Björn Mennenga

Search sequence determination for tree search based detection algorithms

Tree search based detection algorithms provide a promising approach to solve the detection problems in MIMO systems. Depth-first, Breadth-first or Metric-first search strategies provide near max-log detection at reduced but still significant complexity. In this paper we show how the incurred complexity can be reduced substantially. In order to reduce the number of metric calculations to a minimum, we propose a novel relative determination of search sequences for QAM constellations, usable inexpensively independent of the underlying constellation size and search strategy and moreover also usable for soft-in soft-out detection. Based on its application to a sphere detector, we will demonstrate the impact on complexity and performance of the detection as well as on the detector structure. Building on the results, we propose refinements of the resulting detector providing a very good performance at minimized complexity, making the resulting detector particularly favorable for implementation.

Complexity Reduced Soft-In Soft-Out Sphere Detection Based on Search Tuples

Depth-first tree search algorithms provide a promising approach to solve the detection problems in MIMO systems. Realizations like the List Sphere Detector (LSD) or the Single Tree Search (STS) enable near max-log detection at reduced but still high complexity. In this paper we show how the complexity of List Sphere Detection can be significantly reduced by MMSE preprocessing in combination with a novel unbiased and separated candidate handling. Therefor, we propose an extension of the LSD by search tuples. Without any performance loss, the resulting Tuple Search (TS) algorithm enables major reduction of sphere sizes and enables moreover a detection with flexible performance respectively complexity. Avoiding loss of useful status information, caused by unbiased MMSE preprocessing or small candidate storage, is provided by a novel matched candidate determination, leading also to reduced hardware complexity. The combination of these methods enable high-performance soft-out detection at very low complexity. More specifically, this enables a performance improvement up to 1 dB at half the complexity of common LSD or STS algorithms.

Iterative Soft-In Soft-Out Sphere Detection for MIMO Systems

Soft-Input Soft-Output (SISO) tree search algorithms pro- vide a promising approach for complexity reduced iterative MIMO detection. Realizations based on depth-first search enable near max-log optimal detection at reduced but still high complexity. In this paper we introduce how SISO sphere detectors based on enhancements of single tree search and tuple search algorithms can be efficiently used in iterative detection, outclassing previously proposed decoders or list based iterations. The complexity of the proposed algorithms can be significantly reduced by MMSE preprocessing in combination with a novel unbiased and separated candidate assimilation. Internal clipping of search paths enables further complexity reduction as well as alignment of the tree searches leading to efficient realizations.

Vectorization of the Sphere Detection algorithm

In this paper we present concepts for vectorization of sphere detection algorithms based on regularization of depth first tree search algorithms. Due to data dependant control flow, these tree search algorithms exhibit a highly irregular structure not allowing an efficient collaborative detection of multiple received symbols in parallel. In order to enable parallel symbol processing, a transformation of the irregular tree search algorithm is proposed resulting in a novel regular algorithm structure. Based on this, a concept for a vectorized List Sphere Detector is introduced, employing a SIMD computational model. In addition to this, limiting effects of vector processing are studied, leading to concepts which ease these effects and enable the utilization of vectorizations benefits.

A 335Mb/s 3.9mm 2 65nm CMOS flexible MIMO detection-decoding engine achieving 4G wireless data rates

In current and future wireless standards, such as WiMAX, 3GPP-LTE or LTE-Advanced, receiver terminals have to support numerous operating modes for each protocol [1], as well as sophisticated transmission techniques, especially enhanced MIMO detection and iterative forward error correction (FEC). MIMO detection and FEC belong to the most computationally complex parts of the receiver-side baseband signal processing chain. Implementations thereof must have low power consumption, but also be able to interact in a flexible and efficient way in the detection-decoding engine, while at the same time not compromising on the challenging throughput and flexibility requirements associated with 4G standards. In this paper, we present a chip implementation of a MIMO sphere detector combined with a flexible FEC engine, realizing a detection-decoding engine in silicon capable of satisfying 4G requirements with a data rate of 335Mb/s.

Code generation for STA architecture

This paper presents a novel compiler backend which generates assembly code for Synchronous Transfer Architecture (STA). STA is a Very Long Instruction Word (VLIW) architecture and in addition it uses a non-orthogonal Instruction Set Architecture (ISA). Generating efficient code for this architecture needs highly optimizing techniques. The compiler backend presented in this paper is based on Integer Linear Programming (ILP). Experimental results show that the generated assembly code consumes much less execution time than the code generated by traditional ways, and the code generation can be accomplished in acceptable time.

VLSI architecture for soft-output tuple search sphere decoding

High detection complexity is known to be one of the major challenges in MIMO communications based on spatial multiplexing. Tuple Search Detector (TSD) was recently introduced, significantly reducing detection complexity in comparison to conventional algorithms while achieving close to full max-log-APP BER performance. Irregular control flow and sequential nature of depth-first-based detectors frustrate efficient application of parallelization techniques, typically leading to inefficient realizations. This work presents a novel TSD implementation, based on a scalable and parallelizable pipelined ASIP architecture. The proposed VLSI design is implemented for 4×4 MIMO transmission using 64-QAM constellation on 65-nm CMOS technology. In low SNR scenarios, proposed detector achieves 403.6 Mbps throughput at 454 MHz clock frequency. TSD can be moreover adjusted according to transmission conditions, reaching >1 Gbps. A silicon area of 0.14 mm2 (98.9 kGEs) is occupied by the TSD core, reporting low power dissipation (57.94 mW) under typical case operating conditions. Proposed detector implementation achieves close to full max-log-APP BER performance and high detection throughput with reasonable hardware complexity, by far outperforming state-of-the-art realizations.

Survey on an efficient, low-complex tuple search based sphere detector

Nowadays, high detection complexity is known to be one of the major challenges in MIMO communications based on spatial multiplexing. Tuple search (TS) sphere detection was recently introduced, demonstrating to represent a promising approach in this context. It provides significant complexity reduction in comparison to conventional algorithms, providing in addition close to full max-log-APP BER performance. Due to the increasing multiplicity of communication standards as well as variety of mobile applications demanded by users, tackling the lack of flexibility of common receiver realizations has become an additional key challenge in MIMO detection. Aim of this work is to demonstrate that the benefit provided by the tuple search strategy is still present in a wide range of possible transmission schemes. For this purpose, a novel efficiency indicator is introduced, based on which an exhaustive analysis is performed. The existing tuple search detector has been adapted to deal with different constellation orders and transmit/receive antenna configurations. In addition, the applied MMSE strategy has been modified to support undetermined systems. The obtained results show the superiority of the proposed sphere detector under different transmission conditions, thus demonstrating its efficiency and flexibility.

Complexity Reduction in Iterative Soft-In Soft-Out Sphere Detection

Soft-In Soft-Out (SISO) MIMO detection algorithms providing soft information to subsequent channel decoder are computationally high complex. Realizations based on depth-first search e.g. the Tuple Search (TS) algorithm enables near full MaxLogAPP optimal detection at much reduced but still high complexity. This paper presents a novel method for the complexity reduction of SISO MIMO detection algorithms. This method is based on the pruning of tree nodes and the corresponding subtrees. The pruning is decided based on the absolute value of a priori information of bits greater than or equal to a threshold value. Simulation results for the TS algorithm show that up to 25% reduction in complexity can be achieved without any BER performance degradation.

Scalable ASIP implementation and parallelization of a MIMO sphere detector

High detection complexity is known to be one of the major challenges in MIMO communications based on spatial multiplexing. Tuple Search Detector (TSD) was recently introduced, significantly reducing detection complexity in comparison to conventional algorithms while achieving close to full max-log-APP BER performance. Besides high computational complexity, irregular control flow and sequential nature of the tree search represent major limitations of depth-first-based detectors, frustrating efficient application of parallelization techniques and hence leading to inefficient realizations with regard to most practical applications. This work1 presents a novel TSD implementation, scalable in constellation size and number of antennas and mapped to a highly parallel and pipelined ASIP architecture. Major challenges and key strategies enabling a high-throughput and low-complexity realization are presented and performance of the resulting flexible and efficient detector implementation is evaluated. Proposed realization is shown to achieve > 300 Mbps throughput at a reference clock frequency of 400 MHz (regarding 4×4 MIMO transmission with 16-QAM), by far outperforming comparable state-of-the-art realizations.