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Analog Approximate-FFT 8/16-Beam Algorithm, Architectures and CMOS Circuits for 5G Beamforming MIMO Transceivers

IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS 2018年第3期8卷 466-479页

作者： Ariyarathna, Viduneth Madanayake, Arjuna Tang, Xinyao Coelho, Diego Cintra, Renato J. Belostotski, Leonid Mandal, Sownyajit Rappaport, Theodore S. Univ Akron Dept Elect & Comp Engn Akron OH 44325 USA Case Western Reserve Univ Dept Elect Engn & Comp Sci Cleveland OH 44106 USA Univ Calgary Dept Elect & Comp Engn Calgary AB T2N 1N4 Canada Univ Fed Pernambuco Signal Proc Grp Dept Estat BR-50740540 Recife PE Brazil NYU Dept Elect & Comp Engn NYU WIRELESS Tandon Sch Engn Brooklyn NY 11201 USA

Emerging millimeter-wave (mmW) wireless systems require beamforming and multiple-input multiple-output (MIMO) approaches in order to mitigate path loss, obstructions, and attenuation of the communication channel. Sharp mmW beams are essential for this purpose and must support baseband bandwidths of at least 1 GHz to facilitate higher system capacity. This paper explores a baseband multi-beamforming method based on the spatial Fourier transform. Approximate computing techniques are used to propose a low-complexity fast algorithm with sparse factorizations that neatly map to integer W/L ratios in CMOS current mirrors. The resulting approximate fast Fourier transform (FFT) can thus be efficiently realized using CMOS analog integrated circuits to generate multiple, parallel mmW beams in both transmit and receive modes. The paper proposes both 8- and 16-point approximate-FFT algorithms together with circuit theory and design information for 65-nm CMOS implementations. Post-layout simulations of the 8-point circuit in Cadence Spectre provide well-defined mmW beam shapes, a baseband bandwidth of 2.7 GHz, a power consumption of 70 mW, and a dynamic range >42.2 dB. Preliminary experimental results confirm the basic functionality of the 8-beam circuit. Schematic-level analysis of the 16-beam I/Q version show worst-case and average side lobe levels of -10.2 dB and -12.2 dB at 1 GHz bandwidth, and -9.1 dB and -11.3 dB at 1.5 GHz bandwidth. The proposed multibeam architectures have the potential to reduce circuit area and power requirements while meeting the bandwidth requirements of emerging 5G baseband systems.

关键词： Analog beamforming multi-beams 5G multi-beam arrays low-complexity algorithms

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low complexity Image Compression using Pruned 8-point DCT Approximation in Wireless Visual Sensor Networks

Low Complexity Image Compression using Pruned 8-point DCT Ap...

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International Conference on Mathematics and Information Technology (ICMIT)

作者： Araar, Chaouki Ghanemi, Salim Benmohammed, Mohammed Bourennane, El-Bey Badji Mokhtar Univ Dept Comp Sci Annaba Algeria Abdelhamid Mehri Univ Dept Software Technol & Informat Syst Constantine Algeria Univ Burgundy Dept Comp Sci Elect & Mech Dijon France

ISBN: (纸本)9781538632697

Since the transmission of the uncompressed image in the context of wireless visual sensor networks (WVSNs) consumes less energy than transmitting the compressed image, developing energy-aware compression algorithms are mandatory to extend the camera node's lifetime and thereby the whole network lifetime. The present paper studies a low-complexity image compression algorithm in the context of WVSNs. This algorithm consists of applying a pruning approach on a DCT approximation transform. The scheme is investigated in terms of computation cycles, processing time, energy consumption and image quality. Experimental works are conducted using the Atmel Atmega128 processor of Mica2 and MicaZ sensor boards. Simulation results show that the studied scheme can exhibit a competitive performance when compared against other algorithms. Furthermore, the scheme can achieve the best tradeoff between energy consumption and image quality.

关键词： WVSNs image compression approximate DCT low-complexity algorithms pruning approach pruned 8-point DCT energy conservation

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Mixed modified weighted bit-flipping decoding of low-density parity-check codes

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IET COMMUNICATIONS 2015年第2期9卷 283-290页

作者： Huang, Haiyi Wang, Yige Wei, Gang S China Univ Technol Sch Elect & Informat Engn Guangzhou 510641 Guangdong Peoples R China

In this study, a new weighted bit-flipping (WBF) algorithm called mixed modified WBF (MM-WBF) decoding is proposed for low-density parity-check codes. The new algorithm is built by mixing two WBF algorithms, one acting as the main decoding algorithm and the other acting as the auxiliary. Simulation results show that the new algorithm achieves a notable performance gain over reliability ratio-based WBF, improved M-WBF and low-complexity WBF algorithms with almost the same computational complexity. Compared with some belief-propagation-based algorithms, MM-WBF also provides an appealing performance against complexity trade-off.

关键词： parity check codes decoding computational complexity belief-propagation-based algorithms computational complexity low-complexity algorithms reliability ratio performance gain MM-WBF decoding LDPC codes low-density parity-check codes mixed modified weighted bit-flipping decoding

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Improved 8-Point Approximate DCT for Image and Video Compression Requiring Only 14 Additions

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2014年第6期61卷 1727-1740页

作者： Potluri, Uma Sadhvi Madanayake, Arjuna Cintra, Renato J. Bayer, Fabio M. Kulasekera, Sunera Edirisuriya, Amila Univ Akron Dept Elect & Comp Engn Akron OH 44325 USA Univ Fed Pernambuco Dept Estat Signal Proc Grp Recife PE Brazil Univ Fed Santa Maria Dept Estat BR-97119900 Santa Maria RS Brazil Univ Fed Santa Maria Lab Ciencias Espaciais Santa Maria LACESM BR-97119900 Santa Maria RS Brazil

Video processing systems such as HEVC requiring low energy consumption needed for the multimedia market has lead to extensive development in fast algorithms for the efficient approximation of 2-D DCT transforms. The DCT is employed in a multitude of compression standards due to its remarkable energy compaction properties. Multiplier-free approximate DCT transforms have been proposed that offer superior compression performance at very low circuit complexity. Such approximations can be realized in digital VLSI hardware using additions and subtractions only, leading to significant reductions in chip area and power consumption compared to conventional DCTs and integer transforms. In this paper, we introduce a novel 8-point DCT approximation that requires only 14 addition operations and no multiplications. The proposed transform possesses low computational complexity and is compared to state-of-the-art DCT approximations in terms of both algorithm complexity and peak signal-to-noise ratio. The proposed DCT approximation is a candidate for reconfigurable video standards such as HEVC. The proposed transform and several other DCT approximations are mapped to systolic-array digital architectures and physically realized as digital prototype circuits using FPGA technology and mapped to 45 nm CMOS technology.

关键词： Approximate DCT low-complexity algorithms image compression HEVC low power consumption

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low-complexity 8-point DCT approximations based on integer functions

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SIGNAL PROCESSING 2014年第0期99卷 201-214页

作者： Cintra, R. J. Bayer, F. M. Tablada, C. J. Univ Fed Pernambuco Dept Estat Signal Proc Grp Recife PE Brazil Univ Akron Dept Elect & Comp Engn Akron OH 44325 USA Univ Fed Santa Maria Dept Estat Santa Maria RS Brazil Univ Fed Santa Maria LACESM Santa Maria RS Brazil

The discrete cosine transform (DCT) is a central mathematical operation in several digital signal processing methods and image/video standards. In this paper, we propose a collection of twelve approximations for the 8-point DCT based on integer functions. Considered functions include: the floor, ceiling, truncation, and rounding-off functions. Sought approximations are required to meet the following specific criteria: (i) very low arithmetic complexity, (ii) orthogonality or quasi-orthogonality, and (iii) low-complexity inversion. By varying a scaling parameter, approximations could be systematically obtained and several existing approximations were identified as particular cases of the proposed methodology. Particular cases include the signed DCT and the rounded DCT. Four new quasi-orthogonal approximations were introduced and their practical relevance was demonstrated. All approximations were given fast algorithms based on matrix factorization methods. Proposed approximations are multiplierless;their computation requires only additions and bit-shifting operations. Additive complexity ranged from 18 to 24 additions. Obtained approximations were compared with the exact DCT and assessed in the context of JPEG-like image compression. As quality assessment measures, we considered the peak signal-to-noise ratio and the structural similarity index. Because its low-complexity and good performance properties, the proposed approximations are suitable for hardware implementation in dedicated architectures. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Approximate DCT Image compression Integer functions low-complexity algorithms

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low-complexity transcoding algorithm from H.264/AVC to SVC using data mining

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EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING 2013年第1期2013卷 1页

作者： Garrido-Cantos, Rosario De Cock, Jan Luis Martinez, Jose Van Leuven, Sebastian Cuenca, Pedro Garrido, Antonio Univ Castilla La Mancha Albacete Res Inst Informat Albacete 02071 Spain Ghent Univ IBBT Dept Elect & Informat Syst Multimedia Lab B-9050 Ghent Belgium

Nowadays, networks and terminals with diverse characteristics of bandwidth and capabilities coexist. To ensure a good quality of experience, this diverse environment demands adaptability of the video stream. In general, video contents are compressed to save storage capacity and to reduce the bandwidth required for its transmission. Therefore, if these compressed video streams were compressed using scalable video coding schemes, they would be able to adapt to those heterogeneous networks and a wide range of terminals. Since the majority of the multimedia contents are compressed using H.264/AVC, they cannot benefit from that scalability. This paper proposes a low-complexity algorithm to convert an H.264/AVC bitstream without scalability to scalable bitstreams with temporal scalability in baseline and main profiles by accelerating the mode decision task of the scalable video coding encoding stage using machine learning tools. The results show that when our technique is applied, the complexity is reduced by 87% while maintaining coding efficiency.

关键词： low-complexity algorithms Scalable video coding H.264/AVC Transcoding Temporal scalability Data mining

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Sparsity-aware space-time adaptive processing algorithms with L₁-norm regularisation for airborne radar

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IET SIGNAL PROCESSING 2012年第5期6卷 413-423页

作者： Yang, Z. de Lamare, R. C. Li, X. Natl Univ Def Technol Elect Sci & Engn Sch Res Inst Space Elect Changsha 410073 Hunan Peoples R China Univ York Dept Elect Commun Res Grp York YO10 5DD N Yorkshire England

This study proposes novel sparsity- aware space-time adaptive processing (SA-STAP) algorithms with L-1-norm regularisation for airborne phased-array radar applications. The proposed SA-STAP algorithms suppose that a number of samples of the full-rank STAP datacube are not meaningful for processing and the optimal full-rank STAP filter weight vector is sparse, or nearly sparse. The core idea of the proposed method is imposing a sparse regularisation (L-1-norm type) to the minimum variance STAP cost function. Under some reasonable assumptions, the authors firstly propose an L-1-based sample matrix inversion to compute the optimal filter weight vector. However, it is impractical because of its matrix inversion, which requires a high computational cost when using a large phased-array antenna. In order to compute the STAP parameters in a cost-effective way, the authors devise low-complexity algorithms based on conjugate gradient techniques. A computational complexity comparison with the existing algorithms and an analysis of the proposed algorithms are conducted. Simulation results with both simulated and the Mountain-Top data demonstrate that fast signal-to-interference-plus-noise-ratio convergence and good performance of the proposed algorithms are achieved.

关键词： radar signal processing Electromagnetic compatibility and interference Linear algebra (numerical analysis) optimal full-rank STAP filter weight vector phased array radar minimum variance STAP cost function antenna phased arrays large phased-array antenna Radar equipment, systems and applications SA-STAP algorithms matrix inversion mountain-top data Filtering methods in signal processing L1-based sample matrix inversion space-time adaptive processing radar interference Antenna arrays airborne phased-array radar applications L1-norm regularisation full-rank STAP datacube Interpolation and function approximation (numerical analysis) fast signal-to-interference-plus-noise-ratio convergence computational complexity low-complexity algorithms sparsity-aware space-time adaptive processing algorithms conjugate gradient methods filtering theory airborne radar conjugate gradient techniques

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Joint User Pairing and Resource Allocation for Uplink SC-FDMA Systems

Joint User Pairing and Resource Allocation for Uplink SC-FDM...

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54th Annual IEEE Global Telecommunications Conference (GLOBECOM)

作者： Fan, Jiancun Yin, Qinye Li, Geoffrey Ye Peng, Bingguang Zhu, Xiaolong Xi An Jiao Tong Univ Sch Elect & Informat Engn MOE Key Lab INNS Xian 710049 Peoples R China Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA USA Huawei Shanghai Res Inst Shanghai Peoples R China

ISBN: (纸本)9781424492688

In this paper, we investigate joint user pairing and resource allocation under the practical constraints in single-carrier frequency-division multiple access (SC-FDMA) LTE uplink systems. We first introduce a joint optimal algorithm based on branch-and-bound search as a benchmark. To reduce complexity, we divide the joint optimization problem into two subproblems: user pairing and resource block allocation. For these subproblems, we develop suboptimal but low-complexity algorithm. The simulation results show that the proposed algorithms outperform the conventional one.

关键词： complexity theory Joints Long Term Evolution MIMO Optimization Resource management Throughput Vectors branch-and-bound search algorithm frequency division multiple access joint optimal algorithm joint optimization problem joint user pairing low-complexity algorithms resource allocation resource allocation search problems single carrier frequency-division multiple access LTE uplink systems tree searching uplink SC-FDMA systems

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Gradient projection decoding of LDPC codes and algorithmic variations

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IET COMMUNICATIONS 2010年第2期4卷 223-233页

作者： Kasparis, C. Beaudonnet, M. Gyftodimos, E. Evans, B. G. Univ Surrey Ctr Commun Syst Res Guildford GU2 5XH Surrey England Univ Aberdeen Dept Comp Sci Aberdeen Scotland

The current study proposes decoding algorithms for low density parity check codes (LDPC), which offer competitive performance-complexity trade-offs relative to some of the most efficient existing decoding techniques. Unlike existing low-complexity algorithms, which are essentially reduced complexity variations of the classical belief propagation algorithm, starting point in the developed algorithms is the gradient projections (GP) decoding technique, proposed by Kasparis and Evans (2007). The first part of this paper is concerned with the GP algorithm itself, and specifically with determining bounds on the step-size parameter, over which convergence is guaranteed. Consequently, the GP algorithm is reformulated as a message passing routine on a Tanner graph and this new formulation allows development of new low-complexity decoding routines. Simulation evaluations, performed mainly for geometry-based LDPC constructions, show that the new variations achieve similar performances and complexities per iteration to the state-of-the-art algorithms. However, the developed algorithms offer the implementation advantages that the memory-storage requirement is significantly reduced, and also that the performance and convergence speed can be finely traded-off by tuning the step-size parameter.

关键词： algorithmic variations performance-complexity tradeoff gradient methods low density parity check codes Interpolation and function approximation (numerical analysis) parity check codes computational complexity low-complexity algorithms classical belief propagation algorithm LDPC codes gradient projection decoding geometry-based LDPC constructions memory-storage requirement decoding Tanner graph Codes

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low-complexity Network Coding algorithms for Energy Efficient Information Exchange

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JOURNAL OF COMMUNICATIONS AND NETWORKS 2008年第4期10卷 396-402页

作者： Wang, Yu Henning, Ian D. Univ Essex Dept Comp & Elect Syst Colchester CO4 3SQ Essex England

The use of network coding in wireless networks has been proposed in the literature for energy efficient broadcast. However, the decoding complexity of existing algorithms is too high for low-complexity devices. In this work we formalize the all-to-all information exchange problem and shows how to optimize the transmission scheme in terms of energy efficiency. Furthermore, we prove by construction that there exists O(1)-complexity network coding algorithms for grid networks which can achieve such optimality. We also present low-complexity heuristics for random-topology networks. Simulation results show that network coding algorithms outperforms forwarding algorithms in most cases.

关键词： Broadcast information exchange low-complexity algorithms network coding wireless network

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