Method and system for data communication

• US 8,412,260 B2
• Filed: 05/06/2009
• Issued: 04/02/2013
• Est. Priority Date: 05/09/2008
• Status: Active Grant

• Current Assignee: Vodafone Holding GmbH (Vodafone Group PLC)
• Original Assignee: Vodafone Holding GmbH (Vodafone Group PLC)
• Inventors: Rave, Wolfgang
• Primary Examiner(s): NGUYEN, HAI V
• Application Number:
  US12/436,565
• Publication Number:
  US 20090279442A1
• Time in Patent Office: 1,427 Days
• Field of Search: 455/524
• US Class Current: 455/524
• CPC Class Codes: H04L 1/0048 in conjunction with detection of multiuser or interfering signals, e.g. iteration between CDMA or MIMO detector and FEC decoder for spatial equalizer H04L25/03286
• CPC Class Codes: H04L 25/067 providing soft decisions, i.e. decisions together with an estimate of reliability H04L25/068 and H04L25/069 take precedence; sequence estimation techniques H04L25/03178

Abstract

There is provided a system and method for multi-user detection by a plurality of base stations situated at different geographical locations through base station cooperation. An exemplary method comprises exchanging detected data iteratively while performing separate detection and decoding of received data streams.

Claims

1. A method for multi-user detection by a plurality of base stations situated at different geographical locations through base station cooperation, the method comprising exchanging detected data iteratively among the base stations while performing separate detection and decoding of received data streams, wherein the detected data is based on processed information relating to associated mobile terminals between the base stations, and wherein the detected data comprises L-values for which optimum quantization and decision levels have been obtained based on a transformed variable showing saturation with increasing reliability.

2. The method recited in claim 1, comprising exchanging only processed information relating to associated mobile terminals between the base stations.

3. The method recited in claim 1, comprising calculating local estimates of dominant interferers of at least two base stations.

4. The method recited in claim 3, comprising combining local estimates of dominant interferers of a first subset of the plurality of base stations with independently received copies from a second subset of the plurality of base stations.

5. The method recited in claim 4, wherein the first subset of the plurality of base stations comprises most of the plurality of base stations.

6. The method recited in claim 3, comprising combining the local estimates for the at least two base stations with their independently received copies from other ones of the plurality of base stations.

7. The method recited in claim 1, comprising:

calculating local estimates of dominant interferers of the plurality of base stations; and

combining the local estimates with independently received copies from at least some of the plurality of base stations.

8. The method recited in claim 1, comprising generating local estimates of dominant interferers at each of the plurality of base stations using single-antenna interference cancellation techniques.

9. The method recited in claim 1, wherein the transformed variable showing saturation with increasing reliability is a soft-bit density presentation of the L-values.

10. The method recited in claim 9, wherein only soft-bits that have changed signs between iterations are exchanged.

11. The method recited in claim 1, wherein the transformed variable showing saturation with increasing reliability is a mutual information presentation of the L-values.

12. The method recited in claim 1, wherein used levels vary with mean and variance of a currently to be transmitted block of L-values.

13. The method recited in claim 1, comprising estimating a data rate required for the exchange of quantized L-values by exploiting the fact that used quantization levels differ strongly in their respective probabilities, wherein the levels can represented with an entropy coding technique and prefix-free codes using labels of different length.

14. The method recited in claim 1, wherein the optimum quantization comprises nonuniform quantization minimizing mean square quantization error.

15. A communication system that is adapted to carry out communication between a plurality of communication devices situated at different geographical locations, each of the communication devices being adapted to exchange detected data iteratively among the plurality of base stations while performing separate detection and decoding of received data streams, whereby the exchanged detected data is based on processed information relating to associated mobile terminals between the base stations and the exchanged detected data comprises L-values for which optimum quantization and decision levels have been obtained based on a transformed variable showing saturation with increasing reliability.

16. The communication system recited in claim 15, wherein each of the communication devices comprises a logical node.