METHOD AND APPARATUS FOR CONFIGURING A COMMUNICATION CHANNEL

• US 20090171874A1
• Filed: 08/17/2006
• Published: 07/02/2009
• Est. Priority Date: 08/19/2005
• Status: Active Grant

• Current Assignee: University Of Plymouth Enterprise Limited (University of Plymouth)
• Original Assignee: University of Plymouth Enterprise
• Inventors: Harris, Christopher
• Granted Patent: US 8,438,123 B2
• Time in Patent Office: Days
• US Class Current: 706/26
• CPC Class Codes: H04L 5/1438 Negotiation of transmission parameters prior to communication modified according to link quality H04L1/0001

Abstract

A method of configuring a communication channel prior to the transmission of an input signal along the communication channel, the communication channel comprising a plurality of sub-channels, the method comprising determining the strength of the input signal and in accordance with the determined signal strength, selecting a set of the plurality of sub-channels and transmitting said in put signal along the set of sub-channels in parallel, wherein each of the sub-channels has a predetermined noise characteristic such that the set of selected sub-channels exhibits a combined noise characteristic in which the standard deviation of the noise is proportional to the signal strength.

Claims

1. A method of configuring a communication channel prior to the transmission of an input signal along the communication channel, the communication channel comprising a plurality of sub-channels, the method comprising determining the strength of the input signal and in accordance with the determined signal strength, selecting a set of the plurality of sub-channels and transmitting said input signal along the set of sub-channels in parallel, wherein each of the sub-channels has a predetermined noise characteristic such that the set of selected sub-channels exhibits a combined noise characteristic in which the standard deviation of the noise is proportional to the input signal strength.

2. A method according to claim 1, wherein each sub-channel is selected only if the instantaneous input signal strength exceeds an individual threshold value associated with each sub-channel.

3. A method according to claim 1, wherein the noise characteristic of each sub-channel is defined by a gain function associated with each sub-channel and a constant weighting value w, applied to the output of each sub-channel.

4. A method according to claim 3, wherein for a given gain function the threshold value and weighting value for each sub-channel are selected such that the combined noise characteristic of the communication channel exhibits proportional noise.

5. A method according to claim 4, wherein the distribution of the weighting values w(x) and the distribution of sub-channels having a threshold value equal to the instantaneous signal strength ρ

(x) is given by solving the equations

$y=x={\int <br><br>}_0^{x_{\max }}<br><br>w<br><br>\left(x^{\mathrm{\prime <br><br>}}\right)<br><br>\mathrm{\rho <br><br>}<br><br>\left(x^{\mathrm{\prime <br><br>}}\right)<br><br>y_x<br><br>\left(x^{\mathrm{\prime <br><br>}}\right)<br><br><br><br>x$ $\mathrm{and}$ ${\mathrm{\sigma <br><br>}}^2=k^2<br><br>x^2={\int <br><br>}_0^{x_{\max }}<br><br>w^2<br><br>\left(x^{\mathrm{\prime <br><br>}}\right)<br><br>\mathrm{\rho <br><br>}<br><br>\left(x^{\mathrm{\prime <br><br>}}\right)<br><br>y_x<br><br>\left(x^{\mathrm{\prime <br><br>}}\right)<br><br><br><br>x^{\mathrm{\prime <br><br>}}$

where y is the instantaneous combined output signal value, σ

is standard deviation of the noise function and k is a constant of proportionality.

6. A method according to claim 4, wherein the threshold values and weighting values are selected by solving the equations

$y$

( x ) = ∑

i = 1 N 

w i 

f i 

( x - θ

i ) $\mathrm{and}$ ${\mathrm{\sigma <br><br>}}_y^2<br><br>\left(x\right)=\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>w_i^2<br><br>g_i<br><br>\left(x-{\mathrm{\theta <br><br>}}_i\right)$

where θ

_i is the threshold value for the ith sub-channel.

7. A method according to claim 5, wherein the equations are solved by numerical methods.

8. A method according to claim 3, wherein the gain function for each sub-channel comprises a step function, the input signal has a minimum instantaneous value ε

and the total number N of sub-channels is determined according to the equation

$N={\int <br><br>}_{\mathrm{\varepsilon <br><br>}}^{x_{\max }}<br><br>\mathrm{\rho <br><br>}<br><br>\left(x\right)<br><br><br><br>x.$

9. A method according to claim 3, wherein each sub-channel is arranged to simulate a neuron within a neural network such that the distribution of weighting values w(x) and the distribution of sub-channels having a threshold value equal to the instantaneous signal strength ρ

(x) is given by solving the equations

$w<br><br>\left(x\right)=\frac{2<br><br>k^2}{F}<br><br>\left(1/\mathrm{\alpha <br><br>}+x\right)$ $\mathrm{and}$ $\mathrm{\rho <br><br>}<br><br>\left(x\right)=\frac{F}{2<br><br><br><br>{\mathrm{Ak}}^2}<br><br>\left(\frac{1}{1/\mathrm{\alpha <br><br>}+x}\right)$

for x>

0, where k is a constant, F is the Fano number for the sub-channel renewal process, α

is a rise-time constant for the simulated neurons and A is the maximal firing rate for the simulated neurons.

10. Apparatus for configuring a communication channel comprising a plurality of sub-channels, each sub-channel having a threshold switch arranged to receive an input signal having an instantaneous signal value and to connect the sub-channel to the input signal only if the instantaneous signal value exceeds a predetermined threshold value, the apparatus further comprising a summator arranged to receive the output of each sub-channel and combine said outputs to provided a combined output signal, wherein each sub-channel has a predetermined noise characteristic such that the connected sub-channels exhibit a combined noise characteristic in which the standard deviation of the noise is proportional to the input signal strength.

11. Apparatus according to claim 10, wherein each sub-channel includes a constant gain unit arranged to apply a constant weighting value w_i to the output of each sub-channel prior to the output being provided to the summator and each sub-channel has a further gain function associated with it, such that the noise characteristic of each sub-channel is defined by said gain function and said constant weighting value w_i.

12. Apparatus according to claim 11, wherein the distribution of the weighting values w(x) and the distribution of sub-channels having a threshold value equal to the instantaneous signal strength ρ

(x) is given by the equations

$y=x={\int <br><br>}_0^{x_{\max }}<br><br>w<br><br>\left(x^{\mathrm{\prime <br><br>}}\right)<br><br>\mathrm{\rho <br><br>}<br><br>\left(x^{\mathrm{\prime <br><br>}}\right)<br><br>y_x<br><br>\left(x^{\mathrm{\prime <br><br>}}\right)<br><br><br><br>x$ $\mathrm{and}$ ${\mathrm{\sigma <br><br>}}^2=k^2<br><br>x^2={\int <br><br>}_0^{x_{\max }}<br><br>w^2<br><br>\left(x^{\mathrm{\prime <br><br>}}\right)<br><br>\mathrm{\rho <br><br>}<br><br>\left(x^{\mathrm{\prime <br><br>}}\right)<br><br>y_x<br><br>\left(x^{\mathrm{\prime <br><br>}}\right)<br><br><br><br>x^{\mathrm{\prime <br><br>}}$

where y is the instantaneous combined output signal value, σ

is standard deviation of the noise function and k is a constant of proportionality.

13. Apparatus according to claim 11, wherein the threshold values and weighting values are given by the equations

$y$

( x ) = ∑

i = 1 N 

w i 

f i 

( x - θ

i ) $\mathrm{and}$ ${\mathrm{\sigma <br><br>}}_y^2<br><br>\left(x\right)=\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>w_i^2<br><br>g_i<br><br>\left(x-{\mathrm{\theta <br><br>}}_i\right)$

where θ

_i is the threshold value for the ith sub-channel.

14. Apparatus according to claim 11, wherein the gain function for each sub-channel comprises a step function, the input signal has a minimum instantaneous value ε

and the total number N of sub-channels is determined according to the equation

$N={\int <br><br>}_{\mathrm{\varepsilon <br><br>}}^{x_{\max }}<br><br>\mathrm{\rho <br><br>}<br><br>\left(x\right)<br><br><br><br>x.$

15. Apparatus according to claim 11, wherein each sub-channel is arranged to simulate a neuron within a neural network such that the distribution of weighting values w(x) and the distribution of sub-channels having a threshold value equal to the instantaneous signal strength ρ

(x) is given by solving the equations

$w<br><br>\left(x\right)=\frac{2<br><br>k^2}{F}<br><br>\left(1/\mathrm{\alpha <br><br>}+x\right)$ $\mathrm{and}$ $\mathrm{\rho <br><br>}<br><br>\left(x\right)=\frac{F}{2<br><br><br><br>{\mathrm{Ak}}^2}<br><br>\left(\frac{1}{1/\mathrm{\alpha <br><br>}+x}\right)$

for x>

0, where k is a constant, F is the Fano number for the sub-channel renewal process, α

is a rise-time constant for the simulated neurons and A is the maximal firing rate for the simulated neurons.