Low-Complexity Minimum Energy Beamforming in Directional Networking

2020 ◽  
Author(s):  
Yuanzhang Xiao ◽  
Gui Chao Huang ◽  
Pratiksha Shukla ◽  
Zhengqing Yun ◽  
Magdy Iskander
Keyword(s):  
Minimum Energy ◽  
Low Complexity ◽  
Energy Beamforming

scholarly journals Hierarchical Distribution Matching for Probabilistic Amplitude Shaping

Entropy ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. 958
Author(s):  
Stella Civelli ◽  
Marco Secondini
Keyword(s):  
Lower Layer ◽  
Minimum Energy ◽  
Single Layer ◽  
Low Complexity ◽  
Design Guidelines ◽  
Constant Composition ◽  
Distribution Matching ◽  
Practical Design ◽  
Rate Loss ◽  
Complexity Increase

Probabilistic amplitude shaping—implemented through a distribution matcher (DM)—is an effective approach to enhance the performance and the flexibility of bandwidth-efficient coded modulations. Different DM structures have been proposed in the literature. Typically, both their performance and their complexity increase with the block length. In this work, we present a hierarchical DM (Hi-DM) approach based on the combination of several DMs of different possible types, which provides the good performance of long DMs with the low complexity of several short DMs. The DMs are organized in layers. Each upper-layer DM encodes information on a sequence of lower-layer DMs, which are used as “virtual symbols”. First, we describe the Hi-DM structure, its properties, and the encoding and decoding procedures. Then, we present three particular Hi-DM configurations, providing some practical design guidelines, and investigating their performance in terms of rate loss and energy loss. Finally, we compare the system performance obtained with the proposed Hi-DM structures and with their single-layer counterparts: a 0.19dB SNR gain is obtained by a two-layer Hi-DM based on constant composition DMs (CCDM) compared to a single-layer CCDM with same complexity; a 0.12dB gain and a significant complexity reduction are obtained by a Hi-DM based on minimum-energy lookup tables compared to a single-layer DM based on enumerative sphere shaping with same memory requirements.

A Low-Complexity Sparse Channel Estimation Method for OFDM Systems

2010 ◽  
Vol E93-B (8) ◽  
pp. 2211-2214
Author(s):  
Bin SHENG ◽  
Pengcheng ZHU ◽  
Xiaohu YOU ◽  
Lan CHEN
Keyword(s):  
Channel Estimation ◽  
Estimation Method ◽  
Low Complexity ◽  
Ofdm Systems ◽  
Sparse Channel Estimation ◽  
Sparse Channel

Low-Complexity Soft-ML Detection Algorithm for Modified-DCM in WiMedia UWB Systems

2013 ◽  
Vol E96.B (3) ◽  
pp. 910-913 ◽  
Author(s):  
Kilhwan KIM ◽  
Jangyong PARK ◽  
Jihun KOO ◽  
Yongsuk KIM ◽  
Jaeseok KIM
Keyword(s):  
Low Complexity ◽  
Detection Algorithm ◽  
Ml Detection
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