Review of channel quality indicator estimation schemes for multi-user MIMO in 3GPP LTE/LTE-a systems

Multiple-in multiple-out (MIMO) in long-term evolution (LTE) is an essential factor in achieving high speed data rates and spectral efficiency. The unexpected growth in data rate demand has pushed researchers to extend the benefits of multi-user MIMO. The multi-user MIMO system can take full advantage of channel conditions by employing efficient adjustment techniques for scheduling, and by assigning different modulation and coding rates. However, one of the critical issues affecting this feature is the appropriate estimation of channel quality indicator (CQI) to manage the allocated resources to users. Therefore, an accurate CQI estimation scheme is required for the multi-user MIMO transmission to obtain significant improvements on spectral efficiency. This paper presents overviews of multi-user MIMO in LTE/LTE-advanced systems. The link adaptation, scheduling process, and different factors that affect the reliability of CQI measurements are discussed. State-of-the-art schemes for the post-processing CQI estimation, and the comparisons of various CQI estimation schemes to support multi-user MIMO are also addressed

An adaptive threshold feedback compression scheme based on channel quality indicator (CQI) in long term evolution (LTE) system

Channel quality indicator (CQI) feedback in long-term evolution (LTE) system is an essential technique in describing the instantaneous channel state information. The CQI calculations highly depend on the accuracy of the channel estimation process in order to assign appropriate modulation and coding scheme. However, one of the critical issues affecting the LTE system performance is obtaining the CQI for each transmission period which will inevitably cost many resources. Therefore, an appropriate method for reducing CQI feedback overhead along with accurate channel estimation technique is required to manage the allocated resources and obtains significant improvements in system performance. In this paper, an adaptive threshold feedback compression scheme based on CQI scheme is proposed to obtain better system performance in terms of system throughput and error rate in LTE system. This proposed adaptive scheme dynamically adapts its threshold level to the signal to noise ratio variations, thus increasing the throughput and reducing the CQI feedback overhead. Results show that the proposed CQI based adaptive threshold feedback compression scheme enhances the tradeoff between system throughput and block error rate

An adaptive threshold based CQI compression scheme for LTE cellular networks

The frequency domain scheduling gain can be maximized when precise channel information is available at the eNodeB for the whole bandwidth. To compensate for the continuous variations of channel conditions in time and frequency domains, a huge undesirable amount of signaling overhead is required to report the channel quality indicator (CQI). On the contrary, partial channel state information detriments the downlink performances and does not guarantee the quality-of-service (QoS) when real-time multimedia services are applied. Thus, in this paper, the impact of CQI signaling overhead on the downlink performances is formulated. Then, an adaptive signal-to-interference-plus-noise ratio (SINR) threshold based CQI scheme is proposed by using multi-objective swarm intelligence to find the optimal feedback threshold. Based on an LTE system-level simulation, significant enhancements of 20% and 38% in throughput and packet loss ratio (PLR) respectively are obtained compared to a fixed threshold feedback with reasonable cost of feedback overhead. The proposed algorithm provides a high flexibility in responding to certain variations without complex modifications

A channel quality indicator (CQI) prediction scheme using feed forward neural network (FF-NN) technique for MU-MIMO LTE system

In Multi User-Multiple-in Multiple-Out - Long Term Evolution (MU-MIMO-LTE) networks, Channel Quality indicator (CQI) plays a vital role. CQI is crucial in describing the channel information to assign appropriate modulation and coding scheme (MCS). However, obtaining CQI values for each transmission time interval (TTI) inevitably entails use and can lead to an undesirable degradation in spectral efficiency (SE) as well as increasing the error rate. Therefore, providing an accurate and reliable CQI with low overhead is an intricate task. In this paper, a CQI prediction scheme using Feed Forward-Neural Network (FF-NN) algorithm for MU-MIMO-LTE Advanced systems is proposed. Initially, a channel model for MU-MIMO-LTE advanced network is carried out. Through this model, CQI is predicted and the obtained values are compressed using a feedback compression technique. Finally, the proposed technique makes use of FF-NN algorithm to train and achieve enhanced CQI values. Further, an enhanced and accurate CQI values are acquired. Results show that the system SE of single user (SU)-MIMO proportionally increases with the SNR values at the cost of BER. Therefore, a MU-MIMO CQI prediction scheme is recommended to improve the tradeoff between BER and SE

Approximate linear minimum mean square error estimation based on channel quality indicator feedback in LTE systems

The fast fading channel produced by the fast user mobility requires a powerful channel estimation to report the most accurate channel status. Such estimation techniques are usualy suffer from large number of computational processes, and thus, their complexity needs to be minimized. However, the calculation reliability of channel coefficients depends mainly on the accuracy of the channel estimation model. Therefore, obtaining a joint optimized solution for channel estimation error, feedback overhead, and complexity is very crucial. In this paper, two different channel estimation schemes; Linear Minimum Mean Square Error (LMMSE) and Approximate Linear Minimum Mean Square Error (ALMMSE) are used to calculate Channel Quality Indicator (CQI) and Precoding Matrix Indicator (PMI) in the 3GPP-LTE fast fading channel. It is found that, by using a low-complexity ALMMSE, the estimation error is reduced with relatively small reduction in throughput. Therefore, the proposed method is recommended to be used when the network is not fully loaded for better tradeoff concerning MSE and throughput taking into account the fixed and mobility scenarios, and thus, reliable transmission will be targeted

A threshold feedback compression scheme of channel quality indicator (CQI) in LTE systems

The channel quality indicator (CQI) feedback is an essential technique in describing channel state information, especially at high-speed mobility for LTE and LTE-A systems. The number of reported CQI feedback increases when a large number of users are served by eNodeB. However, this feedback inevitably entails uses and can lead to severe degradation in system throughput. Therefore, an appropriate method for reducing CQI feedback overhead must be developed. In this paper, the system throughput and bit error rate (BER) are investigated by using a threshold feedback compression scheme of CQI at low and high user speeds. Results show that the system throughput proportionally increases with the threshold values at the cost of BER. Therefore, a high threshold level is recommended under high user speed conditions to improve the tradeoff between BER and throughput. In contrast, a low threshold level is targeted to provide reliable transmission when the network is fully loaded and the user is in a bad channel state

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

A partial feedback reporting scheme for LTE mobile video transmission with QoS provisioning

Opportunistic frequency-domain scheduling and link adaptation enable the long term evolution (LTE) cellular systems to maximize the throughput. Successful scheduling and link adaptation require perfect channel state information (CSI) at the eNodeB. However, for multi-carriers systems, a huge undesirable amount of signaling overhead is required to report the channel quality indicator (CQI) for the whole bandwidth. On the contrary, reducing the size of CQI overhead detriments the downlink performances and does not guarantee the quality-of-service (QoS) when real-time multimedia services are applied. As a consequence, a tradeoff between CQI overhead and the downlink performances is presented in this paper. Then, an Adaptive Threshold CQI Partial Feedback (ATCPF) scheme is proposed by using multi-objective swarm intelligence to find the optimal feedback threshold. Based on an LTE system-level simulation, significant enhancements of 20% and 38% in throughput and packet loss ratio (PLR) respectively are obtained compared to a fixed threshold feedback. Since video flows are considered, a self-optimized partial feedback (SOPF) is further developed by using cross-layer optimization to guarantee QoS. The results show that the feedback overhead is minimized at low-load network condition while maintaining the PLR below its target. The proposed algorithm provides a high flexibility in responding to certain variations, and it enables the cellular systems to support multimedia services