Filter structure for iterative signal processing

• US 20040264561A1
• Filed: 07/23/2004
• Published: 12/30/2004
• Est. Priority Date: 05/02/2002
• Status: Active Grant

• Current Assignee: Cohda Wireless Pty Ltd., University of South Australia (University of Adelaide)
• Original Assignee: Cohda Wireless Pty Ltd., University of South Australia (University of Adelaide)
• Inventors: Jakas, Stephen Peter, Rasmussen, Lars Kildehoj, Alexander, Paul Dean, Grant, Alexander James
• Granted Patent: US 7,486,726 B2
• Time in Patent Office: Days
• US Class Current: 375/232
• CPC Class Codes: H04L 25/0202 Channel estimation
• CPC Class Codes: H04L 25/0204 of multiple channels
• CPC Class Codes: H04L 25/03171 Arrangements involving maximum a posteriori probability [MAP] detection
• CPC Class Codes: H04L 27/2657 Carrier synchronisation
• CPC Class Codes: H04L 27/2662 Symbol synchronisation
• CPC Class Codes: H04L 27/2675 Pilot or known symbols

Abstract

The present invention relates to improved multiple access communications. In one form, the invention relates to an improved signal processing method and apparatus for an iterative method of determining the reception of a signal in a multi user packet based wireless OFDM (Orthogonal Frequency Division Multiplexing) communication system. In other forms the present invention provides recursive filtering for joint iterative decoding in a variety of systems and functions such as linear multiple access channel decoders, iterative equalisation, iterative joint channel estimation and detection/decoding, iterative space-time processing, iterative multi user interference cancellation and iterative demodulation. In one particular form the present invention provides an iterative decoding circuit for a wireless multiuser communications receiver comprising a first signal processing means for receiving at least one received signal, said first signal processing means comprising at least two linear iterative filters such that the first linear iterative filter provides an estimate of a selected received signal to an estimated signal output and a second linear iterative filter provides estimates of at least one other received signal, delayed by one iteration cycle, to an input of said first linear iterative filter, a second signal processing means for receiving the estimated signal output of the first linear iterative filter and providing a further received signal estimate to the input of the first signal processing means in a succeeding iteration cycle of the decoding circuit.

Claims

1. An iterative signal processing arrangement having:

one or more pairs of first and second signal processing components, the pairs of components being in iterative configuration, each of the first signal processing components having as input one or more received signals dependent upon one or more transmitted signals, wherein for each said signal processing component pair the output of said first signal processing component is an estimate of a characteristic of a selected transmitted signal based on the current and one or more previous input signals received by said first signal processing component, which is input to said corresponding second signal processing component that provides a further estimate of said selected transmitted signal to the output of said second signal processing component, the outputs of all said second signal processing components of respective pairs are input to each said first signal processing components of all said pairs in a succeeding iteration cycle.

2. An iterative signal processing arrangement according to claim 1, wherein said first signal processing components consists of:

at least two linear iterative filters wherein

a first of said linear iterative filters outputs an estimate of a selected characteristic of a selected one of said transmitted signals to said second signal processing component, and

a second or said iterative filters having the same inputs as said first linear iterative filter provides an estimate of a characteristic of a selected of one or more transmitted signals and then delays by one iteration cycle said estimate and outputs said delayed estimate to an input of said first linear iterative filter.

3. An iterative signal processing arrangement according to claim 2, wherein said first linear iterative filter provides a minimum least squared estimate of said selected transmitted signal subject to predetermined statistical models of said signals.

4. An iterative signal processing arrangement according to claim 2, wherein said second linear iterative filter provides a minimum least squared estimate of said selected transmitted signal subject to predetermined statistical models of said signals.

5. An iterative signal processing arrangement according to claim 2, wherein said first and second linear iterative filters provide a minimum least squared estimate of said selected transmitted signal subject to predetermined statistical models of said signals.

6. An iterative signal processing arrangement according to claim 5, wherein said first and second linear iterative filters further consist of a switch the input of which at a first iteration is all received signals, and the input for subsequent iterations is the output of all second signal processing components wherein the output of said switch is input to a first summing device, and said first linear iterative filter receives as input the output of said first summing device which is input to a filter having taps that are recursively updated based on receiving one or more said received signals, the output of said first linear iterative filter is input to a second summing device the output of which becomes the output of said first signal processing component as well as being input to a first single iteration delay device the output of which is input to said second summing device, while said second linear iterative filter receives as input the output of said first summing device which is input to a second linear iterative filter having taps which are recursively updated based on receiving one or more said received signals the output of said second linear iterative filter is input to a third summing device the output of which is input to a second single iteration delay device, the output of which is input to said third summing device, the output of which is negated and input to said first summing device.

7. An iterative signal processing arrangement according to claim 6, wherein said filters in said first and a second linear iterative filters are of the type that conform to the following mathematical expression using the following assumptions,

A1:

The received signal is described as r=Sx+n, where S is the constraint matrix, containing all the linear channel constraints, x is a vector containing all transmitted information symbols and n is circularly symmetric complex Gaussian with covariance matrix covn=σ

²I, and where the noise variance σ

² and the constraint matrix S are known.

A2;

The interleaved code symbol estimates of the interfering users {circumflex over (x)}_k⁽ⁿ⁾ which is a vector containing all the signal estimates at iteration n for all users except user k, coming out of said corresponding signal processing component 2 can be modelled as {circumflex over (x)}_k⁽ⁿ)=x_k+{circumflex over (v)}_k⁽ⁿ⁾ where x_k is the transmitted symbol for user k and {circumflex over (v)}_k⁽ⁿ⁾ is the corresponding estimated noise sample which is uncorrelated with x, which is a vector containing the transmitted symbols for all users, and also uncorrelated over time and iterations, but not over users at a given iteration, that is <

x, {circumflex over (v)}_k⁽ⁿ⁾>

=0, <

{circumflex over (v)}_k⁽ⁿ⁾, {circumflex over (v)}_k⁽ⁿ⁾>

=0 for n≠

m, where n and m denote different iteration numbers, and the estimated noise correlation for user k and j at iteration n is defined as <

{circumflex over (v)}_k⁽ⁿ⁾, {circumflex over (v)}_j⁽ⁿ⁾>

=q_kj.

Define the estimated noise covariance matrix Q_k⁽ⁿ⁾=<

{circumflex over (v)}_k⁽ⁿ⁾, {circumflex over (v)}_{{overscore (k)}}⁽ⁿ⁾>

, with elements determined as shown above.

Let c_k⁽ⁿ⁾ be the auxiliary vector that contains all signals received from user k at iteration n and all previous iterations, according to the following recursively defined vector of observables as input to the said linear iterative filter denoted by Λ

_k⁽ⁿ⁾,

$c_k^{\left(n\right)}=\{\begin{array}{cc}r& n=1\\ \left(\begin{array}{c}{c}_k^{\left(n-1\right)}\\ {\hat{x}}_k^{\left(n-1\right)}\end{array}\right)& n=2,3,\mathrm{\dots <br><br>}\end{array}$

Under A1 and A2, the linear minimum mean square error estimate of said signal x_k given sad signal c_k⁽ⁿ⁾ is given by the output x_k⁽ⁿ⁾ of the recursive filter which is an updated estimate of the transmitted signal for user k at iteration n, defined as follows.

m_k⁽ⁿ⁾=−

w_k⁽ⁿ⁾(I+Q_k<sup>(n−

1)</sup>−

W_k⁽ⁿ⁾)<sup>−

1</sup> M_k⁽ⁿ⁾=(I−

W₂⁽ⁿ⁾)(I+Q_k<sup>(n−

1)</sup>−

W_k⁽ⁿ⁾)<sup>−

1</sup>

where for user k at iteration n m_k⁽ⁿ⁾ is the said first linear iterative filter, M_k⁽ⁿ⁾ is the said second linear iterative filter, I is an identity matrix with ones on the diagonal and zeros everywhere else, w_k⁽ⁿ⁾ is a recursive, complex auxiliary vector and W_k⁽ⁿ⁾ is a first recursive, complex auxiliary matrix, respectively, the recursive update equations for n=3,4, . . . are as follows;

w_k⁽ⁿ⁾=w_k<sup>(n−

1)</sup>[I−

(H_k<sup>(n−

1</sup>)<sup>−

1</sup>(I−

W_k<sup>(n−

1)</sup>)]<sup>−

1</sup> W_k⁽ⁿ⁾=W_k<sup>(n−

1)</sup>+(I−

W_k<sup>(n−

1)</sup>)(H_k<sup>(n−

1)</sup>)<sup>−

1</sup>(I−

W_k<sup>(n−

1)</sup>) H_k<sup>(n−

1)</sup>−

I+Q_k<sup>(n−

2)</sup>−

W_k<sup>(n−

1)</sup>

where H_k<sup>(n−

1)</sup> is a second recursive, complex auxiliary matrix. The initial conditions with x_k⁽⁰⁾=0 and x_k⁽⁰⁾=0 are m_k⁽¹⁾=s_k^t(SS^t+σ

²I)<sup>−

1</sup>, M_k⁽¹⁾=S_{{overscore (k)}}^t(SS^t+σ

²I)<sup>−

1</sup> for n=1 and w_k⁽²⁾=s_k^t(SS^t+I)<sup>−

1</sup>S_{{overscore (k)}}, W_k⁽²⁾=S_{{overscore (k)}}^t(SS^t+σ

²I)<sup>−

1</sup>S_{{overscore (k)}} for n=2, where s_k is the linear constraint for user k, s_k^t denotes the complex conjugate transpose of said vector s_k,S_{{overscore (k)}} is the constraint matrix with column k deleted and S_{{overscore (k)}} denotes the complex conjugate transpose of vector S_{{overscore (k)}}.

8. An iterative filter arrangement according to claim 1, wherein the output of said first signal processing component is de-interleaved and the output of said second signal processing component is interleaved.

9. An iterative signal processing arrangement according to claim 1, wherein the characteristic of a selected transmitted signal is a discrete time series representation of a said selected transmitted signal and where the output of said first signal processing component is a minimum least squared estimate of said selected transmitted signal subject to predetermined statistical models of said signals.

10. An iterative signal processing arrangement according to claim 2, wherein said first and second linear iterative filters provide a minimum least squared estimate of said selected transmitted signal subject to different predetermined statistical models of said signals.

11. An iterative decoding circuit for a wireless multiuser communications receiver comprising:

a first signal processing means for receiving at least one received signal, said first signal processing means comprising at least two linear iterative filters such that;

the first linear iterative filter provides an estimate of a selected received signal to an estimated signal output and;

a second linear iterative filter provides estimates of at least one other received signal, delayed by one iteration cycle, to an input of said first linear iterative filter;

a second signal processing means for receiving the estimated signal output of the first linear iterative filter and providing a further received signal estimate to the input of the first signal processing means in a succeeding iteration cycle of the decoding circuit.

12. An iterative decoding circuit according to claim 11 wherein the linear filters function in accordance with at least one predetermined recursive Bayesian expression.

13. An iterative decoding circuit according to claim 12 wherein the predetermined recursive expression comprises the following recursive Bayesian estimation using the following assumptions:

A1;

The received signal is described as r=Sx+n, where S is the constraint matrix, containing all the linear channel constraints, x is a vector containing all transmitted information symbols and n is circularly symmetric complex Gaussian with covariance matrix covn=σ

²I, and where the noise variance σ

² and the constraint matrix S are known.

A2;

The interleaved code symbol estimates of the interfering users {circumflex over (x)}_{{overscore (k)}}⁽ⁿ⁾ which is a vector containing all the signal estimates at iteration n for all users except user k, coming out of said corresponding signal processing component 2 can be modelled as {circumflex over (x)}_k⁽ⁿ⁾=k_k+{circumflex over (v)}_k⁽ⁿ⁾ where x_k is the transmitted symbol for user k and {circumflex over (v)}_k⁽ⁿ⁾ is the corresponding estimated noise sample which is uncorrelated with x, which is a vector containing the transmitted symbols for all users, and also uncorrelated over time and iterations, but not over users at a given iteration, that is <

x, {circumflex over (v)}_k⁽ⁿ⁾>

=0, <

{circumflex over (v)}_k⁽ⁿ⁾, {circumflex over (v)}_k^(m)>

=0 for m≠

m, where n and m denote different iteration numbers, and the estimated noise correlation for user k and j at iteration n is defined as <

{circumflex over (v)}_k⁽ⁿ⁾, {circumflex over (v)}_j⁽ⁿ⁾>

=q_kj.

Define the estimated noise covariance matrix Q_k⁽ⁿ⁾=<

{circumflex over (v)}_{{overscore (k)}}⁽ⁿ⁾, {circumflex over (v)}_{{overscore (k)}}⁽ⁿ⁾>

, with elements determined as shown above.

Let c_k⁽ⁿ⁾ be the auxiliary vector that contains all signals received from user k at iteration n and all previous iterations, according to the following recursively defined vector of observables as input to the said linear iterative filter denoted by Λ

_k⁽ⁿ⁾,

$c_k^{\left(n\right)}=\{\begin{array}{cc}r& n=1\\ \left(\begin{array}{c}{c}_k^{\left(n-1\right)}\\ {\hat{x}}_k^{\left(n-1\right)}\end{array}\right)& n=2,3,\mathrm{\dots <br><br>}\end{array}$

Under A1 and A2, the linear minimum mean square error estimate of said signal x_k given said signal c_k⁽ⁿ⁾ is given by the output {tilde over (x)}_k⁽ⁿ⁾ of the recursive filter which is an updated estimate of the transmitted signal for user k at iteration n, defined as follows.

${\tilde{x}}_k^{\left(n\right)}={{{\tilde{x}}_k^{\left(n-1\right)}+\text{\hspace{1em}<br><br>}<br><br>{.}_{\text{\hspace{1em}<br><br>}<br><br>k}^{\text{\hspace{1em}<br><br>}<br><br>\left(n\right)}<br><br>\left({{.}^{^}}_{\stackrel{\_}{k}}^{\left(n-1\right)}<br><br>-\text{\hspace{1em}<br><br>}<br><br>{{.}^{~}}_{\stackrel{\_}{k}}^{\left(n-1\right)}\right)<br><br><br><br>{{.}^{~}}_{\stackrel{\_}{k}}^{\left(n\right)}=.<br><br>\text{\hspace{1em}<br><br>}}^{~\text{\hspace{1em}<br><br>}}<br><br>\text{\hspace{1em}<br><br>}}_{\stackrel{\_}{k}}^{\left(n-1\right)}+\text{\hspace{1em}<br><br>}<br><br>{.}_{\text{\hspace{1em}<br><br>}<br><br>k}^{\text{\hspace{1em}<br><br>}<br><br>\left(n\right)}<br><br>\left({{.}^{^}}_{\stackrel{\_}{k}}^{\left(n-1\right)}<br><br>-\text{\hspace{1em}<br><br>}<br><br>{{.}^{~}}_{\stackrel{\_}{k}}^{\left(n-1\right)}\right)$m_k⁽ⁿ⁾=−

w_k⁽ⁿ⁾(I+Q_k<sup>(n−

1)</sup>−

W_k⁽ⁿ⁾)<sup>−

1</sup> M_k⁽ⁿ⁾=(I−

W_k⁽ⁿ⁾)(I+Q_k<sup>(n−

1)</sup>−

W_k⁽ⁿ⁾)<sup>−

1</sup>

where for user k at iteration n m_k⁽ⁿ⁾ is the said first linear iterative filter, M_k⁽ⁿ⁾ is the said second linear iterative filter, I is an identity matrix with ones on the diagonal and zeros everywhere else, w_k⁽ⁿ⁾ is a recursive, complex auxiliary vector and W_k⁽ⁿ⁾ is a first recursive, complex auxiliary matrix, respectively, the recursive update equations for n=3,4, . . . are as follows;

w_k⁽ⁿ⁾=w_k<sup>(n−

1)</sup>[I−

(H_k<sup>(n−

1</sup>)<sup>−

1</sup>(I−

W_k<sup>(n−

1)</sup>)]<sup>−

1</sup> W_k⁽ⁿ⁾=W_k<sup>(n−

1)</sup>+(I−

W_k<sup>(n−

1)</sup>)(H_k<sup>(n−

1)</sup>)<sup>−

1</sup>(I−

W_k<sup>(n−

1)</sup>) H_k<sup>(n−

1)</sup>−

I+Q_k<sup>(n−

2)</sup>−

W_k<sup>(n−

1)</sup>

where H_k<sup>(n−

1)</sup> is a second recursive, complex auxiliary matrix. The initial conditions with {tilde over (x)}_k⁽⁰⁾=0 and

${.}_{\stackrel{\_}{k}}^{\left(0\right)}=.$

 

are m_k⁽¹⁾=s_k^t(SS^t+σ

²I)<sup>−

1</sup>,

$M_k^{\left(1\right)}={S_{\stackrel{\_}{k}}^t<br><br>\left({\mathrm{SS}}^t+{\mathrm{\sigma <br><br>}}^2<br><br>I\right)}^{-1}$

 

for n=1 and w_k⁽²⁾=s_k^t(SS^t+I)<sup>−

1</sup>S_{{overscore (k)}},

$W_k^{\left(2\right)}={S_{\stackrel{\_}{k}}^t<br><br>\left({\mathrm{SS}}^t+{\mathrm{\sigma <br><br>}}^2<br><br>I\right)}^{-1}<br><br>S_{\stackrel{\_}{k}}$

 

for n=2, where s_k is the linear constraint for user k, S_k^t denotes the complex conjugate transpose of said vector s_k, S_{{overscore (k)}} is the constraint matrix with column k deleted and S_{{overscore (k)}} denotes the complex conjugate transpose of vector S_{{overscore (k)}}.

14. A method of communicating in a multiple access network by iteratively receiving multi user signals the method comprising the steps of:

determining a first set of signal estimates for the multi user signals based on linear channel constraints;

determining a second set of signal estimates based on non-linear channel constraints and the first set of signal estimates;

providing the second set of signal estimates as input to the step of determining the first set of signal estimates;

repeating the above steps at least once.

15. An iterative receiver for receiving multi user signals comprising:

a first signal processing component for determining a first set of signal estimates for the multi user signals based on linear channel constraints;

a second signal processing component for receiving the first set of signal estimates and determining a second set of signal estimates based on non-linear channel constraints;

wherein the signal processing components are operatively connected so as to provide the second set of signal estimates as input to the first signal processing component in a succeeding iteration cycle.

16. A method of communicating in a multiple access network by iteratively receiving OFDM packets the method comprising the following steps:

a) sample a receiver input signal consisting of signals from one or more antenna;

b) add the input signal with one of a plurality of prior stored received packet sample estimates to determine a packet sample hypothesis;

c) determine an information bit estimate from the sample hypothesis for storage in an information bit estimates list;

d) determine an updated received packet sample estimate from the sample hypothesis for updating the plurality of prior stored estimates;

e) subtract the updated sample estimate from the sample hypothesis to determine a noise hypothesis and provide the noise hypothesis as the receiver input signal;

f) repeat steps a) to e) until at least one or more complete packets are accumulated in the information bit estimates list.

17. A method of communicating in a multiple access network by iteratively providing a sample estimates list in an OFDM receiver the method comprising the following steps:

a) sample a receiver input signal;

b) determine a packet sample estimate from the sampled receiver input signal;

c) store the packet sample estimate;

d) determine a packet sample hypothesis by adding the receiver input with a selected previously stored packet sample estimate;

e) determine an updated packet sample estimate by decoding and re-transmission modelling the packet sample hypothesis;

f) update the selected previously stored packet sample estimate with the updated packet sample estimate.

18. A method of communicating in a multiple access network by iteratively providing a packet information bit estimates list in an OFDM receiver the method comprising the following steps:

a) determine a packet sample hypothesis by adding a receiver input with a selected previously stored packet sample estimate;

b) determine an information bit estimate by decoding the packet sample hypothesis with one or more of a hard decoding technique and a soft decoding technique

c) storing the information bit estimate with one or more previously determined information bit estimates;

d) repeating steps a) to c) until a complete packet is accumulated.

19. A method of communicating in a multiple access network including determining a hybrid OFDM received packet sample estimate the method comprising the step of:

multiplexing a time domain channel application received sample estimate with a frequency domain channel application received sample estimate, such that the multiplexed time domain sample estimate is mapped to correspond to one or more of;

an OFDM signal cyclic prefix;

an OFDM tail portion, and;

an OFDM guard period,

and wherein the multiplexed frequency domain sample estimate is mapped to correspond to one or more of;

an OFDM signal preamble and;

an OFDM payload data symbol.

20. A method of communicating in an OFDM multiple access network comprising the step of:

performing multi-user interference cancelling which comprises adapting a single pass OFDM receiver to iteratively receive signals at the sampling level so as to allow the receiver to differentiate a desired packet from an observation of an interference signal at the receiver input.

21. A method of communicating in a multiple access communication network by synchronizing packets arriving at a receiver the method comprising the steps of:

receiving a packet input signal;

determining a correlation signal corresponding to the packet input signal;

processing the input and correlation signals such that at least one of the input signal and the correlation signal are filtered;

determining a decision statistic by combining a power component of the processed correlation signal with a power component of the processed input signal;

nominate a point in time given by a predetermined threshold condition of the decision statistic as a received packet arrival time.

22. A method according to claim 21 wherein the step of processing at least one of the input and correlation signals is performed by one of:

a center weighted filter having a triangular impulse response;

a root raised cosine filter;

a Hanning window filter;

a Hamming window filter;

a combined Hanning/Hamming window filter.

23. A method according to claim 21, wherein the predetermined threshold condition is one of:

the decision statistic crossing the predetermined threshold and;

a maximum of the decision statistic occurring above the predetermined threshold.

24. A method according to claim 21, wherein the step of determining the correlation signal is performed every Kth sample of a sampled packet input signal, where K is an integer greater than or equal to 1.

25. A method of communicating by tracking time varying channels in a multiple access packet based communication network the method comprising the steps of:

a) initializing a channel estimate reference based on an initial channel estimate derived from a received packet preamble;

b) updating the channel estimate reference based on a packet data symbol channel estimate in a coded portion of the current and all previously received data symbols;

c) repeating step b) at the arrival of subsequent packet data symbols.

26. A method according to claim 25 further comprising the step of:

storing the channel estimate reference in a channel estimate data base at the receiver.

27. A method according to claim 25, further comprising the step of:

transforming the packet data symbol channel estimates to the frequency domain prior to updating the stored channel estimate reference to provide a time smoothed channel estimate reference.

28. A method according to claim 25 wherein the method further comprises the steps of:

for each subsequent received data symbol within step b), pipelining the steps of demodulating and modulating, and;

updating the channel estimate reference with the further step of FEC decoding.

29. A method of communicating by estimating time varying channel impairments in a multiple access packet based communication network, where channel impairments comprise channel variation, signal frequency offset and signal time offset, the method comprising the steps of:

a) initializing a set of channel impairment estimates based on initial pilot and preamble symbols included in a received packet;

b) performing a decoder operation which comprises processing the set of channel impairment estimates and the received packet to determine a set of transmit symbol estimates;

c) updating the set of channel impairment estimates with the determined set of symbol estimates and the received packet;

d) repeating steps b) and c).

30. A method of communicating in a multiple access network by time varying channel estimation in a receiver for receiving transmitted packets, the method comprising the steps of:

a) estimating a frequency offset based on information included in a received packet preamble;

b) correcting a received signal using the estimated frequency offset;

c) determining a channel estimate using information included in the received packet preamble;

d) transforming a sample sequence of the received signal into the frequency domain such that the sample sequence includes OFDM symbols and intervening cyclic prefixes;

e) performing a decoding operation which comprises processing the determined channel estimate and received packet;

f) generating a transmission sample sequence using the decoding results and information in the received packet preamble;

g) transforming the transmission sample sequence into the frequency domain;

h) updating the determined channel estimate by combining the received sample sequence and the transmission sample sequence in the frequency domain;

i) repeating steps e) to h).

31. A method of communicating in a multiple access network by time varying channel estimation in a receiver for receiving transmitted packets, where the receiver retrieves OFDM symbols from a received signal and transforms the retrieved symbols to the frequency domain, the method comprising the steps of:

a) determine a matrix of training symbols comprised of symbol estimates derived from a decoder;

b) determine a matrix of frequency domain received OFDM symbols;

c) determine an intermediate channel estimate matrix by multiplying the OFDM symbol matrix by the conjugate of the training symbol matrix;

d) determine an intermediate matrix of training weights comprising the absolute value of the training symbol matrix;

e) perform a smoothing operation on both intermediate matrices comprising 2 dimensional filtering;

f) determine the channel estimate by dividing the smoothed channel estimate matrix with the smoothed training weight matrix.

32. A method of communicating in a multiple access network by estimating offsets in a receiver for receiving transmitted packets, the method comprising the steps of:

a) determine a matrix of frequency domain received OFDM symbols;

b) determine a matrix of conjugated data symbols wherein the data symbols comprise one or more of preamble, training and estimated symbols;

c) determine a 2 dimensional Fourier transform matrix comprised of the received symbol matrix multiplied with the conjugated symbol matrix;

d) filter the Fourier transform matrix;

e) determine time and frequency offsets by locating peak power occurrences within the filtered Fourier transform.

33. A method of communicating in a multiple access packet communication network by synchronizing a received signal in a multi antenna receiver the method comprising:

correlating a received signal observation at each of a plurality of antennae with a known signal preamble to provide a received signal sequence;

determine a power signal of each received signal sequence;

combine the determined power signals in accordance with a time averaged weighting based on estimated antenna signal strength for each antenna;

determine a time of arrival for the received signal in accordance with a predetermined threshold condition.

34. A method according to claim 33 further comprising the steps of:

determining an estimate of the relative phase and amplitude coefficients of a receiving channel for each antenna;

combining a received signal with the estimated coefficients to provide a composite signal;

determining a time of arrival of the received signal by correlating the composite signal with a delayed version of itself.

35. Apparatus adapted to communicate in a multiple access communication network, said apparatus comprising:

processor means adapted to operate in accordance with a predetermined instruction set,

said apparatus, in conjunction with said instruction set, being adapted to perform a method of communicating in a multiple access network by iteratively receiving multi user signals, the method comprising the steps of;

determining a first set of signal estimates for the multi user signals based on linear channel constraints;

determining a second set of signal estimates based on non-linear channel constraints and the first set of signal estimates;

providing the second set of signal estimates as input to the step of determining the first set of signal estimates;

repeating the above steps at least once.

36. Apparatus adapted to communicate in a multiple access communication network, said apparatus comprising:

processor means adapted to operate in accordance with a predetermined instruction set, said apparatus, in conjunction with said instruction set, being adapted to perform a method of communicating in a multiple access network by iteratively receiving OFDM packets, the method comprising the following steps;

g) sample a receiver input signal consisting of signals from one or more antenna;

h) add the input signal with one of a plurality of prior stored received packet sample estimates to determine a packet sample hypothesis;

i) determine an information bit estimate from the sample hypothesis for storage in an information bit estimates list;

j) determine an updated received packet sample estimate from the sample hypothesis for updating the plurality of prior stored estimates;

k) subtract the updated sample estimate from the sample hypothesis to determine a noise hypothesis and provide the noise hypothesis as the receiver input signal;

l) repeat steps a) to e) until at least one or more complete packets are accumulated in the information bit estimates list.

37. A computer program product comprising:

a computer usable medium having computer readable program code and computer readable system code embodied on said medium for communicating in a multiple access communication network, said computer program product comprising;

computer readable code within said computer usable medium for performing the method steps of a method of communicating in a multiple access network by iteratively receiving multi user signals, the method comprising the steps of;

determining a first set of signal estimates for the multi user signals based on linear channel constraints;

determining a second set of signal estimates based on non-linear channel constraints and the first set of signal estimates;

providing the second set of signal estimates as input to the step of determining the first set of signal estimates;

repeating the above steps at least once.

38. A computer program product comprising:

a computer usable medium having computer readable program code and computer readable system code embodied on said medium for communicating in a multiple access communication network, said computer program product comprising;

computer readable code within said computer usable medium for performing the method steps of a method of communicating in a multiple access network by iteratively receiving OFDM packets, the method comprising the following steps;

m) sample a receiver input signal consisting of signals from one or more antenna;

n) add the input signal with one of a plurality of prior stored received packet sample estimates to determine a packet sample hypothesis;

o) determine an information bit estimate from the sample hypothesis for storage in an information bit estimates list;

p) determine an updated received packet sample estimate from the sample hypothesis for updating the plurality of prior stored estimates;

q) subtract the updated sample estimate from the sample hypothesis to determine a noise hypothesis and provide the noise hypothesis as the receiver input signal;

r) repeat steps a) to e) until at least one or more complete packets are accumulated in the information bit estimates list.