Example of IEEE Wireless Communications Letters format
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Example of IEEE Wireless Communications Letters format Example of IEEE Wireless Communications Letters format Example of IEEE Wireless Communications Letters format Example of IEEE Wireless Communications Letters format Example of IEEE Wireless Communications Letters format
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Example of IEEE Wireless Communications Letters format Example of IEEE Wireless Communications Letters format Example of IEEE Wireless Communications Letters format Example of IEEE Wireless Communications Letters format Example of IEEE Wireless Communications Letters format
Sample paper formatted on SciSpace - SciSpace
This content is only for preview purposes. The original open access content can be found here.
open access Open Access

IEEE Wireless Communications Letters — Template for authors

Publisher: IEEE
Categories Rank Trend in last 3 yrs
Control and Systems Engineering #29 of 260 up up by 8 ranks
Electrical and Electronic Engineering #79 of 693 up up by 20 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 1377 Published Papers | 11311 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 03/06/2020
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Related Journals

open access Open Access

Springer

Quality:  
High
CiteRatio: 6.6
SJR: 1.392
SNIP: 1.036
open access Open Access
recommended Recommended

IEEE

Quality:  
High
CiteRatio: 8.9
SJR: 1.19
SNIP: 1.833
open access Open Access

Hindawi

Quality:  
High
CiteRatio: 4.1
SJR: 0.399
SNIP: 1.108
open access Open Access

IEEE

Quality:  
High
CiteRatio: 7.7
SJR: 0.864
SNIP: 1.736

Journal Performance & Insights

CiteRatio

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

A measure of average citations received per peer-reviewed paper published in the journal.

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

8.2

17% from 2019

CiteRatio for IEEE Wireless Communications Letters from 2016 - 2020
Year Value
2020 8.2
2019 7.0
2018 5.8
2017 5.0
2016 4.4
graph view Graph view
table view Table view

1.23

25% from 2019

SJR for IEEE Wireless Communications Letters from 2016 - 2020
Year Value
2020 1.23
2019 1.636
2018 0.923
2017 0.678
2016 0.669
graph view Graph view
table view Table view

1.584

7% from 2019

SNIP for IEEE Wireless Communications Letters from 2016 - 2020
Year Value
2020 1.584
2019 1.699
2018 1.564
2017 1.331
2016 1.211
graph view Graph view
table view Table view

insights Insights

  • CiteRatio of this journal has increased by 17% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

insights Insights

  • SJR of this journal has decreased by 25% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has decreased by 7% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

IEEE Wireless Communications Letters

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IEEE

IEEE Wireless Communications Letters

Approved by publishing and review experts on SciSpace, this template is built as per for IEEE Wireless Communications Letters formatting guidelines as mentioned in IEEE author instructions. The current version was created on 03 Jun 2020 and has been used by 772 authors to write and format their manuscripts to this journal.

Engineering

i
Last updated on
03 Jun 2020
i
ISSN
2162-2337
i
Impact Factor
High - 2.065
i
Open Access
No
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Bibliography Name
IEEEtran
i
Citation Type
Numbered
[25]
i
Bibliography Example
C. W. J. Beenakker, “Specular andreev reflection in graphene,” Phys. Rev. Lett., vol. 97, no. 6, p.

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.1109/LWC.2014.2342736
Optimal LAP Altitude for Maximum Coverage
Akram Al-Hourani1, Sithamparanathan Kandeepan1, Simon Lardner

Abstract:

Low-altitude aerial platforms (LAPs) have recently gained significant popularity as key enablers for rapid deployable relief networks where coverage is provided by onboard radio heads. These platforms are capable of delivering essential wireless communication for public safety agencies in remote areas or during the aftermath ... Low-altitude aerial platforms (LAPs) have recently gained significant popularity as key enablers for rapid deployable relief networks where coverage is provided by onboard radio heads. These platforms are capable of delivering essential wireless communication for public safety agencies in remote areas or during the aftermath of natural disasters. In this letter, we present an analytical approach to optimizing the altitude of such platforms to provide maximum radio coverage on the ground. Our analysis shows that the optimal altitude is a function of the maximum allowed pathloss and of the statistical parameters of the urban environment, as defined by the International Telecommunication Union. Furthermore, we present a closed-form formula for predicting the probability of the geometrical line of sight between a LAP and a ground receiver. read more read less

Topics:

Radio propagation (50%)50% related to the paper
View PDF
2,153 Citations
open accessOpen access Journal Article DOI: 10.1109/LWC.2017.2757490
Power of Deep Learning for Channel Estimation and Signal Detection in OFDM Systems
Hao Ye1, Geoffrey Ye Li1, Biing-Hwang Juang1

Abstract:

This letter presents our initial results in deep learning for channel estimation and signal detection in orthogonal frequency-division multiplexing (OFDM) systems. In this letter, we exploit deep learning to handle wireless OFDM channels in an end-to-end manner. Different from existing OFDM receivers that first estimate chann... This letter presents our initial results in deep learning for channel estimation and signal detection in orthogonal frequency-division multiplexing (OFDM) systems. In this letter, we exploit deep learning to handle wireless OFDM channels in an end-to-end manner. Different from existing OFDM receivers that first estimate channel state information (CSI) explicitly and then detect/recover the transmitted symbols using the estimated CSI, the proposed deep learning-based approach estimates CSI implicitly and recovers the transmitted symbols directly. To address channel distortion, a deep learning model is first trained offline using the data generated from simulation based on channel statistics and then used for recovering the online transmitted data directly. From our simulation results, the deep learning based approach can address channel distortion and detect the transmitted symbols with performance comparable to the minimum mean-square error estimator. Furthermore, the deep learning-based approach is more robust than conventional methods when fewer training pilots are used, the cyclic prefix is omitted, and nonlinear clipping noise exists. In summary, deep learning is a promising tool for channel estimation and signal detection in wireless communications with complicated channel distortion and interference. read more read less

Topics:

Channel state information (59%)59% related to the paper, Communication channel (56%)56% related to the paper, Orthogonal frequency-division multiplexing (55%)55% related to the paper, Distortion (53%)53% related to the paper, Cyclic prefix (53%)53% related to the paper
1,357 Citations
open accessOpen access Journal Article DOI: 10.1109/LWC.2014.2363831
Low-Complexity Hybrid Precoding in Massive Multiuser MIMO Systems
Le Liang1, Wei Xu2, Xiaodai Dong1

Abstract:

Massive multiple-input multiple-output (MIMO) is envisioned to offer considerable capacity improvement, but at the cost of high complexity of the hardware. In this paper, we propose a low-complexity hybrid precoding scheme to approach the performance of the traditional baseband zero-forcing (ZF) precoding (referred to as full... Massive multiple-input multiple-output (MIMO) is envisioned to offer considerable capacity improvement, but at the cost of high complexity of the hardware. In this paper, we propose a low-complexity hybrid precoding scheme to approach the performance of the traditional baseband zero-forcing (ZF) precoding (referred to as full-complexity ZF), which is considered a virtually optimal linear precoding scheme in massive MIMO systems. The proposed hybrid precoding scheme, named phased-ZF (PZF), essentially applies phase-only control at the RF domain and then performs a low-dimensional baseband ZF precoding based on the effective channel seen from baseband. Heavily quantized RF phase control up to 2 bits of precision is also considered and shown to incur very limited degradation. The proposed scheme is simulated in both ideal Rayleigh fading channels and sparsely scattered millimeter wave (mmWave) channels, both achieving highly desirable performance. read more read less

Topics:

Precoding (67%)67% related to the paper, Zero-forcing precoding (67%)67% related to the paper, MIMO (59%)59% related to the paper, Baseband (53%)53% related to the paper, Fading (51%)51% related to the paper
View PDF
653 Citations
open accessOpen access Journal Article DOI: 10.1109/LWC.2019.2948632
Cascaded Channel Estimation for Large Intelligent Metasurface Assisted Massive MIMO
Zhen-Qing He1, Xiaojun Yuan1

Abstract:

In this letter, we consider the problem of channel estimation for large intelligent metasurface (LIM) assisted massive multiple-input multiple-output (MIMO) systems. The main challenge of this problem is that the LIM integrated with a large number of low-cost metamaterial antennas can only passively reflect the incident signa... In this letter, we consider the problem of channel estimation for large intelligent metasurface (LIM) assisted massive multiple-input multiple-output (MIMO) systems. The main challenge of this problem is that the LIM integrated with a large number of low-cost metamaterial antennas can only passively reflect the incident signals by certain phase shifts, and does not have any signal processing capability. To deal with this, we introduce a general framework for the estimation of the transmitter-LIM and LIM-receiver cascaded channel, and propose a two-stage algorithm that includes a sparse matrix factorization stage and a matrix completion stage. Simulation results illustrate that the proposed method can achieve accurate channel estimation for LIM-assisted massive MIMO systems. read more read less

Topics:

MIMO (61%)61% related to the paper, Communication channel (52%)52% related to the paper, Sparse matrix (52%)52% related to the paper
View PDF
621 Citations
open accessOpen access Journal Article DOI: 10.1109/LWC.2018.2832128
Deep Learning-Based Channel Estimation for Beamspace mmWave Massive MIMO Systems
Hengtao He1, Chao-Kai Wen2, Shi Jin1, Geoffrey Ye Li3

Abstract:

Channel estimation is very challenging when the receiver is equipped with a limited number of radio-frequency (RF) chains in beamspace millimeter-wave massive multiple-input and multiple-output systems. To solve this problem, we exploit a learned denoising-based approximate message passing (LDAMP) network. This neural network... Channel estimation is very challenging when the receiver is equipped with a limited number of radio-frequency (RF) chains in beamspace millimeter-wave massive multiple-input and multiple-output systems. To solve this problem, we exploit a learned denoising-based approximate message passing (LDAMP) network. This neural network can learn channel structure and estimate channel from a large number of training data. Furthermore, we provide an analytical framework on the asymptotic performance of the channel estimator. Based on our analysis and simulation results, the LDAMP neural network significantly outperforms state-of-the-art compressed sensing-based algorithms even when the receiver is equipped with a small number of RF chains. read more read less

Topics:

Communication channel (55%)55% related to the paper, Artificial neural network (51%)51% related to the paper, Deep learning (51%)51% related to the paper, Compressed sensing (50%)50% related to the paper
587 Citations
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IEEE Wireless Communications Letters format uses IEEEtran citation style.

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Frequently asked questions

1. Can I write IEEE Wireless Communications Letters in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the IEEE Wireless Communications Letters guidelines and auto format it.

2. Do you follow the IEEE Wireless Communications Letters guidelines?

Yes, the template is compliant with the IEEE Wireless Communications Letters guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in IEEE Wireless Communications Letters?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the IEEE Wireless Communications Letters citation style.

4. Can I use the IEEE Wireless Communications Letters templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for IEEE Wireless Communications Letters.

5. Can I use a manuscript in IEEE Wireless Communications Letters that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper IEEE Wireless Communications Letters that you can download at the end.

6. How long does it usually take you to format my papers in IEEE Wireless Communications Letters?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in IEEE Wireless Communications Letters.

7. Where can I find the template for the IEEE Wireless Communications Letters?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per IEEE Wireless Communications Letters's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the IEEE Wireless Communications Letters's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. IEEE Wireless Communications Letters an online tool or is there a desktop version?

SciSpace's IEEE Wireless Communications Letters is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

10. I cannot find my template in your gallery. Can you create it for me like IEEE Wireless Communications Letters?

Sure. You can request any template and we'll have it setup within a few days. You can find the request box in Journal Gallery on the right side bar under the heading, "Couldn't find the format you were looking for like IEEE Wireless Communications Letters?”

11. What is the output that I would get after using IEEE Wireless Communications Letters?

After writing your paper autoformatting in IEEE Wireless Communications Letters, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is IEEE Wireless Communications Letters's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for IEEE Wireless Communications Letters?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for IEEE Wireless Communications Letters. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In IEEE Wireless Communications Letters?

The 5 most common citation types in order of usage for IEEE Wireless Communications Letters are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the IEEE Wireless Communications Letters?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per IEEE Wireless Communications Letters's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download IEEE Wireless Communications Letters in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in IEEE Wireless Communications Letters Endnote style according to Elsevier guidelines.

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