Telecommunication System Engineering

Freeman, Roger L.

doi:10.1002/0471728489

Cited by 51 publications

(32 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Smaller objects, foliage, and edges can also cause the signal to scatter resulting to rapid variations in the received signal strength. The Log-distance Path Loss Model path loss model takes this into account and is shown in (4) where the loss is calculated over a distance d [20], [12], [17], [11], [30], [6].…”

Section: ) Log-distance Path Loss Modelmentioning

confidence: 99%

Assessment and Modeling of GSM Signal Propagation in Uyo, Nigeria

Orike¹,

Elechi²,

Ekanem³

2017

EJERS

View full text Add to dashboard Cite

Abstract-High quality of service is a paramount concern in wireless networks. One of the strategies in achieving optimal performance is to use wireless empirical models to predict wireless link quality factors such as path loss and the received power in any given transmission domain with irregular terrain. The primary goal of this study is to develop a radio wave propagation model for Uyo metropolis. An assessment was carried out in three major roads within the city of Uyo in Akwa Ibom State, to determine the quality of GSM signal reception by measuring the signal field strength, magnetic field strength, and power density of the base transceiver stations. The measurements were carried out using radio frequency electromagnetic field strength meter over a distance of 2000 meters from the base stations. The results of the measurements were analysed and a path loss model was developed for Uyo using linear regression model. Three empirical models: Okumura-Hata model, COST-Hata model, and Egli model were also applied in predicting the path loss in Uyo and the results obtained were compared with the developed model for Uyo metropolis. The comparison showed that Route D model had a better comparison factor with the developed model while the Okumura-Hata and COST-Hata were almost the same with more loss as the distance increased. In all the measurements, the standard deviation was between 3.31 dB and 3.36 dB.

show abstract

Section: ) Log-distance Path Loss Modelmentioning

confidence: 99%

Assessment and Modeling of GSM Signal Propagation in Uyo, Nigeria

Orike¹,

Elechi²,

Ekanem³

2017

EJERS

View full text Add to dashboard Cite

show abstract

“…Moreover, in the case with the lowest value of the innovation parameter p 5 =0.5, the calculated value of the number of telecommunication services users was 92423. Precisely calculated number of users is shown in Table 1 for all values of the selected parameter p. It presents a calculated number of users within the first hour after a natural disaster, which represented 30 eBhC (equated busy hour call) 14 . If the critical time analysis (during which the number of users of telecommunication services reaches its maximum) is carried out, the time that defines the speed of diffusion is obtained, i.e., time giving the maximum number of users in the shortest period of time.…”

Section: Time (H)mentioning

confidence: 99%

The Application of Bass Diffusion Model in Forecasting Telecommunication Services Users in Military Assistance to Civilian Authorities

Pavlović¹,

Karović²

2015

DSJ

View full text Add to dashboard Cite

This paper analyses the application of Bass's diffusion model in forecasting the number of telecommunication services users in the event of natural disasters. Citizens' behaviour has been modelled in the case of an emergency situation caused by an earthquake with high magnitude. We analysed the area of an administrative district in the south-west part of the Republic of Serbia which includes two cities and three municipalities. To control the consequences of natural disasters, a unit of the Army of Serbia with the required number of radio transceivers for establishing communication between the vulnerable population and rescuers with command staff at the observed territory has been dimensioned. Special emphasis is given to the provision of telecommunication support in the military assistance in a relief operation with civil authorities.

show abstract

“…3. The sum of unavailabilities is a well-established and wellverified approximation for the product of availabilities where all availabilities being considered are in practice close to 100% [11].…”

Section: Notesmentioning

confidence: 99%

Availability Analysis and Enhanced Availability Design in p-Cycle-Based Networks

Clouqueur

Grover

2005

Photon Netw Commun

View full text Add to dashboard Cite

Abstract. p-Cycle protection is a fairly new survivability scheme that has the interesting properties of offering restoration speeds essentially the same as those offered by ring protection while requiring almost as little redundant capacity as adaptive mesh restoration [D. Stamatelakis, W.D. Grover, IEEE Transactions on Communications, vol. 48, no. 8, (August 2000), pp. 1262-1265. This paper presents the first analytical consideration of the availability of paths in a network protected by p-cycles. Results confirm the importance that cycle sizes play in terms of availability and suggests principles or strategies for achieving high availability of paths in a network protected by p-cycles. Based on these insights, two new formulations for joint service path provisioning and capacity planning are proposed. The first one offers a way to improve the availability of selected service paths by using a different routing strategy for them than for regular service paths. The second formulation enables a new class of service paths that are offered two protection options instead of just one. That class of service paths is expected to see its availability improved in a quantum step way relative to the availability of paths having only one protection option.

show abstract

Telecommunication System Engineering

Cited by 51 publications

References 0 publications

Assessment and Modeling of GSM Signal Propagation in Uyo, Nigeria

Assessment and Modeling of GSM Signal Propagation in Uyo, Nigeria

The Application of Bass Diffusion Model in Forecasting Telecommunication Services Users in Military Assistance to Civilian Authorities

Availability Analysis and Enhanced Availability Design in p-Cycle-Based Networks

Contact Info

Product

Resources

About