Channel quality indicator for long term evolution system based on adaptive threshold feedback compression scheme

The huge demands for mobile wireless data traffics are increasing rapidly during the recent years. Long-term evolution (LTE) has been standardized by the Third- Generation Partnership Project (3GPP) as a new access technology to meet the tremendous requirements of current mobile systems. To further support the network infrastructure and satisfy all the diverse sets of requirements, LTE adopted an advanced and powerful technique such as Multiple-in multiple-out (MIMO) and orthogonal frequency division multiplexing OFDM. CQI feedback is an essential technique in describing the channel state information of LTE system. Hence, CQI calculations highly depend on the accuracy of the channel estimation process. A precious channel estimation scheme is necessary to indicate the instantaneous channel condition. Many practical problems in LTE occur when LTE feedback is calculated by CQI. If the user needs to report precise channel state condition, the amount of CQI reported to the eNodeB must be increased. However,increasing the amount of such feedback inevitably results in extra signaling overhead and system performance degradation. Therefore, an appropriate method for CQI estimation and CQI feedback overhead reduction is important. This thesis proposes an adaptive feedback algorithm that uses a threshold scheme to enhance the system throughput while maintaining low Block Error Rate (BLER), Bit Error Rate (BER), and overhead. This proposed feedback mechanism considers the channel quality condition, modulation order, and code rate for various antenna configurations and different user speeds. Results show that the system throughput increases with a stable LTE BLER target and system overhead by using the adaptive threshold of the CQI feedback scheme. This proposed adaptive scheme dynamically adapts the threshold level to Signal to Noise Ratio (SNR) variations, thus increasing the throughput and reducing the CQI feedback overhead. This adaptive approach also enhances the tradeoff between system throughput and BLER. Compared with conventional CQI feedback schemes,such as the full feedback, averaging best-m CQI methods, the proposed scheme significantly improves the system throughput while maintaining the BLER target and overhead. The percentage difference from the adaptive threshold CQI feedback scheme is around 2.4% compared with the averaging method, wherein a 2% system improvement occurs across all SNR values. The percentage difference is 2.1%,compared with the full feedback method, with only 0.5% degradation. The results demonstrate that although increasing the antenna was improved the system throughput remarkably but it comes at the cost of BLER performance. Using MIMO 2x2 is highly recommended since it achieves a reasonable results compared with high and low order antenna configurations.

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