Skip to main content
We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate
arXiv logo
Cornell University Logo

Computer Science > Information Theory

arXiv:1611.00491 (cs)
[Submitted on 2 Nov 2016]

Title:A High Throughput Pilot Allocation for M2M Communication in Crowded Massive MIMO Systems

Authors:Huimei Han, Xudong Guo, Ying Li
View PDF
Abstract:A new scheme to resolve the intra-cell pilot collision for M2M communication in crowded massive multiple-input multiple-output (MIMO) systems is proposed. The proposed scheme permits those failed user equipments (UEs), judged by a strongest-user collision resolution (SUCR) protocol, to contend for the idle pilots, i.e., the pilots that are not selected by any UE in the initial step. This scheme is called as SUCR combined idle pilots access (SUCR-IPA). To analyze the performance of the SUCR-IPA scheme, we develop a simple method to compute the access success probability of the UEs in each random access slot (RAST). The simulation results coincide well with the analysis. It is also shown that, compared to the SUCR protocol, the proposed SUCR-IPA scheme increases the throughput of the system significantly, and thus decreases the number of access attempts dramatically.
Comments: 5 pages,6 figures
Subjects: Information Theory (cs.IT)
Cite as: arXiv:1611.00491 [cs.IT]
  (or arXiv:1611.00491v1 [cs.IT] for this version)
  https://doi.org/10.48550/arXiv.1611.00491

Submission history

From: Huimei Han [view email]
[v1] Wed, 2 Nov 2016 07:36:23 UTC (783 KB)
Full-text links:

Access Paper:

  • View PDF
  • TeX Source
  • Other Formats
view license
Current browse context:
cs.IT
< prev   |   next >
new | recent | 2016-11
Change to browse by:
cs
math
math.IT

References & Citations

DBLP - CS Bibliography

listing | bibtex
Huimei Han
Xudong Guo
Ying Li
export BibTeX citation

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)