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Partial Feedback Scheme with an Interference‐
Aware Subcarrier Allocation Scheme in a 
Correlated LTE Downlink 
Rosdiadee ...
METHODOLOGY
• SINR metric, representation of CQI & to determine the subcarrier allocation process
• has the knowledge of s...
RESULTS & ANALYSIS
-8 -6 -4 -2 0 2 4 6 8
10
-3
10
-2
10
-1
10
0
Signal-to-Noise Ratio (SNR) in dB
BitErrorRate(BER)
CSI on...
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Partial Feedback Scheme with an Interference-Aware Subcarrier Allocation Scheme in a Correlated LTE Downlink

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Partial Feedback Scheme with an Interference-Aware Subcarrier Allocation Scheme in a Correlated LTE Downlink

  1. 1. Partial Feedback Scheme with an Interference‐ Aware Subcarrier Allocation Scheme in a  Correlated LTE Downlink  Rosdiadee Nordin, Mahamod Ismail Department of Electrical, Electronics and Systems Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia (Malaysia) adee@eng.ukm.my, mahamod@eng.ukm.my  INTRODUCTION • Full feedback scheme increase the uplink overhead requirement • This paper consider the use of partial feedback scheme utilizing DFT‐based codebook precoding to exploit spatial diversity from the multiuser (MU)‐MIMO. • In addition, the frequency diversity will be exploited via an interference‐aware subcarrier allocation scheme. • Self‐interference occurs due to an increasing spatial correlation between the communicating MIMO antennas PROBLEM  BACKGROUNDS Feedback Schemes in MU‐MIMO Transmissions • MU‐MIMO transmission uses the Channel Quality Information (CQI) to serve the spatially multiplexed users from the precoding techniques • The use of precoding is at the expense of channel knowledge – places significant burden on the uplink • Two feedback strategies considered: – Full: feeds back a single CQI value for every matrix in the codebook for each RB – Partial: feeds back a single CQI value for the preferred matrix for each RB (quantized) • CQI information available per RB, allows channel resources to be allocated effectively to different users while reducing the amount of feedback. DFT‐Based Codebook Precoding • In LTE Rel 8, eNodeB transmits through a codebook‐based spatial beam, which ensures uniform sector coverage across the cell • DFT‐based codebook has shown to be effective against wide range of spatial correlation: uncorrelated to fully correlated -10 -5 0 5 10 15 20 0 2 4 6 8 10 12 SNR (dB) capacity(bps/Hz) RBS =0.0,RMS =0.0 RBS =0.4,RMS =0.4 RBS =0.5,RMS =0.5 RBS =0.0,RMS =0.9 RBS =0.9,RMS =0.0 RBS =0.9,RMS =0.9 RBS =1.0,RMS =1.0 OBJECTIVES • Investigate BER performance between partial vs. full feedback scheme in varying MIMO channel conditions • Mitigate the effect of MIMO spatial correlation (self‐interference) by combining both spatial and frequency diversity
  2. 2. METHODOLOGY • SINR metric, representation of CQI & to determine the subcarrier allocation process • has the knowledge of self‐interference, especially when the correlation is high inside spatial subchannels • Allows the user with lowest channel gain to have the next best subcarrier gain: fairness vs. error probability • Involves sorting, comparing and simple arithmetic. • Ranks users from lowest to highest channel gain     NGGEHG EHG SINR qjqjkqqksqjqjkk sqqkkq k         2 , 22 , 2 Knowledge of self- interference Main spatial layerq= spatial layer k= subcarrier index MMSE filter Parameters Value Downlink Bandwidth 5 MHz Time Slot/ Sub‐frame  duration 0.5 ms/  1ms Subcarrier Spacing 15 kHz Precoding CB size, L 1,2,4,8 FFT Size, NFFT 1024 Useable subcarrier, Nsub 600 Total users, K 10 OFDM symbols/ time slot  (Short/Long CP) 7/6 Correlation Modes RMS RBS Uncorrelated 0.00 0.00 Fully Correlated 0.90 0.90 Feedback Scheme Full  Feedback Partial  Feedback SU‐ MIMO  Preferred Layer 1 CQI 4 bits 4 bits 4 bits Preferred Layer 2 CQI 4 bits 4 bits Alternative Layer 1 CQI 4 bits ‐ ‐ Alternative Layer 2 CQI 4 bits ‐ ‐ Preferred Matrix Index 1 bit 1 bit 1 bit Total bits per RB 17 bits 9 bits 5 bits Assumptions • 2x2 MU‐MIMO, QPSK ½ rate (LTE Rel. 8) • 500m radius, NLOS with 251 ns delay spread (3GPP‐SCM Urban Micro)
  3. 3. RESULTS & ANALYSIS -8 -6 -4 -2 0 2 4 6 8 10 -3 10 -2 10 -1 10 0 Signal-to-Noise Ratio (SNR) in dB BitErrorRate(BER) CSI only (no precoding) DFT only, L=2 DFT+ Interference-Aware, L=2 DFT+ Interference-Aware, L=8 Fully correlated channel Uncorrelated channel -8 -6 -4 -2 0 2 4 6 8 10 -3 10 -2 10 -1 10 0 Signal-to-Noise Ratio (SNR) in dB BitErrorRate(BER) Partial MU, RMIMO =0.99 Full MU, RMIMO =0.99 Partial MU, RMIMO =0.00 Full MU, RMIMO =0.00 CONCLUSIONS • DFT‐based codebook adaptation enables the quantization to exploit the spatial correlation inherent in the channel. • Full feedback scheme offers superior BER performance at the expense of a high uplink overhead requirement. • The partial feedback scheme offers a trade‐off between the multiuser diversity gain and reduced feedback requirement. • Combination of partial feedback and interference‐aware subcarrier allocation scheme improve the BER performance, especially in a fully correlated MIMO channel. -10 -5 0 5 10 15 20 10 -3 10 -2 10 -1 10 0 Signal-to-Noise Ratio (SNR) in dB BitErrorRate(BER) L=1, 'Full' L=1, 'Uncorr' L=2, 'Full' L=2, 'Uncorr' L=4, 'Full' L=4, 'Uncorr' L=8, 'Full' L=8, 'Uncorr' • SU‐MIMO does not benefit from the increased codebook size for either correlation scenario since eNodeB unable to exploit the channel knowledge from the feedback path • partial feedback scheme offers negligible performance loss to the full feedback scheme with the advantage of a reduced overhead requirement on the uplink capacity • Benefit of combining the DFT‐based codebook precoding and an interference‐aware subcarrier allocation scheme in a fully correlated channel for partial feedback MU‐MIMO case -8 -6 -4 -2 0 2 4 6 8 10 -3 10 -2 10 -1 10 0 Signal-to-Noise Ratio (SNR) in dB BitErrorRate(BER) CSI only (no precoding) DFT only, L=2 DFT+ Interference-Aware, L=2 DFT+ Interference-Aware, L=8 • Trade‐offs to mitigate self‐interference vs. codebook size • Larger codebook has a richer selection of precoding matrices that can be used to find a better codeword match during encoding *This work is supported by the Universiti Kebangsaan Malaysia, under the grant scheme UKM‐GGPM‐ICT‐032‐2011*

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