With the astronomical increase in cellular traffic, there is need to cut down on the power consumption so as to reduce CO2 emissions and in the process lowering network operational expenditure (OPEX). In this thesis, one method that can be used to lower a Base Station energy consumption is proposed. Traditional cellular networks are designed to offer maximum coverage and connectivity for peak traffic. This is not energy efficient since a lot of energy will go to waste during the time cellular traffic is very low. The scheme that was developed, identifies Base Stations that have very low traffic loads and User Equipment that can all be transferred to neighbouring Base Stations and put the Base Stations to sleep for as long as necessary to save energy and to maintain Quality of Services (QoS) at an acceptable level. The Next Generation Networks (specifically 5G) will be heterogeneous networks as heterogeneous are a promising solution in increasing network performance especially in providing indoor and cell-edges coverage. The solution that was developed in this thesis was specifically designed to work with heterogeneous networks and its performance was also tested on heterogeneous networks. OMNeT++ V4.6 together with INET 2.3.0 and SimuLTE 9.1 were used for the validation of the proposed scheme. After extensive simulations were carried out, it was concluded that some Base Stations in a cellular network, can be put to sleep during the time that cellular traffic is low without compromising the Quality of Service. End-to-end delay, sum throughputs, queue length and Channel Quality Indicator were some of the performance metrics that were used to check whether the developed scheme did not reduce the QoS of a network. / Electrical and Mining Engineering / M. Tech. (Electrical Engineering)

International Telemetering Conference Proceedings / October 28-31, 1996 / Town and Country Hotel and Convention Center, San Diego, California / The concept and model of Spread Spectrum ALOHA (SS-ALOHA), as an important subject to develop dual-purpose satellite system in China, are described in this paper. The new synchronous code format and method for capturing the SS-ALOHA signals are presented and the process of correlation with surface-audio wave (SAW) is shown. The diagram of fast acquisition system and the results of experiment are given.

published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy

published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

published_or_final_version / abstract / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

Huge amounts of data are being collected as a result of the increased use of mobile telecommunications. Insight into information and knowledge derived from these databases can give operators a competitive edge in terms of customer care and retention,<br /> marketing and fraud detection. One of the strategies for fraud detection checks for signs of questionable changes in user behavior. Although the intentions of the mobile phone users cannot be observed, their intentions are reflected in the call data which define usage patterns. Over a period of time, an individual phone generates a large pattern of use. While call data are recorded for subscribers for billing purposes, we are making no prior assumptions about the data indicative of fraudulent call patterns, i.e. the calls made for billing purpose are unlabeled. Further analysis is thus, required to be able to isolate fraudulent usage. An unsupervised learning algorithm can analyse and cluster call patterns for each subscriber in order to facilitate the fraud detection process.<br /> <br /> This research investigates the unsupervised learning potentials of two neural networks for the profiling of calls made by users over a period of time in a mobile telecommunication network. Our study provides a comparative analysis and application of Self-Organizing Maps (SOM) and Long Short-Term Memory (LSTM) recurrent neural networks algorithms to user call data records in order to conduct a descriptive data mining on users call patterns.<br /> <br /> Our investigation shows the learning ability of both techniques to discriminate user call patterns / the LSTM recurrent neural network algorithm providing a better discrimination than the SOM algorithm in terms of long time series modelling. LSTM discriminates different types of temporal sequences and groups them according to a variety of features. The ordered features can later be interpreted and labeled according to specific requirements of the mobile service provider. Thus, suspicious call behaviours are isolated within the mobile telecommunication network and can be used to to identify fraudulent call patterns. We give results using masked call data<br /> from a real mobile telecommunication network.

Approved for public release, distribution is unlimited / Presently, the uniform linear array (ULA) is the most commonly used antenna system for a sectorized cell system like the commercial cellular systems. However, in many omni-directional cell communication systems, such as the ground-based military communications, interest in using the uniform circular array (UCA) has greatly increased. This thesis examines the use of an equally-spaced circular adaptive antenna array at the mobile station for a typical coded direct sequence code division multiple access (DS-CDMA) communication system. This thesis analyzed the performance of a randomly orientated adaptive UCA in the forward channel (base station to mobile station) of a coded multi-cell DS-CDMA system. Using a 3- and 4-element UCA, the ca-pacity and performance of different cellular systems under a range of shadowing conditions, with and without an-tenna sectoring at the base station, and various user capacities were simulated using the Monte Carlo simulation. The results for both ULA, as studied in [7], and UCA were compared and presented in this thesis. / http://hdl.handle.net/10945/1064 / Civilian, Defence Science and Technology Agency (Singapore)

Approved for public release, distribution is unlimited / This thesis examines a circular adaptive antenna array used at the mobile station for a typical Direct Sequence Code Division Multiple Access (DS-CDMA) cellular mobile communications system. The primary objective is to reduce co-channel interference of a wideband CDMA cellular network under a multi-path fading environment. We analyzed the performance of a randomly positioned mobile terminal with a randomly orientated adaptive antenna array in the forward channel (base-station to mobile) of a multi-cell DS-CDMA system and established four performance boundaries. A single complex circular adaptive weight in each element channel of a circular adaptive array sufficiently processes narrowband signals. However, in order to process broadband signals, a tapped-delay line (transveral filter) is required. This tapped-delay line is employed because it can adjust the frequency dependent amplitude and phase. The performance of a DS-CDMA cellular system with a mobile terminal equipped with a circular array and a tapped-delay line is analyzed. It has been demonstrated that the optimization process has been extremely computationally expensive and hence minimum taps should be used for practical considerations. The results illustrated that, in general, for a four-element circular array system, a two tapped-delay line would be sufficient to equalize the broadband signal while providing a similar performance level to that of a narrow-band adaptive array system. / http://hdl.handle.net/10945/1080 / Major, Republic of Singapore Air Force