Network Signal Strength Research Articles

The Distribution of Route Search Packet Flows in Ad Hoc Networks

The amount of route search (RS) packets in Ad Hoc networks depend on the usage of network node location data and signal strength levels for defining response zones and sending RS packets. In case when route response zones are not restricted in every next step of the routing process, the number of generated RS packets grows according to the geometric progression. When node location data and signal strength level is used, the number of RS packets generated at the next routing step increases according to the arithmetic progression or may be constant. It has been shown in the paper that response zone restrictions help to reduce the number of generated RS packets significantly in high density network, while exploiting the location data and signal strength level in lower density network is less efficient. Ill. 5, bibl. 10, tabl. 1 (in English; abstracts in English and Lithuanian). http://dx.doi.org/10.5755/j01.eee.115.9.744

Using Cellular Network Signal Strength to Monitor Vegetation Characteristics

We demonstrate a new application for cellular communications equipment in monitoring vegetation. We analyze how the vegetation in a cornfield affects the received signal power recorded at cell modems in the field, and we show that the received signal power exhibited long-term and diurnal patterns related to the properties of the vegetation biomass. A novel aspect of this letter is that we recorded the signal strength data at the cellular modem in the field rather than at a cell phone tower and therefore does not require the cooperation of the cell tower owner.

A Methodology for Speech Quality Assessment in Wireless Networks

Performance factors are important in today's* competitive telecommunications market where price differentials have been minimized. An important aspect of service performance is speech quality. This paper illustrates the theoretical foundation of Perceptual Evaluation of Speech Quality (PESQ), the most recent ITU-T standard for objective assessment of speech quality in telecommunication networks, and a methodology for its implementation in wireless networks. Further, the development of the PESQ algorithm according to the standard is presented with the methodology of obtaining the PESQ scores which measure the perceived speech quality of the telecommunication network under test. Finally, the results obtained with the developed measurement setup are discussed. How the results can be used to analyse the impact of various factors on the speech quality of wireless networks is explained. The results were also used to examine the correlation between channel conditions (e.g. network load and signal strength) and the perceived speech quality.

System simulation methodology of optical interconnects for high-performance computing systems

The relentless quest for processing speed in the range of teraflops and beyond has accelerated the need for scalable, parallel, high-performance computing (HPC) systems. To meet this high bandwidth and low power requirements, optical interconnect-based system architectures are being implemented by the HPC industry. While computer-aided design tools have significantly assisted electronic system simulation, the field of system level optoelectronics modeling has lagged behind owing to lack of simulation methodologies and tools. This paper explores the design space of developing OPTISIM, a system level modeling and simulation methodology of optical interconnects for HPC systems. OPTISIM can provide computer architects, designers, and researchers a highly optimized, efficient, and accurate discrete-event environment to test various research hypotheses on HPC systems with power-performance implications. For any given optical interconnect architecture with optical transceivers, wavelength assignment, and traffic patterns, OPTISIM provides end users with network throughput, average latency, power loss, power consumption, and signal strength at the output. The proposed OPTISIM simulation methodology is explained with a case study on the performance of an optical HPC architecture called RAPID.