Search
Results
-
On the Achievable Rates of Decentralized Equalization in Massive MU-MIMO Systems
(2017)2017 IEEE International Symposium on Information Theory (ISIT)Massive multi-user (MU) multiple-input multiple-output (MIMO) promises significant gains in spectral efficiency compared to traditional, small-scale MIMO technology. Linear equalization algorithms, such as zero forcing (ZF) or minimum mean-square error (MMSE)-based methods, typically rely on centralized processing at the base station (BS), which results in (i) excessively high interconnect and chip input/output data rates, and (ii) high ...Conference Paper -
ADMM-based Infinity Norm Detection for Large MU-MIMO: Algorithm and VLSI Architecture
(2017)2017 IEEE International Symposium on Circuits and Systems (ISCAS)We propose a novel data detection algorithm and a corresponding VLSI design for large multi-user (MU) multiple-input multiple-output (MIMO) wireless receiver. Our algorithm, referred to as ADMIN, performs alternating direction method of multipliers (ADMM)-based infinity norm constrained equalization. ADMIN is an iterative algorithm that outperforms linear detectors if the number of users is small compared to that of the antennas in base ...Conference Paper -
Estimating Sparse Signals with Smooth Support via Convex Programming and Block Sparsity
(2016)Proceedings of the 29th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016)Conventional algorithms for sparse signal recovery and sparse representation rely on l1-norm regularized variational methods. However, when applied to the reconstruction of sparse images, i.e., images where only a few pixels are non-zero, simple l1-norm-based methods ignore potential correlations in the support between adjacent pixels. In a number of applications, one is interested in images that are not only sparse, but also have a support ...Conference Paper -
Full-Duplex in Large-Scale Wireless Systems
(2013)2013 Asilomar Conference on Signals, Systems and ComputersIn this paper, we investigate the combination of full-duplex wireless communication with large-scale multiple-input multiple-output (MIMO) technology, which has the potential for bidirectional wireless communication at high spectral efficiency and low power consumption. In addition, we study its application to cellular (multi-user) systems that could be extended with large antenna arrays, such as 3GPP LTE. In order to solve the fundamental ...Conference Paper -
HSPA+/LTE-A Turbo Decoder on GPU and Multicore CPU
(2013)2013 Asilomar Conference on Signals, Systems and ComputersThis paper compares two implementations of reconfigurable and high-throughput turbo decoders. The first implementation is optimized for an NVIDIA Kepler graphics processing unit (GPU), whereas the second implementation is for an Intel Ivy Bridge processor. Both implementations support max-log-MAP and log-MAP turbo decoding algorithms, various code rates, different interleaver types, and all block-lengths, as specified by HSPA; and ...Conference Paper -
A Robust and Efficient Method to Recover Neural Events from Noisy and Corrupted Data
(2013)2013 6th International IEEE/EMBS Conference on Neural Engineering (NER)In a variety of neural data analysis problems, “neural events” such as action potentials (APs) or post-synaptic potentials (PSPs), must be recovered from noisy and possibly corrupted measurements. For instance, in calcium imaging, an AP or group of APs generate a stereotyped calcium signal with a quick rise time and slow decay. In this work, we develop a general-purpose method for: (i) learning a template waveform that signifies the ...Conference Paper -
Sparse Probit Factor Analysis for Learning Analytics
(2013)2013 IEEE International Conference on Acoustics, Speech and Signal ProcessingWe develop a new model and algorithm for machine learning-based learning analytics, which estimate a learner's knowledge of the concepts underlying a domain. Our model represents the probability that a learner provides the correct response to a question in terms of three factors: their understanding of a set of underlying concepts, the concepts involved in each question, and each question's intrinsic difficulty. We estimate these factors ...Conference Paper -
Bayesian Pairwise Collaboration Detection in Educational Datasets
(2013)2013 IEEE Global Conference on Signal and Information ProcessingOnline education affords the opportunity to revolutionize learning by providing access to high-quality educational resources at low costs. The recent popularity of so-called MOOCs (massive open online courses) further accelerates this trend. However, these exciting advancements result in several challenges for the course instructors. Among these challenges is the detection of collaboration between learners on online tests or take-home ...Conference Paper -
Implementation Trade-offs for Linear Detection in Large-Scale MIMO Systems
(2013)2013 IEEE International Conference on Acoustics, Speech and Signal ProcessingIn this paper, we analyze the VLSI implementation tradeoffs for linear data detection in the uplink of large-scale multiple-input multiple-output (MIMO) wireless systems. Specifically, we analyze the error incurred by using the sub-optimal, low-complexity matrix inverse proposed in Wu et al., 2013, ISCAS, and compare its performance and complexity to an exact matrix inversion algorithm. We propose a Cholesky-based reference architecture ...Conference Paper -
Approximate Matrix Inversion for High-Throughput Data Detection in the Large-Scale MIMO Uplink
(2013)2013 IEEE International Symposium on Circuits and Systems (ISCAS)The high processing complexity of data detection in the large-scale multiple-input multiple-output (MIMO) uplink necessitates high-throughput VLSI implementations. In this paper, we propose - to the best of our knowledge - first matrix inversion implementation suitable for data detection in systems having hundreds of antennas at the base station (BS). The underlying idea is to carry out an approximate matrix inversion using a small number ...Conference Paper