Capacity based rank prediction for MIMO design

• US 20060018397A1
• Filed: 12/22/2004
• Published: 01/26/2006
• Est. Priority Date: 07/21/2004
• Status: Active Grant

• Current Assignee: Qualcomm, Inc.
• Original Assignee: Qualcomm, Inc.
• Inventors: Sampath, Hemanth, Kadous, Tamer
• Granted Patent: US 7,567,621 B2
• Time in Patent Office: Days
• US Class Current: 375/267
• CPC Class Codes: H04B 17/336 Signal-to-interference ratio [SIR] or carrier-to-interference ratio [CIR]
• CPC Class Codes: H04L 1/0003 by switching between different modulation schemes
• CPC Class Codes: H04L 1/0009 by adapting the channel coding H04L1/1812 takes precedence
• CPC Class Codes: H04L 1/0026 Transmission of channel quality indication
• CPC Class Codes: H04L 1/0071 Use of interleaving interleaving per se H03M13/27
• CPC Class Codes: H04L 1/065 by means of convolutional encoding
• CPC Class Codes: H04L 1/0656 Cyclotomic systems, e.g. Bell Labs Layered Space-Time [BLAST]
• CPC Class Codes: H04L 1/1812 Hybrid protocols; Hybrid automatic repeat request [HARQ]
• CPC Class Codes: H04L 2025/03426 transmission using multiple-input and multiple-output channels
• CPC Class Codes: H04L 25/0204 of multiple channels
• CPC Class Codes: H04L 25/0242 using matrix methods
• CPC Class Codes: H04L 25/03343 Arrangements at the transmitter end
• CPC Class Codes: H04L 27/26265 Arrangements for sidelobes suppression specially adapted to multicarrier systems, e.g. spectral precoding
• CPC Class Codes: H04L 5/0023 Time-frequency-space
• CPC Class Codes: H04L 5/0046 Determination of how many bits are transmitted on different sub-channels
• CPC Class Codes: H04L 5/006 Quality of the received signal, e.g. BER, SNR, water filling
• CPC Class Codes: H04L 5/023 Multiplexing of multicarrier modulation signals multicarrier modulation H04L27/2601

Abstract

The performance of a Single Code Word (SCW) design with low complexity MMSE receiver & rank prediction is similar to the Multiple Code Word (MCW) design with successive interference cancellation (SIC). A method of rank prediction comprises calculating MIMO channel matrices corresponding to layer transmissions for each tone, calculating signal-to-noise ratios (SNRs) for each tone based on the MIMO channel matrices, mapping the SNR for each tone to generate effective SNRs for each layer transmission, calculating additive white Gaussian noise (AWGN) capacities corresponding to the effective SNRs and maximizing an over-all spectral efficiency based on the AWGN capacities; and selecting a rank based on maximizing the over-all spectral efficiency.

Claims

1. A method of rank prediction, comprising:

calculating MIMO channel matrices corresponding to layer transmissions for each tone;

calculating signal-to-noise ratios (SNRs) for each tone based on the MIMO channel matrices;

mapping the SNR for each tone to generate effective SNRs for each layer transmission;

calculating additive white Gaussian noise (AWGN) capacities corresponding to the effective SNRs and denoted as Cap₁, Cap₂, Cap₃, Cap₄;

selecting an absolute highest Cap of the highest Caps; and

selecting a rank based on the selected absolute highest Cap.

2. The method of claim 1, further, comprising sending a quality indicator based on the selected rank.

3. The method of claim 2, wherein the quality indicator is Carrier-Quality-to-Interference (CQI).

4. The method of claim 1, wherein the number of layer transmission is four.

5. The method of claim 1, wherein the SNR is calculated as

${\mathrm{SNR}}_M$

( k ) ≈

1 M ⁢

∑

m = 0 M - 1 ⁢

[ diag ⁢

〈

[ P M ⁡

( k ) * ⁢

H ⁡

( k ) * ⁢

H ⁡

( k ) ⁢

P M ⁡

( k ) + σ

2 ⁢

I ] - 1 〉

] m , m - 1 ⁢

 

⁢

∀

M = [ 1 , 4 ]

, where k is the kth tone, H(k)P₁(k), H(k)P₂(k), H(k)P₃(k) and H(k)P₄(k), correspond to {1,2,3,4} layer transmissions.

6. The method of claim 1, wherein the mapping is unconstrained.

7. The method of claim 1, wherein the selected rank {circumflex over (M)} is calculated as

$\hat{M}=\underset{M=\left[1,4\right]}{\mathrm{argmax}}$

 

[ M ×

Cap M ] .

8. The method of claim 7, wherein the quality indicator CQI is calculated as CQI({circumflex over (M)})=Quant [EffSNR_{{circumflex over (M)}}], where EffSNR is the effective SNR of the selected rank.

9. A wireless communications device, comprising:

means for calculating MIMO channel matrices corresponding to layer transmissions for each tone;

means for calculating signal-to-noise ratios (SNRs) for each tone based on the MIMO channel matrices;

means for mapping the SNR for each tone to generate effective SNRs for each layer transmission;

means for calculating additive white Gaussian noise (AWGN) capacities corresponding to the effective SNRs and denoted as Cap₁, Cap₂, Cap₃, Cap₄;

means for selecting an absolute highest Cap of the highest Caps; and

means for selecting a rank based on the selected absolute highest Cap.

10. A processor programmed to execute a method of rank prediction, the method comprising:

calculating MIMO channel matrices corresponding to layer transmissions for each tone;

calculating signal-to-noise ratios (SNRs) for each tone based on the MIMO channel matrices;

mapping the SNR for each tone to generate effective SNRs for each layer transmission;

calculating additive white Gaussian noise (AWGN) capacities corresponding to the effective SNRs and denoted as Cap₁, Cap₂, Cap₃, Cap₄;

selecting an absolute highest Cap of the highest Caps; and

selecting a rank based on the selected absolute highest Cap.

11. A computer readable media embodying a method of rank prediction, the method comprising:

calculating MIMO channel matrices corresponding to layer transmissions for each tone;

calculating signal-to-noise ratios (SNRs) for each tone based on the MIMO channel matrices;

mapping the SNR for each tone to generate effective SNRs for each layer transmission;

calculating additive white Gaussian noise (AWGN) capacities corresponding to the effective SNRs and denoted as Cap₁, Cap₂, Cap₃, Cap₄;

selecting an absolute highest Cap of the highest Caps; and

selecting a rank based on the selected absolute highest Cap.