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UE Feedback Optimisation in HSDPA
In High-Speed Downlink Packet Access technology (HSDPA) in WCDMA, a base station schedules transmissions and allocates resources to mobile terminals (User Equipment, UEs) based on Channel Quality Indicator (CQI) reports it continuously receives from each UE. This provides the key advantage of HSDPA to render high data rates by rapidly adapting transmission from the network to the present channel conditions.
The thesis will investigate if the existing CQI reporting concept may be enhanced to provide the same or better information quality while consuming less network and terminal resources. The study will involve simulations in a Matlab-based radio network simulator as well as analytical radio resource management (RRM) investigations to evaluate the performance of the new proposed feedback algorithms.
CQI reports from UEs to the base station have proven to be an effective feedback mechanism enabling fast channel adaptation for HSDPA. CQI is constantly reported by each UE to its serving base station at given time intervals. It reflects the instantaneous Carrier-to-Interference Ratio (CIR) that the terminal is experiencing on the HSDPA data channel. As fast fading conditions at the mobile receiver are constantly changing, there is a trade-off between information quality on the one hand, and CQI reporting frequency and resource utilisation in the network on the other.
With enhancements to mobile broadband over HSPA such as Enhanced Uplink (EUL), higher order modulation and MIMO schemes (Multiple Input Multiple Output), resource utilisation efficiency and complexity reductions are becoming increasingly important. Hence there is a vital interest to enhance the CQI reporting concept to reduce its resource burden and the complexity it creates, for example in the HSDPA scheduler. An increased use of ACK/NACK reports on received packets on the HSDPA data channel that are also sent as feedback to the network could be one means to achieve these goals.
By means of computer simulations and/or analytical techniques, the thesis student will estimate the system performance and evaluate the resource consumption of enhanced UE feedback algorithms in a number of system and traffic scenarios. If promising, the results may be directly considered for upcoming solutions in high-speed data networks.
By e-mail in English with “MSc thesis project” in the subject line. Please include a list of courses with marks and a CV. Please also provide the names and contact details of two persons that may be contacted as references during the recruitment process. Applications close on May 11.
Electrical Engineering, Engineering Physics or Computer Engineering, 180 points or equivalent. Good marks are a plus. Advanced courses in control theory, signal processing, queuing theory and performance analysis are an advantage.
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