Self-organizing techniques to resource block scheduling in LTE-A communication systems

The expansion in size and complexity of LTE and LTE-A networks is affecting their performance and their reliability. The consequence of these effects appears in lowering e-node B and individual users throughputs, as well as in increasing Block Error-Rates and overall delays. This work exploits the new Quality of Service feature of Channel Quality Indicator (CQI) that LTE-A systems have introduced in order to alleviate these negative effects. Specifically, we introduce Self Organizing and Neural Network (SONN) algorithms towards providing adaptive solutions. Adaptive Resource-Block scheduling enhances downlink throughput and increases the wireless network capacity as well. Moreover, we present comparative metric performance of the developed algorithms to well-known existing algorithms under the same parameters in extensive standard simulation environment.