A Scalable VLSI Architecture for Soft-Input Soft-Output Depth-First Sphere Decoding

Multiple-input multiple-output (MIMO) wireless transmission imposes huge challenges on the design of efficient hardware architectures for iterative receivers. A major challenge is soft-input soft-output (SISO) MIMO demapping, often approached by sphere decoding (SD). In this paper, we introduce the - to our best knowledge - first VLSI architecture for SISO SD applying a single tree-search approach. Compared with a soft-output-only base architecture similar to the one proposed by Studer et al. in IEEE J-SAC 2008, the architectural modifications for soft input still allow a one-node-per-cycle execution. For a 4x4 16-QAM system, the area increases by 57% and the operating frequency degrades by 34% only.Comment: Accepted for IEEE Transactions on Circuits and Systems II Express Briefs, May 2010. This draft from April 2010 will not be updated any more. Please refer to IEEE Xplore for the final version. *) The final publication will appear with the modified title "A Scalable VLSI Architecture for Soft-Input Soft-Output Single Tree-Search Sphere Decoding

Mapping the SISO module of the Turbo decoder to a FPFA

In the CHAMELEON project a reconfigurable systems-architecture, the Field Programmable Function Array (FPFA) is introduced. FPFAs are reminiscent to FPGAs, but have a matrix of ALUs and lookup tables instead of Configurable Logic Blocks (CLBs). The FPFA can be regarded as a low power reconfigurable accelerator for an application specific domain. In this paper we show how the SISO (Soft Input Soft Output) module of the Turbo decoding algorithm can be mapped on the reconfigurable FPFA

Approximate MIMO Iterative Processing with Adjustable Complexity Requirements

Targeting always the best achievable bit error rate (BER) performance in iterative receivers operating over multiple-input multiple-output (MIMO) channels may result in significant waste of resources, especially when the achievable BER is orders of magnitude better than the target performance (e.g., under good channel conditions and at high signal-to-noise ratio (SNR)). In contrast to the typical iterative schemes, a practical iterative decoding framework that approximates the soft-information exchange is proposed which allows reduced complexity sphere and channel decoding, adjustable to the transmission conditions and the required bit error rate. With the proposed approximate soft information exchange the performance of the exact soft information can still be reached with significant complexity gains.Comment: The final version of this paper appears in IEEE Transactions on Vehicular Technolog