were used during the analysis. The experimental results showed that the proposed system successfully demonstrated the indoor mapping, positioning of weak mobile signal area and suggestion of indoor base stations for the normal rectangular rooms with an area of 100 m2 on single floor.

QUALITY OF SERVICE PARAMETERS EVALUATION IN CELLULAR NETWORKS.

Quality of Service refers to the evaluation of the overall performance of a service, such as a telephony or computer network particularly the performance seen by the users of the network. QoS is mostly observed from the subscriber’s side. This includes aspects such as the mobile signal strength available to users and other call avaibility measurements. QoS is normally calculated during signal transmission called KPIs that is connected to the subscriber’s happiness whilst using mobile services. QoS parameters are monitored through RF analysis by Drive Test. Some of these QoS parameters related to call and data are discussed in this paper. These parameters directly or indirectly represents the quality of service provided by the network operators in context of Nepal. This analysis of parameters has helped us identify problems like call performance, slow servicing, least ease of use in a service test area for different service providers in the country.

Analysis of mobile internet speed, signal strength and FMDH antenna design for improved internet speed

Internet speed is important in many applications. Mobile signal strength of − 110 to − 120 dBm provides poor internet speed by mobile phones. Mobile makes less signal strength and less internet speed from mobile towers. Signal strength ranges between − 30 and − 65 dBm must be maintained to achieve high-speed internet through mobile phones. Good antenna design is necessary to maintain good signal strength and to improve high-speed internet from weak internet speed in required applications. In this work, an FM radio receiver antenna and parabolic dish antenna with a winding helical coil is proposed for the design of an antenna (FMDH antenna) in order to improve weak internet signals to enable high-speed internet signal. Cell tower radiation is normally reduced at a distance of 1000 m, with a weak signal resulting in slow internet speeds. The reduced radiation signal density from the cell tower causes slower internet speeds in mobile. The winding coil of a helical antenna receives the weaker internet signal from the cell towers to increase gain and signal strength between − 30 and − 65 dBm, improving internet to high-speed performance. The FM radio receiver antenna length is increased, so the gain in the main lobe radiation pattern improves internet speed. High-speed internet is needed for computers through mobile internet. Most computers work through mobile internet connections. Wi-Fi connection signal strength should be − 30 to − 60 dBm for maintaining high-speed internet. The FMDH antenna design is proposed in this paper improves mobile Wi-Fi internet, increasing internet signal strength and internet speed.

A locally optimal handoff algorithm for cellular communications

The design of handoff algorithms for cellular communication systems based on mobile signal strength measurements is considered. The design problem is posed as an optimization to obtain the best tradeoff between the expected number of service failures and expected number of handoffs, where a service failure is defined to be the event that the signal strength falls below a level required for satisfactory service to the subscriber. Based on dynamic programming arguments, an optimal solution is obtained, which, though impractical, can be used as a benchmark in the comparison of suboptimal schemes. A simple locally optimal handoff algorithm is derived from the optimal solution. Like the standard hysteresis algorithm, the locally optimal algorithm is characterized by a single threshold. A systematic method for the comparison of various handoff algorithms that are akin to the receiver operating characteristic (ROC) curves of radar detection is presented. Simulation results show that the locally optimal algorithm outperforms the hysteresis algorithm, especially in situations where accurate prediction of signal strength is possible. A straightforward technique for adapting the locally optimal algorithm to changing environments is suggested. That natural adaptability is the algorithm's principle advantage over current approaches.