Real-time system for measuring the ricean K-factor

• US 20020027951A1
• Filed: 02/06/2001
• Published: 03/07/2002
• Est. Priority Date: 02/08/2000
• Status: Active Grant

• Current Assignee: Clearwire Ip Holdings LLC (Deutsche Telekom AG)
• Original Assignee: Clearwire Corporation (Deutsche Telekom AG)
• Inventors: Gormley, Eamonn, Rodriguez-Sanchez, Jose
• Granted Patent: US 6,868,120 B2
• Time in Patent Office: Days
• US Class Current: 375/224
• CPC Class Codes: H04B 17/309 Measuring or estimating channel quality parameters
• CPC Class Codes: H04B 7/005 Control of transmission; Equalising

Abstract

A system and method for measuring the Ricean K-factor of a wireless channel in real time. An amplitude sample of a transmitted RF waveform of either fixed or varying amplitude is low-pass filtered to eliminate high frequency noise if present. The magnitude squared of the filtered sample amplitude is squared to obtain the power gain of the sample and the magnitude squared of the power gain is computed. The sums of a window of power gains and the sum of the squares of the power gains are then updated. These sums of the window of amplitude samples are then averaged to estimate the first and second moments of the window of samples. The averages are low-pass filtered to minimize fluctuations. The final average is input to a moment-based set of Greenstein-Michelson-Erceg (GME) equations to obtain estimates for the time average of the power gain and rms deviation of the power gain. The K-factor is calculated in accordance these equations and low-pass filtered to smooth the result.

Claims

1. A method for measuring the Ricean K-factor of a wireless channel in real-time, comprising the steps of:

(a) obtaining an amplitude sample;

(b) computing the magnitude squared of the sample to obtain the power gain and computing the magnitude squared of the power gain;

(c) calculating the sum of the power gain and the magnitude squared of the power gain for a window of amplitude samples;

(d) final averaging the sums of the window of amplitude samples to estimate the first and second moments of the window of samples;

(e) inputing the final average to obtain estimates for the time average of the power gain Ga and rms deviation of the power gain Gv about Ga;

$\begin{array}{cc}{\hat{G}}_a=\frac{1}{N}<br><br>\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>x_i<br><br><br><br>\mathrm{and},& \text{\hspace{1em}<br><br>}\\ {\hat{G}}_v=\frac{1}{N}<br><br>\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>x_i^2-{\hat{G}}_a^2;<br><br>\mathrm{and}& \text{\hspace{1em}<br><br>}\end{array}$

(f) computing the K-factor in accordance with;

$K=\frac{\sqrt{G_a^2-G_v^2}}{G_a-\sqrt{G_a^2-G_v^2}}.$

2. The method for measuring the Ricean K-factor of a wireless channel in real-time recited in claim 1, further comprising the step of normalizing the incoming amplitude sample.

3. The method for measuring the Ricean K-factor of a wireless channel in real-time recited in claim 1, further comprising the steps of low pass filtering the amplitude sample prior to obtaining the power gain and computing the magnitude squared of the power gain, and low-pass filtering the estimates of first and second moments of the window of samples.

4. The method for measuring the Ricean K-factor of a wireless channel in real-time recited in claim 1, further comprising the step of low-pass filtering the computed K-factor.

5. The method for measuring the Ricean K-factor of a wireless channel in real time recited in claim 1, wherein the window of samples ranges from 2000-10,000.

6. A method for measuring the Ricean K-factor of a wireless channel in real-time, comprising the steps of:

(a) normalizing an incoming amplitude sample;

(b) low-pass filtering the amplitude sample;

(c) computing the magnitude squared of the sample to obtain the power gain and computing the magnitude squared of the power gain

(d) calculating the sum of the power gain and the magnitude squared of the power gain for a window of amplitude samples;

(e) final averaging the sums of the window of amplitude samples to estimate the first and second moments of the window of samples;

(f) low-pass filtering the averages of the sums of the window of amplitude samples;

(g) inputing the final average to obtain estimates for the time average of the power gain Ga and rms deviation of the power gain Gv about Ga;

$\begin{array}{cc}{\hat{G}}_a=\frac{1}{N}<br><br>\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>x_i<br><br><br><br>\mathrm{and},& \text{\hspace{1em}<br><br>}\\ {\hat{G}}_v=\frac{1}{N}<br><br>\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>x_i^2-{\hat{G}}_a^2;<br><br>& \text{\hspace{1em}<br><br>}\end{array}$

(h) computing the K-factor in accordance with;

$K=\frac{\sqrt{G_a^2-G_v^2}}{G_a-\sqrt{G_a^2-G_v^2}};<br><br>\mathrm{and}$

(i) low-pass filtering the computed K-factor.