Algorithms and Architectures of Energy-Efficient Error-Resilient MIMO Detectors for Memory-Dominated Wireless Communication Systems

In a broadband MIMO-OFDM wireless communication system, embedded buffering memories occupy a large portion of the chip area and a significant amount of power consumption. Due to process variations of advanced CMOS technologies, it becomes both challenging and costly to maintain perfectly functioning memories under all anticipated operating conditions. Thus, Voltage over Scaling (VoS) has emerged as a means to achieve energy efficient systems resulting in a tradeoff between energy efficiency and reliability. In this paper we present the algorithm and VLSI architecture of a novel error-resilient K-Best MIMO detector based on the combined distribution of channel noise and induced errors due to VoS. The simulation results show that, compared with a conventional MIMO detector design, the proposed algorithm provides up-to 4.5 dB gain to achieve the near-optimal Packet Error Rate (PER) performance in the 4 × 4 64-QAM system. Furthermore, based on experimental results, when jointly considering the detector and memory power consumption, the proposed resilient scheme with VoS memory can achieve up to 32.64% savings compared to the conventional K-Best detector with perfect memory. © 2014 IEEE

VLSI decoding architectures: flexibility, robustness and performance

Stemming from previous studies on flexible LDPC decoders, this thesis work has been mainly focused on the development of flexible turbo and LDPC decoder designs, and on the narrowing of the power, area and speed gap they might present with respect to dedicated solutions. Additional studies have been carried out within the field of increased code performance and of decoder resiliency to hardware errors. The first chapter regroups several main contributions in the design and implementation of flexible channel decoders. The first part concerns the design of a Network-on-Chip (NoC) serving as an interconnection network for a partially parallel LDPC decoder. A best-fit NoC architecture is designed and a complete multi-standard turbo/LDPC decoder is designed and implemented. Every time the code is changed, the decoder must be reconfigured. A number of variables influence the duration of the reconfiguration process, starting from the involved codes down to decoder design choices. These are taken in account in the flexible decoder designed, and novel traffic reduction and optimization methods are then implemented. In the second chapter a study on the early stopping of iterations for LDPC decoders is presented. The energy expenditure of any LDPC decoder is directly linked to the iterative nature of the decoding algorithm. We propose an innovative multi-standard early stopping criterion for LDPC decoders that observes the evolution of simple metrics and relies on on-the-fly threshold computation. Its effectiveness is evaluated against existing techniques both in terms of saved iterations and, after implementation, in terms of actual energy saving. The third chapter portrays a study on the resilience of LDPC decoders under the effect of memory errors. Given that the purpose of channel decoders is to correct errors, LDPC decoders are intrinsically characterized by a certain degree of resistance to hardware faults. This characteristic, together with the soft nature of the stored values, results in LDPC decoders being affected differently according to the meaning of the wrong bits: ad-hoc error protection techniques, like the Unequal Error Protection devised in this chapter, can consequently be applied to different bits according to their significance. In the fourth chapter the serial concatenation of LDPC and turbo codes is presented. The concatenated FEC targets very high error correction capabilities, joining the performance of turbo codes at low SNR with that of LDPC codes at high SNR, and outperforming both current deep-space FEC schemes and concatenation-based FECs. A unified decoder for the concatenated scheme is subsequently propose