230 research outputs found
A Light Signalling Approach to Node Grouping for Massive MIMO IoT Networks
Massive MIMO is a promising technology to connect very large numbers of
energy constrained nodes, as it offers both extensive spatial multiplexing and
large array gain. A challenge resides in partitioning the many nodes in groups
that can communicate simultaneously such that the mutual interference is
minimized. We here propose node partitioning strategies that do not require
full channel state information, but rather are based on nodes' respective
directional channel properties. In our considered scenarios, these typically
have a time constant that is far larger than the coherence time of the channel.
We developed both an optimal and an approximation algorithm to partition users
based on directional channel properties, and evaluated them numerically. Our
results show that both algorithms, despite using only these directional channel
properties, achieve similar performance in terms of the minimum
signal-to-interference-plus-noise ratio for any user, compared with a reference
method using full channel knowledge. In particular, we demonstrate that
grouping nodes with related directional properties is to be avoided. We hence
realise a simple partitioning method requiring minimal information to be
collected from the nodes, and where this information typically remains stable
over a long term, thus promoting their autonomy and energy efficiency
Multiple Access in Aerial Networks: From Orthogonal and Non-Orthogonal to Rate-Splitting
Recently, interest on the utilization of unmanned aerial vehicles (UAVs) has
aroused. Specifically, UAVs can be used in cellular networks as aerial users
for delivery, surveillance, rescue search, or as an aerial base station (aBS)
for communication with ground users in remote uncovered areas or in dense
environments requiring prompt high capacity. Aiming to satisfy the high
requirements of wireless aerial networks, several multiple access techniques
have been investigated. In particular, space-division multiple access(SDMA) and
power-domain non-orthogonal multiple access (NOMA) present promising
multiplexing gains for aerial downlink and uplink. Nevertheless, these gains
are limited as they depend on the conditions of the environment. Hence, a
generalized scheme has been recently proposed, called rate-splitting multiple
access (RSMA), which is capable of achieving better spectral efficiency gains
compared to SDMA and NOMA. In this paper, we present a comprehensive survey of
key multiple access technologies adopted for aerial networks, where aBSs are
deployed to serve ground users. Since there have been only sporadic results
reported on the use of RSMA in aerial systems, we aim to extend the discussion
on this topic by modelling and analyzing the weighted sum-rate performance of a
two-user downlink network served by an RSMA-based aBS. Finally, related open
issues and future research directions are exposed.Comment: 16 pages, 6 figures, submitted to IEEE Journa
๋๊ท๋ชจ ๋ค์ค ์ํ ๋ ํ๊ฒฝ์์ ๋ฎ์ ๋ณต์ก๋์ ๋ค์ค ์ฌ์ฉ์ ์ ํธ์ ์ก์ ๊ดํ ์ฐ๊ตฌ
ํ์๋
ผ๋ฌธ (๋ฐ์ฌ) -- ์์ธ๋ํ๊ต ๋ํ์ : ๊ณต๊ณผ๋ํ ์ ๊ธฐยท์ปดํจํฐ๊ณตํ๋ถ, 2020. 8. ์ด์ฉํ.Advanced wireless communication systems may employ massive multi-input multi-output (m-MIMO) techniques for performance improvement. A base station equipped with an m-MIMO configuration can serve a large number of users by means of beamforming. The m-MIMO channel becomes asymptotically orthogonal to each other as the number of antennas increases to infinity. In this case, we may optimally transmit signal by means of maximum ratio transmission (MRT) with affordable implementation complexity. However, the MRT may suffer from inter-user interference in practical m-MIMO environments mainly due to the presence of insufficient channel orthogonality. The use of zero-forcing beamforming can be a practical choice in m-MIMO environments since it can easily null out inter-user interference. However, it may require huge computational complexity for the generation of beam weight. Moreover, it may suffer from performance loss associated with the interference nulling, referred to transmission performance loss (TPL). The TPL may become serious when the number of users increases or the channel correlation increases in spatial domain.
In this dissertation, we consider complexity-reduced multi-user signal transmission in m-MIMO environments. We determine the beam weight to maximize the signal-to-leakage plus noise ratio (SLNR) instead of signal-to-interference plus noise ratio (SINR). We determine the beam direction assuming combined use of MRT and partial ZF that partially nulls out interference. For further reduction of computational complexity, we determine the beam weight based on the approximated SLNR.
We consider complexity-reduced ZF beamforming that generates the beam weight in a group-wise manner. We partition users into a number of groups so that users in each group experience low TPL. We approximately estimate the TPL for further reduction of computational complexity. Finally, we determine the beam weight for each user group based on the approximated TPL.์ฐจ์ธ๋ ๋ฌด์ ํต์ ์์คํ
์์ ์ฑ๋ฅ ํฅ์์ ์ํด ๋๊ท๋ชจ ๋ค์ค ์ํ
๋ (massive MIMO) ๊ธฐ์ ๋ค์ ์ฌ์ฉํ ์ ์๋ค. ๋๊ท๋ชจ ์ํ
๋๋ฅผ ๊ฐ์ง ๊ธฐ์ง๊ตญ์ ๋ง์ ์์ ์ฌ์ฉ์๋ค์ ๋นํฌ๋ฐ (beamforming)์ผ๋ก ์๋น์คํด์ค ์ ์๋ค. ์ํ
๋ ์๊ฐ ๋ฌดํํ ์ฆ๊ฐํจ์ ๋ฐ๋ผ์ ์ฑ๋์ ์ ๊ทผ์ ์ผ๋ก ์๋ก ์ง๊ต (orthogonal)ํ๊ฒ ๋๋ค. ์ด๋ฌํ ๊ฒฝ์ฐ, ๋ฎ์ ์ค์ฅ ๋ณต์ก๋๋ฅผ ๊ฐ์ง๋ ์ต๋ ๋น ์ ์ก (maximum ratio transmission)์ ์ฌ์ฉํจ์ผ๋ก์จ ์ ํธ์ ์ก์ ์ต์ ํํ ์ ์๋ค. ํ์ง๋ง, ํ์ค์ ์ธ ๋๊ท๋ชจ ๋ค์ค ์ํ
๋ ํ๊ฒฝ์์๋ ์ฑ๋ ์ง๊ต์ฑ์ด ์ถฉ๋ถํ์ง ๋ชปํ๊ธฐ ๋๋ฌธ์ ์ต๋ ๋น ์ ์ก์ ๊ฐ์ญ์ ์ํ ์ฑ๋ฅ ์ ํ๋ฅผ ๊ฒช์ ์ ์๋ค. ์ ๋ก-ํฌ์ฑ (zero-forcing) ๋นํฌ๋ฐ์ ๊ฐ์ญ์ ์ฝ๊ฒ ์ ๊ฑฐํ ์ ์๊ธฐ ๋๋ฌธ์ ๋๊ท๋ชจ ๋ค์ค ์ํ
๋ ํ๊ฒฝ์์ ํ์ค์ ์ธ ์ ํ์ด ๋ ์ ์๋ค. ํ์ง๋ง, ์ ๋ก-ํฌ์ฑ์ ๋น ๊ฐ์ค์น (beam weight) ์์ฑ์ผ๋ก ์ธํด ๋์ ๊ณ์ฐ ๋ณต์ก๋๋ฅผ ์๊ตฌํ ์ ์๋ค. ๋ฟ๋ง ์๋๋ผ, ์ ๋ก-ํฌ์ฑ์ ๊ฐ์ญ ์ ๊ฑฐ์ ๋ํ ๋๊ฐ๋ก ์ฌ๊ฐํ ์ฑ๋ฅ ์ ํ (์ฆ, transmission performance loss; TPL)๋ฅผ ๊ฒช์ ์ ์๋ค. TPL์ ์ฌ์ฉ์ ์๊ฐ ๋ง๊ฑฐ๋ ์ฑ๋์ ๊ณต๊ฐ ์๊ด๋๊ฐ ํด ๋ ๋ ์ฌ๊ฐํด์ง ์ ์๋ค.
๋ณธ ๋
ผ๋ฌธ์์ ๋๊ท๋ชจ ๋ค์ค ์ํ
๋ ํ๊ฒฝ์์ ๋ฎ์ ๋ณต์ก๋์ ๋ค์ค ์ฌ์ฉ์ ์ ํธ์ ์ก์ ๊ณ ๋ คํ๋ค. ์ ์ ๊ธฐ๋ฒ์ ์ ํธ-๋-๊ฐ์ญ ๋ฐ ์ก์ ๋น (signal-to-interference plus noise ratio) ๋์ ์ ํธ-๋-์ ์ถ ๋ฐ ์ก์ ๋น (signal-to-leakage plus noise ratio)๋ฅผ ์ต๋ํํ๋ ๋น ๊ฐ์ค์น๋ฅผ ๊ฒฐ์ ํ๋ค. ์ ์ ๊ธฐ๋ฒ์ ์ต๋ ๋น ์ ์ก๊ณผ ๊ฐ์ญ์ ์ ํ์ ์ผ๋ก ์ ๊ฑฐํ๋ ๋ถ๋ถ ์ ๋ก-ํฌ์ฑ (partial zero-forcing)์ ์ฌ์ฉ์ ๊ธฐ๋ฐ์ผ๋ก ๋น ๋ฐฉํฅ์ ๊ฒฐ์ ํ๋ค. ๊ณ์ฐ ๋ณต์ก๋๋ฅผ ๋ ๊ฐ์์ํค๊ธฐ ์ํด์, ์ ์ ๊ธฐ๋ฒ์ ๊ทผ์ฌํ๋ ์ ํธ-๋-์ ์ถ ๋ฐ ์ก์๋น๋ฅผ ์ฌ์ฉํ์ฌ ๋น ๊ฐ์ค์น๋ฅผ ๊ฒฐ์ ํ๋ค.
๋ณธ ๋
ผ๋ฌธ์์ ๊ทธ๋ฃน ๊ธฐ๋ฐ์ผ๋ก ๋น ๊ฐ์ค์น๋ฅผ ์์ฑํ๋ ๋ฎ์ ๋ณต์ก๋์ ์ ๋ก-ํฌ์ฑ ๋นํฌ๋ฐ ์ ์ก์ ๊ณ ๋ คํ๋ค. ์ ์ ๊ธฐ๋ฒ์ ์ฌ์ฉ์๋ค์ด ๋ฎ์ TPL์ ๊ฐ๋๋ก ์ฌ์ฉ์๋ค์ ๋ค์์ ๊ทธ๋ฃน์ผ๋ก ๋ถ๋ฆฌ์ํจ๋ค. ๊ณ์ฐ ๋ณต์ก๋๋ฅผ ๋ ๊ฐ์์ํค๊ธฐ ์ํด์, ์ ์ ๊ธฐ๋ฒ์ TPL์ ๊ทผ์ฌ์ ์ผ๋ก ์ถ์ ํ๋ค. ๋ง์ง๋ง์ผ๋ก, ์ ์ ๊ธฐ๋ฒ์ ๊ทผ์ฌํ๋ TPL์ ๊ธฐ๋ฐ์ผ๋ก ํ์ฑ๋ ๊ฐ ์ฌ์ฉ์ ๊ทธ๋ฃน์ ๋ํ์ฌ ๋น ๊ฐ์ค์น๋ฅผ ๊ฒฐ์ ํ๋ค.Chapter 1. Introduction 1
Chapter 2. System model 10
Chapter 3. Complexity-reduced multi-user signal transmission 15
3.1. Previous works 15
3.2. Proposed scheme 24
3.3. Performance evaluation 47
Chapter 4. User grouping-based ZF transmission 57
4.1. Spatially correlated channel 57
4.2. Previous works 59
4.3. Proposed scheme 66
4.4. Performance evaluation 87
Chapter 5. Conclusions and further research issues 94
Appendix 97
A. Proof of Lemma 3-4 97
B. Proof of Lemma 3-5 100
C. Proof of strict quasi-concavity of SLNR_(k) 101
References 103
Korean Abstract 115Docto
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