In this project, we investigate single client throughput optimization High-Speed Downlink Packet Access (HSDPA). In particular, we propose offline and online optimization algorithms which modify the Channel Quality Indicator (CQI) utilized by the system for scheduling of data transmission. In the offline algorithm, a given target block error rate (BLER) is accomplished by changing CQI based on ACK/NAK history. By clearing through various target BLERs, we can discover the throughput ideal BLER disconnected. This calculation could be utilized to advance throughput as well as to enable the fair resource allocation among multiple clients in HSDPA.
In the online algorithm, the CQI offset is adjusted utilizing an estimated short-term throughput gradient without the requirement for an objective BLER. An adaptive size instrument is proposed to track the temporal variation of the environment. onvergence behavior of both algorithms is analyzed. The part of the analysis that deals with constant step size gradient algorithm may be applied to other stochastic optimization techniques. The convergence analysis is confirmed by our simulations. Simulation results also yield valuable insights on the value of optimal BLER target. Both offline and online algorithms are shown to yield up to throughput improvement over the conventional approach of targeting BLER.
CQI reports are expected to accurately reflect the HS-PDSCH performance that the UE can support in the existing wireless channel conditions. It is suggested in that, in static channel conditions, the UE report CQI with the end goal that it achieves a block error rate (BLER) near when scheduled data relating to the medium reported CQI. In practice, the exactness of CQI reports in reflecting HS-PDSCH performance is influenced by the wireless channel conditions.
An adaptive algorithm to achieve a given target BLER utilizing the stochastic gradient descent strategy, which adjusts the CQI balance adaptively based on short-term BLER got from the ACK/NACK history. Via searching through various target BLERs, we can discover the throughput optimal BLER offline. The proposed algorithm can be executed at the UE and also at the Node B. At the point when connected at the Node B, in addition to achieving the objective BLER, it can also save transmit power. This algorithm could be utilized to refine CQI-BLER alignment as well as to enable reasonable resource allocation among mobile clients in HSDPA. Standard stochastic approximation (SA) algorithms commonly require a decreasing stepsize.
Path Set Module.
Packet Transaction Module.
• System: Pentium IV 2.4 GHz.
• Hard Disk: 40 GB.
• Floppy Drive: 1.44 Mb.
• Monitor: 14′ Color Monitor.
• Mouse: Optical Mouse.
• RAM: 512 Mb.
Keyboard: 101 Keyboard.
• Operating system: Windows XP.
• Coding Language: ASP.Net with C#
• Data Base: SQL Server 2005.