Phase Noise Compensation Using Limited Reference Symbols in 3GPP LTE Downlink

It is known that phase noise (PN) can cause link performance to degrade severely in orthogonal frequency division multiplexing (OFDM) systems, such as IEEE 802.11, 3GPP LTE and 5G. As opposed to prior PN mitigation schemes that assume perfect channel information and/or abundant reference symbols (e.g., in 802.11), the proposed PN compensation technique applies to LTE and 5G downlink with a limited number of reference symbols. Specifically, in this work, we propose an efficient PN mitigation algorithm where the PN statistics are used to obtain more accurate channel estimates. Based on LTE downlink subframe structure, numerical results corroborate the effectiveness of the proposed algorithm.Comment: 5 pages, 4 figures, lette

Ricean K-factor Estimation based on Channel Quality Indicator in OFDM Systems using Neural Network

Ricean channel model is widely used in wireless communications to characterize the channels with a line-of-sight path. The Ricean K factor, defined as the ratio of direct path and scattered paths, provides a good indication of the link quality. Most existing works estimate K factor based on either maximum-likelihood criterion or higher-order moments, and the existing works are targeted at K-factor estimation at receiver side. In this work, a novel approach is proposed. Cast as a classification problem, the estimation of K factor by neural network provides high accuracy. Moreover, the proposed K-factor estimation is done at transmitter side for transmit processing, thus saving the limited feedback bandwidth.Comment: 11 pages, 8 figure