Search
Results
-
A 3.8Gb/s large-scale MIMO detector for 3GPP LTE-Advanced
(2014)2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)This paper proposes - to the best of our knowledge - the first ASIC design for high-throughput data detection in single carrier frequency division multiple access (SC-FDMA)-based large-scale MIMO systems, such as systems building on future 3GPP LTE-Advanced standards. In order to substantially reduce the complexity of linear soft-output data detection in systems having hundreds of antennas at the base station (BS), the proposed detector ...Conference Paper -
Conjugate Gradient-based Soft-Output Detection and Precoding in Massive MIMO Systems
(2014)2014 IEEE Global Communications ConferenceMassive multiple-input multiple-output (MIMO) promises improved spectral efficiency, coverage, and range, compared to conventional (small-scale) MIMO wireless systems. Unfortunately, these benefits come at the cost of significantly increased computational complexity, especially for systems with realistic antenna configurations. To reduce the complexity of data detection (in the uplink) and precoding (in the downlink) in massive MIMO ...Conference Paper -
Accelerating Massive MIMO Uplink Detection on GPU for SDR Systems
(2015)2015 IEEE Dallas Circuits and Systems Conference (DCAS)We present a reconfigurable GPU-based uplink detector for massive MIMO software-defined radio (SDR) systems. To enable high throughput, we implement a configurable linear minimum mean square error (MMSE) soft-output detector and reduce the complexity without sacrificing its error-rate performance. To take full advantage of the GPU computing resources, we exploit the algorithm's inherent parallelism and make use of efficient CUDA libraries ...Conference Paper -
VLSI Design of Large-Scale Soft-Output MIMO Detection Using Conjugate Gradients
(2015)2015 IEEE International Symposium on Circuits and Systems (ISCAS)We propose an FPGA design for soft-output data detection in orthogonal frequency-division multiplexing (OFDM)-based large-scale (multi-user) MIMO systems. To reduce the high computational complexity of data detection, our design uses a modified version of the conjugate gradient least square (CGLS) algorithm. In contrast to existing linear detection algorithms for massive MIMO systems, our method avoids two of the most complex tasks, namely ...Conference Paper -
Iterative detection and decoding in 3GPP LTE-based massive MIMO systems
(2014)2014 22nd European Signal Processing Conference (EUSIPCO)Massive multiple-input multiple-output (MIMO) is expected to be a key technology in next-generation multi-user cellular systems for achieving higher throughput and better link reliability than existing (small-scale) MIMO systems. In this work, we develop a novel, low-complexity iterative detection and decoding algorithm for single carrier frequency division multiple access (SC-FDMA)-based massive MIMO systems, such as future 3GPP LTE-based ...Conference Paper -
Decentralized Data Detection for Massive MU-MIMO on a Xeon Phi Cluster
(2016)2016 50th Asilomar Conference on Signals, Systems and ComputersConventional centralized data detection algorithms for massive multi-user multiple-input multiple-output (MU-MIMO) systems, such as minimum mean square error (MMSE) equalization, result in excessively high raw baseband data rates and computing complexity at the centralized processing unit. Hence, practical base-station (BS) designs for massive MU-MIMO that rely on state-of-the-art hardware processors and I/O interconnect standards must ...Conference Paper -
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 -
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 -
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