Statistical Beamforming Techniques for Power Domain NOMA System Article Swipe
Abdulah Jeza Aljohani
,
Muhammad Moinuddin
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3390/electronics10243064
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3390/electronics10243064
Power-domain non-orthogonal multiple access (NOMA) assigns different power levels for near and far users in order to discriminate their signals by employing successive interference cancellation (SIC) at the near user. In this context, multiple-input-single-output NOMA (MISO-NOMA), where the base station (BS) is equipped with multiple antennas while each mobile user has a single antenna receiver, is shown to have a better overall performance by using the knowledge of instantaneous channel state information (CSI). However, this requires prior estimation of CSI using pilot transmission, which increases the transmission overhead. Moreover, its performance is severely degraded in the presence of CSI estimation errors. In this work, we provide statistical beamforming solutions for downlink power-domain NOMA that utilize only knowledge of statistical CSI, thus reducing the transmission overhead significantly. First, we derive the outage probabilities for both near and far users in the multi-user NOMA system without imposing strong assumptions, such as Gaussian or Chi-square distribution. This is done by employing the exact characterization of the ratio of indefinite quadratic form (IQF). Second, this work proposes two techniques to obtain the optimal solution for beam vectors which rely on the derived outage probabilities. Specifically, these two methods are based on (1) minimization of total beam power while constraining the outage probabilities to the QoS threshold, and (2) minimization of outage probabilities while constraining the total beam power. These proposed methods are non-convex function of beam vectors and, hence, are solved using numerical optimization via sequential quadratic programming (SQP). Since the proposed methods do not require pilot transmission for channel estimation, they inherit better spectral efficiency. Our results validate the theoretical findings and prove the supremacy of the proposed method.
Related Topics
Concepts
Beamforming
Noma
Channel state information
Computer science
Single antenna interference cancellation
Overhead (engineering)
Telecommunications link
Context (archaeology)
Mathematical optimization
Transmission (telecommunications)
Power (physics)
Electronic engineering
Algorithm
Mathematics
Channel (broadcasting)
Telecommunications
Engineering
Wireless
Operating system
Physics
Quantum mechanics
Paleontology
Biology
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/electronics10243064
- https://www.mdpi.com/2079-9292/10/24/3064/pdf?version=1639037689
- OA Status
- gold
- Cited By
- 2
- References
- 24
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4200182143
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4200182143Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/electronics10243064Digital Object Identifier
- Title
-
Statistical Beamforming Techniques for Power Domain NOMA SystemWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2021Year of publication
- Publication date
-
2021-12-09Full publication date if available
- Authors
-
Abdulah Jeza Aljohani, Muhammad MoinuddinList of authors in order
- Landing page
-
https://doi.org/10.3390/electronics10243064Publisher landing page
- PDF URL
-
https://www.mdpi.com/2079-9292/10/24/3064/pdf?version=1639037689Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/2079-9292/10/24/3064/pdf?version=1639037689Direct OA link when available
- Concepts
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Beamforming, Noma, Channel state information, Computer science, Single antenna interference cancellation, Overhead (engineering), Telecommunications link, Context (archaeology), Mathematical optimization, Transmission (telecommunications), Power (physics), Electronic engineering, Algorithm, Mathematics, Channel (broadcasting), Telecommunications, Engineering, Wireless, Operating system, Physics, Quantum mechanics, Paleontology, BiologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
- Citations by year (recent)
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2024: 2Per-year citation counts (last 5 years)
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24Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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