An Enhanced IRC Algorithm for LTE Downlink Receiver in Multi-cell Environment ∗

This paper proposes an enhanced Interfer- ence rejection combining (IRC) algorithm for Long term evolution (LTE) downlink receiver in multi-cell communi- cation systems. In this algorithm, a proper Multiple input multiple output (MIMO) receive method is adopted ac- cording to Generalized likelihood ratio test (GLRT) inter- cell interference detection. Iteration between channel es- timation and data detection is carried out to improve the performance of IRC algorithm. Simulation results show that this proposed algorithm can effectively detect inter- cell interference and improve Block error rate (BLER) performance and channel estimation Mean squared error (MSE) compared to non-iterative IRC algorithm, making it suitable for LTE downlink receiver in multi-cell cellular systems.

[1]  S. Kay.  Fundamentals of statistical signal processing: estimation theory , 1993 .

[2]  David W. Lin,et al.  Pilot-Based LMMSE Channel Estimation for OFDM Systems With Power–Delay Profile Approximation , 2010, IEEE Transactions on Vehicular Technology.

[3]  Marko Lampinen,et al.  System-Level Performance of Interference Suppression Receivers in LTE System , 2012, 2012 IEEE 75th Vehicular Technology Conference (VTC Spring).

[4]  Moussa Abdi,et al.  Interference rejection combining in LTE networks , 2012, Bell Labs Technical Journal.

[5]  Changming Zhang,et al.  GLRT Approach for Robust Burst Packet Acquisition in Wireless Communications , 2013, IEEE Transactions on Wireless Communications.

[6]  Ove Edfors,et al.  Low Complexity Channel Estimation for LTE in Fast Fading Environments for Implementation on Multi-Standard Platforms , 2010, 2010 IEEE 72nd Vehicular Technology Conference - Fall.

[7]  Werner Haselmayr,et al.  Improving time variant channel estimation for 3GPP LTE-downlink , 2012, 2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications - (PIMRC).

[8]  Steven Kay,et al.  Fundamentals Of Statistical Signal Processing , 2001 .

[9]  Lajos Hanzo,et al.  Decision Directed Channel Estimation Aided OFDM Employing Sample-Spaced and Fractionally-Spaced CIR Estimators , 2007, IEEE Transactions on Wireless Communications.

[10]  Joseph R. Cavallaro,et al.  Performance—Complexity Comparison of Receivers for a LTE MIMO–OFDM System , 2010, IEEE Transactions on Signal Processing.

[11]  Takahiro Asai,et al.  Performance of Advanced Receiver Employing Interference Rejection Combining to Suppress Inter-Cell Interference in LTE-Advanced Downlink , 2011, 2011 IEEE Vehicular Technology Conference (VTC Fall).

[12]  Helmut Bölcskei,et al.  Soft-output sphere decoding: algorithms and VLSI implementation , 2008, IEEE Journal on Selected Areas in Communications.

[13]  Hüseyin Arslan,et al.  Channel estimation for wireless ofdm systems , 2007, IEEE Communications Surveys & Tutorials.

[14]  Hidekazu Taoka,et al.  Investigation on Advanced Receiver Employing Interference Rejection Combining in Asynchronous Network for LTE-Advanced Downlink , 2012, 2012 IEEE 75th Vehicular Technology Conference (VTC Spring).

[15]  Wenjun Zhang,et al.  A channel estimation method based on frequency-domain pilots and time-domain processing for OFDM systems , 2004, IEEE Trans. Consumer Electron..

[16]  Jack M. Winters,et al.  Optimum Combining in Digital Mobile Radio with Cochannel Interference , 1984, IEEE Journal on Selected Areas in Communications.

[17]  Stefania Sesia,et al.  LTE - The UMTS Long Term Evolution, Second Edition , 2011 .