Bit Allocation for Increased Power Efficiency in 5G Receivers with Variable-Resolution ADCs

Waqas Bin Abbas, Felipe Gomez-Cuba, Michele Zorzi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)


In future mmWave wireless system, fully digital receivers may have an excessive power consumption at the Analog to Digital Converters (ADC), even if lower resolution ADCs are employed. We propose to optimize the ADC resolution exploiting the sparse propagation in mmWave. We identify and assign more bits to antennas that capture stronger incoming signals, and allocate fewer bits to the antennas that see mostly noise. In order to facilitate a potential practical implementation, we constrain the allocation problem so the number of bits assigned to each antenna can take only one of two values, blow or bhigh. Compared to a reference fixed-resolution mmWave system with bref bits (blow ≤ bref ≤ bhigh), and depending on the margin between the two options given to the algorithm, (blow, bhigh), our results show that 2-level receivers with a low margin (e.g., (4, 6)) can achieve moderate power saving (5-20%) consistent across any received unquantized SNR value, whereas 2-level receivers with a wide margin (e.g., (1, 8)) can achieve a large power saving (80%) only at high SNR, while consuming more power than the reference at low SNR. Combining bit allocation with antenna selection techniques, we create a 3-level system (e.g., 0, 4, 8) that can outperform the former scenario when the given resolution options are carefully chosen.

Original languageEnglish
Title of host publication2017 Information Theory and Applications Workshop, ITA 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages7
ISBN (Electronic)9781509052936
ISBN (Print)9781509052943
Publication statusPublished - 31 Aug 2017
Externally publishedYes
Event2017 Information Theory and Applications Workshop - San Diego, United States
Duration: 12 Feb 201717 Feb 2017


Conference2017 Information Theory and Applications Workshop
Abbreviated titleITA 2017
Country/TerritoryUnited States
CitySan Diego


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