Wireless LAN compatible multi-input multi-output system

• US 7,110,350 B2
• Filed: 03/05/2004
• Issued: 09/19/2006
• Est. Priority Date: 06/18/2003
• Status: Expired due to Fees

• Current Assignee: University of Florida Research Foundation, Incorporated (State University System of Florida)
• Original Assignee: University of Florida Research Foundation, Incorporated (State University System of Florida)
• Inventors: Liu, Jianhua, Li, Jian
• Primary Examiner(s): Pham, Chi
• Assistant Examiner(s): Phan, Tri H.
• Application Number:
  US10/793,712
• Publication Number:
  US 20040258025A1
• Time in Patent Office: 928 Days
• Field of Search: 370/310, 370/334, 370/505, 370/338, 370203-208, 375/299, 375/347, 375/349, 375/267, 455/132, 455/296, 455/135, 455/303, 455101-103
• US Class Current: 370/204
• CPC Class Codes: H04L 1/0059 Convolutional codes
• CPC Class Codes: H04L 1/0068 by puncturing
• CPC Class Codes: H04L 1/0071 Use of interleaving interleaving per se H03M13/27
• CPC Class Codes: H04L 1/0656 Cyclotomic systems, e.g. Bell Labs Layered Space-Time [BLAST]
• CPC Class Codes: H04L 27/2602 Signal structure
• CPC Class Codes: H04L 27/2603 Signal structure ensuring backward compatibility with legacy system

Abstract

A system and method for enhancing the data rate of a WLAN. Through the deployment of a MIMO system, the data rate ordinarily expected of a SISO type system can be doubled. Yet, the MIMO system of the present invention can remain backward compatible with conventional WLAN standards implemented by typical SISO type system. In particular, the packet preamble of the MIMO packet of the present invention is similar to that of a conventional SISO system so as to be backward compatible with conventional SISO receivers. Additionally, the data model of the MIMO system can be configured to support the detection of symbols in the MIMO packet of the present invention. Importantly, the present invention can include a least squares soft-detector for use in a wireless LAN compatible MIMO system.

Claims

1. A method of wirelessly conveying data comprising the steps of:

digitally encoding said data into a plurality of data packets using at least one encoder, each data packet having a MIMO preamble;

simultaneously transmitting said packets using a plurality of transmission antennas;

based upon said MIMO preamble, sequentially estimating a carrier frequency offset (CFO), symbol timing, and channel response, wherein the estimated CFO refines a coarse CFO, and the estimated symbol timing refines a course symbol timing; and

based upon said transmitted packets, generating said data at a receiving location.

2. The method of claim 1, said digital encoding step using a channel coding technique to implement forward error correction.

3. The method of claim 2, wherein said channel coding technique is a convolutional encoding technique.

4. The method of claim 1, wherein said transmitting step further comprises the step of:

introducing temporal and spatial correlation into signals transmitted from different ones of said plurality of transmission antennas using a spacetime coding technique.

5. The method of claim 1, wherein said transmitting step further comprises the step of:

scattering data bits of selective ones of said packets across a plurality of said antennas using a spatial interleaving technique.

6. The method of claim 1, said generating step further comprising the steps of:

receiving said packets using a plurality of receiving antennas; and

digitally decoding said packets using a soft decoder.

7. The method of claim 6, wherein said decoding step utilizes an unstructured least squares estimation technique.

8. The method of claim 6, wherein said decoding step further comprises the step of:

computing a signal to noise ratio of received signals that is used during said decoding process.

9. The method of claim 1, wherein the step of encoding comprises encoding each data packet so that the MIMO preamble is backwardly compatible with a SISO system.

10. The method of claim 1, the step of digitally encoding comprises encoding each data packet so that the MIMO preamble comprises first and second long training sequences separated by a signal field, the second long training symbol block comprising a first training sequence associated with a first antenna and a second training sequence associated with a second antenna, the first and second training sequences being orthogonal with respect to one another.

11. A method of wirelessly conveying data comprising the steps of:

digitally encoding said data into a plurality of data packets using at least one encoder, each data packet having a MIMO preamble;

simultaneously transmitting said packets using a plurality of transmission antennas;

generating soft-information for improving the performance of a convolutional decoding process, the soft-information comprising (a) a set of unstructured least squares estimates based upon channel gain between a plurality of transmitting antennas and a plurality of receiving antennas and (b) a variance of error terms, the error terms corresponding to noise generated in a MIMO channel; and

based upon said transmitted packets, generating said data at a receiving location.

12. The method of claim 11, said digital encoding step using a channel coding technique to implement forward error correction.

13. The method of claim 12, wherein said channel coding technique is a convolutional encoding technique.

14. The method of claim 11, wherein said transmitting step further comprises the step of:

introducing temporal and spatial correlation into signals transmitted from different ones of said plurality of transmission antennas using a space-time coding technique.

15. The method of claim 11, wherein said transmitting step further comprises the step of:

scattering data bits of selective ones of said packets across a plurality of said antennas using a spatial interleaving technique.

16. The method of claim 11, said generating step further comprising the steps of:

receiving said packets using a plurality of receiving antennas; and

digitally decoding said packets using a soft decoder.

17. The method of claim 16, wherein said decoding step utilizes an unstructured least squares estimation technique.

18. A machine readable storage having stored thereon a computer program for soft-detecting soft-information required by a convolutional decoder in a wireless multi-input multi-output (MIMO) system, said computer program comprising a set of instructions executable within a computing machine which when executed cause the machine to perform the steps of:

producing an unstructured least squares estimate for a time-varying channel in the MIMO system, said unstructured least square estimate being based upon channel gains between a plurality of transmitting antennae and receiving antennae of the MIMO system;

computing a SNR based on said produced unstructured least squares estimate; and

providing to the convolutional decoder as the soft-information said unstructured least squares estimate and a variance of error terms, each of the error terms based upon the channel gains and noise generated in a MIMO channel.

19. A system for wireless conveying digital information comprising:

a transmitting source having a plurality of transmitting antennas, wherein data is transmitted from said plurality of transmitting antennas simultaneously;

a channel encoder communicatively linked to said transmitting source, said channel encoder configured to encode electronic documents into a plurality of packets, each packet having a MIMO preamble;

a receiving mechanism having a plurality of receiving antennas; and

a soft decoder communicatively linked to said receiving mechanism for receiving a soft information comprising a set of unstructured least squares estimates and a variance of error terms based upon MIMO channel noise.

20. The system of claim 19, wherein said transmitting source introduces temporal and spatial correlation into signals transmitted from different ones of said plurality of transmission antennas using a space-time coding technique.

21. The system of claim 19, wherein said channel encoder utilizes a channel coding technique to implement forward error correction.

22. The system of claim 21, wherein said channel coding technique is a convolutional encoding technique.

23. The system of claim 19, wherein said soft decoder calculates a plurality of unstructured least squares estimates when decoding received signals.

24. The system of claim 19, wherein said soft decoder calculates a signal to noise ratio of received signals when decoding said received signals.

25. The system of claim 19, further comprising:

an interleaver communicatively linked to said transmitting source; and

a deinterleaver communicatively linked to said receiving mechanism.

26. A method of wirelessly conveying data comprising the steps of:

digitally encoding the data into a plurality of data packets using at least one encoder, each data packet having a MIMO preamble that includes a first training symbol block and a second training symbol block, wherein the second training symbol block comprises a first training sequence associated with a first antenna and a second training sequence associated with a second antenna;

simultaneously transmitting said packets using a plurality of transmission antennas; and

based upon the MIMO preamble, performing at least one of estimating a carrier frequency offset, determining a symbol timing, and generating a MIMO channel estimate.

27. The method of claim 26, wherein the step of digitally encoding comprises encoding each data packet so that the first and second training sequences are orthogonal to one another.

28. A method of wirelessly conveying data, the method comprising:

estimating comparative gain for each of a plurality of pairs of transmitting and receiving antennas;

generating a MIMO fat-fading channel representation;

computing a plurality of unstructured least squares estimates and variance of error terms based on MIMO channel noise; and

supplying the unstructured least squares estimates and variance to a decoder for performing a convolutional decoding process based upon the supplying unstructured least squares estimates and variance.