Channel prediction and feedback in multiuser broadcast channels

Multiuser linear precoding requires channel state information (CSI) at the transmitter. In the absence of channel reciprocity between the uplink and downlink, a feedback mechanism must be designed to communicate CSI estimates from the mobile receivers to the transmitter. Limiting the total feedback rate is an important design goal for multiuser multiple-input, multiple-output systems, as the feedback overhead can potentially consume a large percentage of system resources, especially when the total number of antennas is large. In this paper, we focus on the challenges of feedback delay and reducing feedback rate; we predict N-frames-ahead, based on the one-step Kalman predictor, and derive a theoretical expression for the prediction mean squared error (MSE). We present simulation results that illustrate a tradeoff between prediction MSE and computational complexity, and also demonstrate situations where adaptive delta modulation (ADM) can be used to exploit temporal redundancy and reduce the required feedback rate.

[1]  Todor Cooklev,et al.  Air Interface for Fixed Broadband Wireless Access Systems , 2004 .

[2]  H. Boche,et al.  Downlink Sum-MSE Transceiver Optimization for Linear Multi-User MIMO Systems , 2005, Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005..

[3]  Kareem E. Baddour,et al.  Autoregressive modeling for fading channel simulation , 2005, IEEE Transactions on Wireless Communications.

[4]  Mohamed Najim,et al.  Two Ways to Simulate a Rayleigh Fading Channel Based on a Stochastic Sinusoidal Model , 2008, IEEE Signal Processing Letters.

[5]  Mohinder S. Grewal,et al.  Kalman Filtering: Theory and Practice Using MATLAB , 2001 .

[6]  Jaap C. Haartsen Impact of non-reciprocal channel conditions in broadband TDD systems , 2008, 2008 IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications.

[7]  Raviraj S. Adve,et al.  Linear processing and sum throughput in the multiuser MIMO downlink , 2008, IEEE Transactions on Wireless Communications.

[8]  John M. Cioffi,et al.  Joint Tx-Rx beamforming design for multicarrier MIMO channels: a unified framework for convex optimization , 2003, IEEE Trans. Signal Process..

[9]  Nuggehally Sampath Jayant,et al.  Adaptive delta modulation with a one-bit memory , 1970, Bell Syst. Tech. J..

[10]  Namseok Chang,et al.  MIMO-OFDM Downlink Channel Prediction for IEEE802.16e Systems Using Kalman Filter , 2007, 2007 IEEE Wireless Communications and Networking Conference.

[11]  R. Ramesh,et al.  Delta modulation for channel feedback in transmit diversity systems , 2005, 2005 IEEE 61st Vehicular Technology Conference.

[12]  S. P. Lloyd,et al.  Least squares quantization in PCM , 1982, IEEE Trans. Inf. Theory.

[13]  N. S. Jayant Adaptive Delta Modulation of Speech with a One‐Bit Memory , 1970 .

[14]  Raviraj S. Adve,et al.  Linear Processing for the Downlink in Multiuser MIMO Systems with Multiple Data Streams , 2006, 2006 IEEE International Conference on Communications.