Improving the DVB-T2 BICM performance by newly optimized Two-Dimensional Non-Uniform Constellations

Morgade, Javier; Ansorregui, Daniel; Mouhouche, Belkacem; Jeong, Hongsil; Lee, Hak‐Ju

doi:10.1109/icce-berlin.2014.7034316

Cited by 10 publications

(5 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some advanced systems such as Digital Video Broadcasting -Next Generation Handheld (DVB-NGH) [9] and ATSC 3.0 [10] have adopted NUCs. Since 2D-NUCs take more freedoms into account, they can provide higher capacity gain than 1D-NUCs [11]. However, for massive order constellations (beyond 256 constellation points) the latency and demapping complexity involved in 2D-NUCs make their use unfeasible in the practical application.…”

Section: Introductionmentioning

confidence: 99%

International Journal of Electronics and Telecommunications

Wang¹,

Wang²,

Li³

et al. 2019

View full text Add to dashboard Cite

This paper presents a novel low-complexity soft demapping algorithm for two-dimensional non-uniform spaced constellations (2D-NUCs) and massive order one-dimensional NUCs (1D-NUCs). NUCs have been implemented in a wide range of new broadcasting systems to approach the Shannon limit further, such as DVB-NGH, ATSC 3.0 and NGB-W. However, the soft demapping complexity is extreme due to the substantial distance calculations. In the proposed scheme, the demapping process is classified into four cases based on different quadrants. To deal with the complexity problem, four groups of reduced subsets in terms of the quadrant for each bit are separately calculated and stored in advance. Analysis and simulation prove that the proposed demapper only introduces a small penalty under 0.02dB with respect to Max-Log-MAP demapper, whereas a significant complexity reduction ranging from 68.75% to 88.54% is obtained.

show abstract

Section: Introductionmentioning

confidence: 99%

International Journal of Electronics and Telecommunications

Wang¹,

Wang²,

Li³

et al. 2019

View full text Add to dashboard Cite

show abstract

“…In [3], the authors present a performance analysis for their optimized NUC. The effectiveness of NUC was briefly tested in [4] followed by an extensive analysis of a large range of modulation and coding schemes in [7]. The previous analysis in [4,7] focused on the additive white Gaussian noise (AWGN) channel scenario.…”

Section: Introductionmentioning

confidence: 99%

“…The effectiveness of NUC was briefly tested in [4] followed by an extensive analysis of a large range of modulation and coding schemes in [7]. The previous analysis in [4,7] focused on the additive white Gaussian noise (AWGN) channel scenario. The work carried out up to now on NUC has always concentrated on the single channel BICM capacity optimization.…”

Section: Introductionmentioning

confidence: 99%

Multichannel Design of Non Uniform Constellations for Broadcast/Multicast Services

Mouhouche

Al-Imari

Ansorregui

2016

2016 IEEE 84th Vehicular Technology Conference (VTC-Fall)

Self Cite

View full text Add to dashboard Cite

Recent studies have shown the potential performance gain of Non Uniform Constellations (NUC) compared to the conventional uniform constellations. NUC can be a promising candidate in 5G systems to increase the data throughput. In the literature, NUC is designed for a specific SNR value and propagation channel. However, in broadcast/multicast services, the received signal by different users will see independent and different channels. Hence, in this paper, we focus on the potential gain of NUC when jointly optimized for more than one propagation channel. In order to assess the gain, we propose an iterative algorithm to jointly optimize the NUC for different channel conditions. The resulting constellations are then compared to uniform constellation and single channel NUC. The simulation results show that the newly designed constellations outperform the classical single channel NUC across different channel conditions when the average performance (across different channels) is considered.Index Terms-5G Physical Layer, Constellations, Nonuniform QAM, broadcast/multicast. I.

show abstract

“…Systematic approach about how to select multidimensional constellations, how to apply set partitioning process and how to bit to symbol mapping rule is represented in [16,17]. After outperforming TCM coded system with more flexible encoder structure over fading channels, constellation design framework can be seen in bit-interleaved coded modulation (BICM) coded scenarios [18][19][20]. Also, optimization framework to maximize channel capacity for other channel coding techniques like low-density parity check code (LDPC) is represented in [21].…”

Section: A Brief History Of Constellation Designmentioning

confidence: 99%

SNR-Adaptive Constellation Design for Convolutional Codes

Ilter¹

View full text Add to dashboard Cite

The development of 5G communication technology has introduced new families of applications and use cases during just its standardization and some of them have brought peculiar system requirements, where existing channel coding in its current form might suffer from tackling them. As an example of this, it can be shown that deploying one of the powerful channel coding techniques might suffer in tackling stringent delay requirements while sustaining higher reliability in some mission-critical applications due to iterative decoding structure. Besides, an error-floor region might prevent turbo-coded systems from deploying in certain use cases. From this perspective, a channel coding technique, while currently less popular than the others, might have considerable potential over 5G and beyond after optimizing its modules.Motivated by this fact, this thesis aims to present an SNR-adaptive convolutionally coded transmission model where the simplicity of a convolutional encoder has combined with current advanced optimization ability. Basically, the proposed transmission model combines one-shot decoding superiority of convolutional coder with the utilization of choosing an optimized group of symbol points, which are obtained specifically for a given convolutional encoder, channel characteristic and transmission model. The enabler of an SNR-adaptive optimization framework is the derivation of upper bound error performance expression by exploiting the product-state matrix technique, which is used in the calculation of generating function for a given convolutional encoder and it brings the superiority to work with any type of constellations. The importance of including fully arbitrary, irregular type, constellations in constellation search lies on that the uniform constellations can lead to suboptimal performance in many coded scenarios including bit-interleaved coded modulated and turbo-trellis coded modulations as already shown.As an initial step towards the proposed SNR-adaptive transmission model, a generalized error performance calculation was first presented. Once optimized symbol ii point locations via particle swarm constellation optimizer are found for each operating point, the performance comparison of the proposed SNR-adaptive convolutionally coded transmission model with SNR-independent counterparts is given in terms of BER and spectral efficiency. The superiority of the proposed transmission model, in terms of algorithmic complexity and decoding latency, is also presented.iii I dedicate this thesis to my wife, Gozde, who has been with me all these years and has made them the best years of my life.. iv

show abstract

Improving the DVB-T2 BICM performance by newly optimized Two-Dimensional Non-Uniform Constellations

Cited by 10 publications

References 6 publications

International Journal of Electronics and Telecommunications

International Journal of Electronics and Telecommunications

Multichannel Design of Non Uniform Constellations for Broadcast/Multicast Services

SNR-Adaptive Constellation Design for Convolutional Codes

Contact Info

Product

Resources

About