Publication | Closed Access
Achieving near-capacity on a multiple-antenna channel
2K
Citations
38
References
2003
Year
Shannon Capacity LimitsChannel CodesEngineeringChannel Capacity EstimationJoint Source-channel CodingMultiuser MimoAntennaComputer EngineeringIterative DecodingChannel CodingComputer ScienceChannel EstimationDistributed Antenna ArchitectureChannel CodeSignal ProcessingTurbo CodesMultiple-antenna Channel
Recent advances in iterative channel coding and turbo codes enable near‑capacity transmission on single‑antenna Gaussian or fading channels with low complexity, yet extending these techniques to multiple‑antenna systems is difficult because their capacities can be an order of magnitude higher. The study demonstrates that iterative processing can achieve near‑capacity on channel‑state‑known multiple‑antenna systems. The authors employ a list‑sphere decoder to iteratively detect and decode any linear space‑time mapping with soft‑input channel codes, showing near‑capacity performance through simulations benchmarked against Shannon limits for ergodic multiple‑antenna channels. The approach attains near‑capacity with both convolutional and turbo codes, delivering excellent performance at very high data rates.
Recent advancements in iterative processing of channel codes and the development of turbo codes have allowed the communications industry to achieve near-capacity on a single-antenna Gaussian or fading channel with low complexity. We show how these iterative techniques can also be used to achieve near-capacity on a multiple-antenna system where the receiver knows the channel. Combining iterative processing with multiple-antenna channels is particularly challenging because the channel capacities can be a factor of ten or more higher than their single-antenna counterparts. Using a "list" version of the sphere decoder, we provide a simple method to iteratively detect and decode any linear space-time mapping combined with any channel code that can be decoded using so-called "soft" inputs and outputs. We exemplify our technique by directly transmitting symbols that are coded with a channel code; we show that iterative processing with even this simple scheme can achieve near-capacity. We consider both simple convolutional and powerful turbo channel codes and show that excellent performance at very high data rates can be attained with either. We compare our simulation results with Shannon capacity limits for ergodic multiple-antenna channel.
| Year | Citations | |
|---|---|---|
Page 1
Page 1