SINR measurement method for OFDM communications systems

• US 7,260,054 B2
• Filed: 05/30/2002
• Issued: 08/21/2007
• Est. Priority Date: 05/30/2002
• Status: Active Grant

• Current Assignee: DENSO Corporation
• Original Assignee: DENSO Corporation
• Inventors: Olszewski, Kim Joseph
• Primary Examiner(s): Vu; Huy D.
• Assistant Examiner(s): NG, CHRISTINE Y
• Application Number:
  US10/161,133
• Publication Number:
  US 20030223354A1
• Time in Patent Office: 1,909 Days
• Field of Search: 370/208, 370/210, 370/252, 370/335, 370/342, 370/343
• US Class Current: 370/208
• CPC Class Codes: H04B 17/336 Signal-to-interference ratio [SIR] or carrier-to-interference ratio [CIR]
• CPC Class Codes: H04L 1/20 using signal quality detector
• CPC Class Codes: H04L 27/2647 Arrangements specific to the receiver only equalisation H04L27/01

Abstract

A signal to interference-plus-noise power ratio (SINR) measurement method for wireless communications systems which employ orthogonal frequency division multiplexing (OFDM) for multicarrier data transmission is disclosed. Fast-Fourier transform (FFT)-based SINR measurements can be computed on frame-by-frame or greater interval for individual or groupings of subchannel signals. Given a known transmitted time-domain OFDM frame preamble, and the corresponding channel and interference-plus-noise (IPN) corrupted received time-domain frame preamble, the disclosed method first computes the power spectral densities of the received signal of interest and of a received unwanted interference-plus-noise signal. The FFT-computed power spectral densities are then used to compute average received signal and received IPN power measurements for specified individual or groupings of OFDM subchannel signals. The power measurements are then frame-averaged using a recursive exponential smoothing method. The frame-averaged signal and IPN power measurements are then used to form quantized measurements of SINR for the specified OFDM subchannel signals of the received frame.

Claims

1. In a frame-based communications system utilizing orthogonal frequency division multiplexing (OFDM) and OFDM frames for multicarrier data transmission, each transmitted OFDM frame constructed from multiple time-domain OFDM symbols, one of the OFDM symbols being a known OFDM preamble, a method for measuring a signal to interference-plus-noise power ratio (SINR) for selected OFDM subchannel signals within the multicarrier data transmission to indicate channel quality and to adaptively adjust groupings of the OFDM subchannel signals to increase network capacity, the method comprising the steps of:

computing a power spectral density (PSD) measurement vector S_yy[n] from an OFDM preamble y[n] received in an nth OFDM frame;

computing a PSD measurement vector S_xx[n] from an OFDM preamble x[n] transmitted in the nth OFDM frame;

computing a cross-PSD measurement vector S_xy[n] between x[n] and y[n] for the nth OFDM frame;

computing a PSD measurement vector S_SIG[n] for the nth OFDM frame using S_xx[n] and S_xy[n];

computing a PSD measurement vector S_IPN[n] for the nth OFDM frame using S_yy[n] and S_SIG[n];

specifying a subchannel grouping vector G[n] for the nth OFDM frame;

computing a received signal power measurement vector P_SIG[G[n]] for the subchannel grouping vector G[n] using S_SIG[n];

computing a received IPN power measurement vector P_IPN[G[n]] for the subchannel grouping vector G[n] using S_IPN[n]; and

computing a received SINR measurement vector ρ

[G[n]] for the subchannel grouping vector G[n] using P_SIG[G[n]] and P_IPN[G[n]].

2. The method as recited in claim 1, wherein the received signal power measurement vector P_SIG[G[n]] is computed as a frame-averaged received signal power measurement vector P_AVG—

_SIG[G[n]] for the subchannel grouping vector G[n].

3. The method as recited in claim 1, wherein the received IPN power measurement vector P_IPN[G[n] is computed as a frame-averaged received IPN power measurement vector P_AVG—

_IPN[G[n]] for the subchannel grouping vector G[n].

4. The method as recited in claim 1:

wherein the received signal power measurement vector P_SIG[G[n]] is computed as a frame-averaged received signal power measurement vector P<sub>AVG—

SIG</sub>[G[n]] for the subchannel grouping vector G[n]; and

wherein the received IPN power measurement vector P_IPN[G[n] is computed as a frame-averaged received IPN power measurement vector P<sub>AVG—

IPN</sub>[G[n]] for the subchannel grouping vector G[n].

5. The method as recited in claim 1, further comprising quantizing the received SINR measurement vector ρ

[G[n]].

6. The method as recited in claim 1, the step of computing a PSD measurement vector S_yy[n] comprising:

dividing the OFDM preamble y[n] into N_K overlapping vectors of length N_L;

applying a spectral window to each of the N_K overlapping vectors;

performing a length N Fast Fourier Transform (FFT) operation to each of the N_K overlapping vectors of length N_L to produce N_K first FFT vectors; and

computing a squared magnitude of each of the N_K first FFT vectors and averaging the squared magnitudes to produce S_yy[n].

7. The method as recited in claim 6, the step of computing a PSD measurement vector S_xx[n] comprising:

dividing the OFDM preamble x[n] into N_K overlapping vectors of length N_L;

applying a spectral window to each of the N_K overlapping vectors;

performing a length N Fast Fourier Transform (FFT) operation to each of the N_K overlapping vectors of length N_L to produce N_K second FFT vectors; and

computing a squared magnitude of each of the N_K second FFT vectors and averaging the squared magnitudes to produce S_xx[n].

8. The method as recited in claim 7, the step of computing a cross-PSD measurement vector S_xy[n] comprising:

multiplying complex conjugates of the N_K first FFT vectors and the complex conjugates of the N_K second FFT vectors together and averaging the multiplications to produce S_xy[n].

9. The method as recited in claim 1, the PSD measurement vector S_SIG[n] computed as S_SIG[n]={S_SIG[n,s], sε

S_N}, wherein S_N is a vector containing indices of N OFDM subchannels, s a subchannel number in S_N, and

$S_{\mathrm{SIG}}<br><br>\left[n,s\right]=\frac{{<br><br>S_{\mathrm{xy}}<br><br>\left[n,s\right]<br><br>}^2}{S_{\mathrm{xx}}<br><br>\left[n,s\right]}.$

10. The method as recited in claim 9, the PSD measurement vector S_IPN[n] computed as S_IPN[n]={S_IPN[n,s], sε

S_N}, wherein S_IPN[n,s]=S_yy[n,s]−

S_SIG[n,s].

11. The method as recited in claim 9, the received signal power measurement vector P_SIG[G[n]] computed as P_SIG[G[n]]={P_SIG[G_i[n]], i=0, . . . , r−

1}, wherein r denotes a number of subchannel groups, G_i[n] is an ith subchannel group in G[n],

$P_{\mathrm{SIG}}<br><br>\left[G_i<br><br>\left[n\right]\right]=10<br><br><br><br>{\log }_{10}<br><br>\left(\frac{1}{{\mathrm{NT}}_S}<br><br>\underset{s\in <br><br>G_i<br><br>\left[n\right]}{\overset{}{\sum <br><br>}}<br><br>S_{\mathrm{SIG}}<br><br>\left[n,s\right]\right),$

and T_s denotes an information source sampling time interval.

12. The method as recited in claim 10, the received IPN power measurement vector P_IPN[G[n]] computed as P_IPN[G[n]]={P_IPN[G_i[n]], i=0, . . . ,r−

1}, wherein r denotes a number of subchannel groups, G_i[n] is an ith subchannel group in G[n],

$P_{\mathrm{IPN}}<br><br>\left[G_i<br><br>\left[n\right]\right]=10<br><br><br><br>{\log }_{10}<br><br>\left(\frac{1}{{\mathrm{NT}}_S}<br><br>\underset{s\in <br><br>G_i<br><br>\left[n\right]}{\overset{}{\sum <br><br>}}<br><br>S_{\mathrm{IPN}}<br><br>\left[n,s\right]\right),$

and T_s denotes an information source sampling time interval.

13. The method as recited in claim 11, the received signal power measurement vector P_SIG[G[n]] computed as a frame-averaged received signal power measurement vector P_AVG—

_SIG[G[n]]={P<sub>AVG—

SIG</sub>[G_i[n]], i=0, . . . ,r−

1}, wherein P<sub>AVG—

SIG</sub>[G_i[n]]=P<sub>AVG—

SIG</sub>[G_i[n−

1]]+β

(P_SIG[G_i[n]]−

P_AVG[G_i[n−

1]]), and β

is a smoothing parameter.

14. The method as recited in claim 12, the received IPN power measurement vector P_IPN[G[n] computed as a frame-averaged received IPN power measurement vector P_AVG—

_IPN[G[n]]={P<sub>AVG—

IPN</sub>[G_i[n]], i=0, . . . ,r−

1}, wherein P<sub>AVG—

IPN</sub>[G_i[n]]=P<sub>AVG—

IPN</sub>[G_i[n−

1]]+α

(P_IPN[G_i[n ]]−

P<sub>AVG—

IPN</sub>G_i[n−

1]]), and a is a smoothing parameter.

15. The method as recited in claim 5, the received SINR measurement vector ρ

[G[n]] computed and quantized as vector ρ

[G[n]]={ρ

[G_i[n]], i=0, . . . ,r−

1}, wherein ρ

[G_i[n]]=Q(P<sub>AVG—

SIG</sub>[G_i[n]]−

P<sub>AVG—

IPN</sub>[G_i[n]]), and Q is a quantization function.

16. In a frame-based communications system utilizing orthogonal frequency division multiplexing (OFDM) and OFDM frames for multicarrier data transmission, each transmitted OFDM frame constructed from multiple time-domain OFDM symbols, one of the OFDM symbols being a known OFDM preamble, a signal to interference-plus-noise power ratio (SINR) apparatus for measuring the SINR of selected OFDM subchannel signals within the multicarrier data transmission to indicate channel quality and for adaptively adjusting groupings of the OFDM subchannel signals to increase network capacity, the SINR measurement apparatus comprising:

a processor programmed for

computing a power spectral density (PSD) measurement vector S_yy[n] from an OFDM preamble y[n] received in an nth OFDM frame,

computing a PSD measurement vector S_xx[n] from an OFDM preamble x[n] transmitted in the nth OFDM frame,

computing a cross-PSD measurement vector S_xy[n] between x[n] and y[n] for the nth OFDM frame,

computing a PSD measurement vector S_SIG[n] for the nth OFDM frame using S_xx[n] and S_xy[n],

computing a PSD measurement vector S_IPN[n] for the nth OFDM frame using S_yy[n] and S_SIG[n],

specifying a subchannel grouping vector G[n] for the nth OFDM frame,

computing a received signal power measurement vector P_SIG[G[n]] for the subchannel grouping vector G[n] using S_SIG[n],

computing a received IPN power measurement vector P_IPN[G[n]] for the subchannel grouping vector G[n] using S_IPN[n], and

computing a received SINR measurement vector ρ

[G[n]] for the subchannel grouping vector G[n] using P_SIG[G[n]] and P_IPN[G[n]].

17. The SINR measurement apparatus as recited in claim 16, wherein the processor is further programmed for computing the received signal power measurement vector P_SIG[G[n]] as a frame-averaged received signal power measurement vector P_AVG—

_SIG[G[n]] for the subchannel grouping vector G[n].

18. The SINR measurement apparatus as recited in claim 16, wherein the processor is further programmed for computing the received IPN power measurement vector P_IPN[G[n] as a frame-averaged received IPN power measurement vector P_AVG—

_IPN[G[n]] for the subchannel grouping vector G[n].

19. The SINR measurement apparatus as recited in claim 16, wherein the processor is further programmed for:

computing the received signal power measurement vector P_SIG[G[n]] as a frame-averaged received signal power measurement vector P<sub>AVG—

SIG</sub>[G[n]] for the subchannel grouping vector G[n]; and

computing the received IPN power measurement vector P_IPN[G[n] as a frame-averaged received IPN power measurement vector P<sub>AVG—

IPN</sub>[G[n]] for the subchannel grouping vector G[n].

20. The SINR measurement apparatus as recited in claim 16, the processor further programmed for quantizing the received SINR measurement vector ρ

[G[n]].

21. The SINR measurement apparatus as recited in claim 16, the processor further programmed for computing a PSD measurement vector S_yy[n] by:

dividing the OFDM preamble y[n] into N_K overlapping vectors of length N_L;

applying a spectral window to each of the N_K overlapping vectors;

performing a length N Fast Fourier Transform (FFT) operation to each of the N_K overlapping vectors of length N_L to produce N_K first FFT vectors; and

computing a squared magnitude of each of the N_K first FFT vectors and averaging the squared magnitudes to produce S_yy[n].

22. The SINR measurement apparatus as recited in claim 21, the processor further programmed for computing a PSD measurement vector S_xx[n] by:

dividing the OFDM preamble x[n] into N_K overlapping vectors of length N_L;

applying a spectral window to each of the N_K overlapping vectors;

performing a length N Fast Fourier Transform (FFT) operation to each of the N_K overlapping vectors of length N_L to produce N_K second FFT vectors; and

computing a squared magnitude of each of the N_K second FFT vectors and averaging the squared magnitudes to produce S_xx[n].

23. The SINR measurement apparatus as recited in claim 22, the processor further programmed for computing a cross-PSD measurement vector S_xy[n] by:

multiplying complex conjugates of the N_K first FFT vectors and the complex conjugates of the N_K second FFT vectors together and averaging the multiplications to produce S_xy[n].

24. The SINR measurement apparatus as recited in claim 16, the processor further programmed for computing the PSD measurement vector S_SIG[n] as S_SIG[n]={S_SIG[n,s], sε

S_N}, wherein S_N is a vector containing indices of N OFDM subchannels, s a subchannel number in S_N, and

$S_{\mathrm{SIG}}<br><br>\left[n,s\right]=\frac{{<br><br>S_{\mathrm{xy}}<br><br>\left[n,s\right]<br><br>}^2}{S_{\mathrm{xx}}<br><br>\left[n,s\right]}.$

25. The SINR measurement apparatus as recited in claim 24, the processor further programmed for computing the PSD measurement vector S_IPN[n] as S_IPN[n]={S_IPN[n,s], sε

S_N}, wherein S_IPN[n,s]=S_yy[n,s]−

S_SIG[n,s].

26. The SINR measurement apparatus as recited in claim 24, the processor further programmed for computing the received signal power measurement vector P_SIG[G[n]] as P_SIG[G[n]]={P_SIG[G_i[n]], i =0, . . . ,r−

1}, wherein r denotes a number of subchannel groups, G_i[n] is an ith subchannel group in G[n],

$P_{\mathrm{SIG}}<br><br>\left[G_i<br><br>\left[n\right]\right]=10<br><br><br><br>{\log }_{10}<br><br>\left(\frac{1}{{\mathrm{NT}}_S}<br><br>\underset{s<br><br>\in <br><br><br><br>G_i<br><br>\left[n\right]}{\sum <br><br>}<br><br>S_{\mathrm{SIG}}<br><br>\left[n,s\right]\right),$

and T_s denotes an information source sampling time interval.

27. The SINR measurement apparatus as recited in claim 25, the processor further programmed for computing the received IPN power measurement vector P_IPN[G[n]] as P_IPN[G[n]]={P_IPN[G_i[n]], i=0, . . . ,r−

1}, wherein r denotes a number of subchannel groups, G_i[n] is an ith subchannel group in G[n],

$P_{\mathrm{IPN}}<br><br>\left[G_i<br><br>\left[n\right]\right]=10<br><br><br><br>{\log }_{10}<br><br>\left(\frac{1}{{\mathrm{NT}}_S}<br><br>\underset{s<br><br>\in <br><br><br><br>G_i<br><br>\left[n\right]}{\sum <br><br>}<br><br>S_{\mathrm{IPN}}<br><br>\left[n,s\right]\right),$

and T_s denotes an information source sampling time interval.

28. The SINR measurement apparatus as recited in claim 26, the processor further programmed for computing the received signal power measurement vector P_SIG[G[n]] as a frame-averaged received signal power measurement vector P_AVG—

_SIG[G[n]]={P<sub>AVG—

SIG</sub>[G_i[n]], i=0, . . . ,r−

1}, wherein P<sub>AVG—

SIG</sub>[G_i[n]]=P<sub>AVG—

SIG</sub>[G_i[n−

1]]+β

(P_SIG[G_i[n ]]−

P<sub>AVG—

SIG</sub>[G_i[n−

1]]), and β

is a smoothing parameter.

29. The SINR measurement apparatus as recited in claim 27, the processor further programmed for computing the received IPN power measurement vector P_IPN[G[n] as a frame-averaged received IPN power measurement vector P_AVG—

_IPN[G[n]]={P<sub>AVG—

IPN</sub>[G_i[n]], i=0, . . . ,r−

1}, wherein P<sub>AVG—

IPN</sub>[G_i[n]]=P<sub>AVG—

IPN</sub>[G_i[n−

1]]+α

(P_IPN[G_i[n]]−

P<sub>AVG—

IPN</sub>[G_i[n−

1]]), and a is a smoothing parameter.

30. The SINR measurement apparatus as recited in claim 20, the processor further programmed for computing and quantizing the received SINR measurement vector ρ

[G[n]] as vector ρ

[G[n]]={ρ

[G_i[n]], i=0, . . . ,r−

1}, wherein ρ

[G_i[n]]=Q(P<sub>AVG—

SIG</sub>[G_i[n]]−

P<sub>AVG—

IPN</sub>[G_i[n]]), and Q is a quantization function.