20 research outputs found
๊ณ ์ ์ด๋ ํ๊ฒฝ์์ ๋๊ท๋ชจ ๋ค์ค์ํ ๋ ์์คํ ์ ๊ดํ ์ฐ๊ตฌ
ํ์๋
ผ๋ฌธ (๋ฐ์ฌ) -- ์์ธ๋ํ๊ต ๋ํ์ : ๊ณต๊ณผ๋ํ ์ ๊ธฐยท์ ๋ณด๊ณตํ๋ถ, 2020. 8. ์ด์ฉํ.Advanced cellular communication systems may obtain high array gain by employing massive multi-input multi-output (m-MIMO) systems, which may require accurate channel state information (CSI). When users are in high mobility, it may not be easy to get accurate CSI. When we transmit signal to users in high mobility, we may experience serious performance loss due to the inaccuracy of outdated CSI, associated with so-called channel aging effect. This problem may be alleviated by exploiting channel correlation matrix (CCM) in spatial domain. However, it may require an additional process for the estimation of CCM, which may require high signaling overhead in m-MIMO environments. In this dissertation, we consider signal transmission to multiple users in high mobility in m-MIMO environments.
We consider the estimation of CSI with reduced signaling overhead. The signaling overhead for the CSI estimation is a challenging issue in m-MIMO environments. We may reduce the signaling overhead for the CSI estimation by using pilot signal transmitted by means of beamforming with a weight determined by eigenvectors of CCM. To this end, we need to estimate the CCM, which may still require large signaling overhead. We consider the estimation of CCM with antennas in a uniform linear array (ULA). Since pairs of antennas with an equal distance may experience spatial channel correlation similar to each other in ULA antenna environments, we may jointly estimate the spatial channel correlation. We estimate the mean-square error (MSE) of elements of estimated CCM and then discard the elements whose MSE is higher than a reference value for the improvement of CCM estimation. We may estimate the CSI from the estimated CCM with reduced signaling overhead.
We consider signal transmission robust to the presence of channel aging effect. Users in different mobility may differently experience the channel aging effect. This means that they may differently suffer from transmission performance loss. To alleviate this problem, we transmit signal to maximize the average signal-to-leakage-plus-noise ratio, making it possible to individually handle the channel aging effect. We consider the signal transmission to the eigen-direction of a linear combination of CSI and CCM. Analyzing the transmission performance in terms of signal-to-interference-plus-noise ratio, we control the transmit power by using an iterative water-filling technique.
Finally, we consider the allocation of transmission resource in the presence of channel aging effect. We design a sub-optimal greedy algorithm that allocates the transmission resource to maximize the sum-rate in the presence of channel aging effect. We may estimate the sum-rate from the beam weight and a hypergeometric function (HF) that represents the effect of outdated CSI on the transmission performance. However, it may require very high computational complexity to calculate the beam weight and the HF in m-MIMO environments. To alleviate the complexity problem, we determine the beam weight in dominant eigen-direction of CCM and approximate the HF as a function of temporal channel correlation. Since we may estimate the sum-rate by exploiting spatial and temporal channel correlation, we may need to update the resource allocation only when the change of CCM or temporal channel correlation is large enough to affect the sum-rate. Simulation results show that the proposed scheme provides performance similar to a greedy algorithm based on accurate sum-rate, while significantly reducing the computational complexity.๊ธฐ์ง๊ตญ์ด ์๋ง์ ์ํ
๋๋ฅผ ํ์ฉํ์ฌ ๋์ ์ ์ก ์ด๋์ ์ป์ ์ ์๋ ๋๊ท๋ชจ ๋ค์ค ์ํ
๋(massive MIMO) ์์คํ
์ด ์ฐจ์ธ๋ ๋ฌด์ ํต์ ์์คํ
์ผ๋ก ๊ฐ๊ด๋ฐ๊ณ ์๋ค. ์ด๋ฅผ ์ํด์๋ ์ ํํ ์ฑ๋ ์ ๋ณด(channel state information)๋ฅผ ๊ธฐ๋ฐ์ผ๋ก ํ๋ ์ ํธ ์ ์ก ๋ฐ ์์ ๊ด๋ฆฌ ๊ธฐ์ ์ด ํ์์ ์ด๋ค. ํ์ง๋ง ์ฌ์ฉ์๊ฐ ๊ณ ์์ผ๋ก ์ด๋ํ๋ ํ๊ฒฝ์์๋ ๊ธฐ์ง๊ตญ์ด ์ถ์ ํ ์ฑ๋ ์ ๋ณด์ ์ค์ ์ ์ก ์ฑ๋์ด ํฌ๊ฒ ๋ฌ๋ผ์ง๋ ์ฑ๋ ๋ณํ ํจ๊ณผ(channel aging effect)๊ฐ ๋ฐ์ํ์ฌ, ์์คํ
์ ์ก ์ฑ๋ฅ์ด ์ฌ๊ฐํ๊ฒ ํ๋ฝํ ์ ์๋ค. ์ ๋ฌธ์ ๋ฅผ ํด๊ฒฐํ๊ธฐ ์ํ์ฌ, ์๋์ ์ผ๋ก ์ฌ์ฉ์ ์ด๋์ฑ์ ๋๋ฆฌ๊ฒ ๋ณํํ๋ ๊ณต๊ฐ ์๊ด๋ ํ๋ ฌ(channel correlation matrix)์ ํ์ฉํ ์ ์๋ค. ํ์ง๋ง ๋๊ท๋ชจ ๋ค์ค ์ํ
๋ ์์คํ
์์๋ ๊ธฐ์ง๊ตญ์ด ๊ณต๊ฐ ์๊ด๋ ํ๋ ฌ์ ์ถ์ ํ๋ ๊ณผ์ ์์ ํฐ ํ์ผ๋ฟ(pilot) ์ ํธ ๋ถ๋ด์ด ๋ฐ์ํ ์ ์๋ค. ๋ณธ ๋
ผ๋ฌธ์ ๊ณ ์ ์ด๋ ํ๊ฒฝ์์์ ๋๊ท๋ชจ ๋ค์ค ์ํ
๋ ์์คํ
์์ ๋ค์ค ์ฌ์ฉ์์ ๋ํ ์ ํธ ์ ์ก์ ๊ณ ๋ คํ๋ค.
์ฐ์ , ๋ฎ์ ํ์ผ๋ฟ ์ ํธ ๋ถ๋ด์ ๊ฐ๋ ์ฑ๋ ์ ๋ณด ์ถ์ ๋ฐฉ๋ฒ์ ์ ์ํ๋ค. ๋๊ท๋ชจ ๋ค์ค ์ํ
๋ ์์คํ
์์ ์ฑ๋ ์ ๋ณด ์ถ์ ์ ํฐ ํ์ผ๋ฟ ์ ํธ ๋ถ๋ด์ ์ผ๊ธฐํ ์ ์๋ค. ์ด๋ ๊ณต๊ฐ ์๊ด๋ ํ๋ ฌ์ ํ์ฉํ ํ์ผ๋ฟ ์ ํธ ์ค๊ณ๋ฅผ ํตํ์ฌ ์ฑ๋ ์ ๋ณด ์ถ์ ์ผ๋ก ์ธํ ์ ํธ ๋ถ๋ด์ ํจ๊ณผ์ ์ผ๋ก ๊ฐ์์ํฌ ์ ์๋ค. ํ์ง๋ง ์ด๋ฅผ ์ํด์๋ ๊ณต๊ฐ ์๊ด๋ ํ๋ ฌ์ ์ถ์ ํด์ผ ํ๋ฉฐ, ์ด ๊ณผ์ ์์ ํฐ ์ ํธ ๋ถ๋ด์ด ์ผ๊ธฐ๋ ์ ์๋ค. ์ ์ ๊ธฐ๋ฒ์ ๊ธฐ์ง๊ตญ์ด ๊ท ์ผํ ์ ํ ์ํ
๋ ๋ฐฐ์ด(uniform linear array)์ ๊ฐ์ง๊ณ ์๋ ํ๊ฒฝ์์, ๊ฐ์ ๊ฑฐ๋ฆฌ์ ์ํ
๋ ์๋ค์ ์ฑ๋ ๊ฐ ๊ณต๊ฐ ์๊ด๋๊ฐ ์ ์ฌํ๋ค๋ ํน์ง์ ํ์ฉํ์ฌ, ์๊ธฐ ์ํ
๋ ์๋ค์ ์ฑ๋ ๊ฐ ๊ณต๊ฐ ์๊ด๋๋ฅผ ์ต์์์น์ถ์ ๋ฒ(least-square estimation)์ ํ์ฉํ์ฌ ์ถ์ ํ๋ค. ๊ทธ๋ฆฌ๊ณ ์ถ์ ๋ ๊ณต๊ฐ ์๊ด๋์ ํ๊ท ์ ๊ณฑ์ค์ฐจ(mean-square error)๋ฅผ ์ถ์ ํ์ฌ, ์๊ธฐ ํ๊ท ์ ๊ณฑ์ค์ฐจ๊ฐ ํฐ ๊ณต๊ฐ ์๊ด๋๋ฅผ 0์ผ๋ก ์นํํ์ฌ ๊ณต๊ฐ ์๊ด๋ ํ๋ ฌ์ ์ถ์ ์ ํ๋๋ฅผ ๋์ธ๋ค. ๋ํ ์๊ธฐ ์ถ์ ํ ๊ณต๊ฐ ์๊ด๋ ํ๋ ฌ์ ํ์ฉํ์ฌ ๋ฎ์ ์ ํธ ๋ถ๋ด์ผ๋ก ์ฑ๋ ์ ๋ณด๋ฅผ ์ถ์ ํ ์ ์๋ ๊ฒ์ ๋ณด์ธ๋ค.
๋์งธ๋ก, ์ฌ์ฉ์ ์ด๋์ฑ์ ์ํ ์ฑ๋ ๋ณํ์ ๊ฐ์ธํ ์ ํธ ์ ์ก ๋ฐฉ๋ฒ์ ์ ์ํ๋ค. ์ฌ์ฉ์๋ค์ด ์๋ก ๋ค๋ฅธ ์๋๋ก ์ด๋ํ๋ ํ๊ฒฝ์์๋ ์ฑ๋ ๋ณํ์ ์ํ ์ ํธ ์ ์ก ์ฑ๋ฅ ์ ํ ์ญ์ ์ฌ์ฉ์๋ง๋ค ๋ค๋ฅด๊ฒ ๋ํ๋ ์ ์๋ค. ์ ๋ฌธ์ ๋ฅผ ํด๊ฒฐํ๊ธฐ ์ํ์ฌ, ๊ฐ ์ฌ์ฉ์์ ๋ํ ์ฑ๋ ๋ณํ ํจ๊ณผ๋ฅผ ๊ฐ๋ณ์ ์ผ๋ก ๊ณ ๋ คํ๋ฉด์ ํ๊ท ์ ํธ ๋ ๋์๊ฐ์ญ ๋ฐ ์ก์๋น(signal-to-leakage-plus-noise ratio)๋ฅผ ์ต๋ํํ๋ ์ ์ก ๋น ๊ฐ์ค์น๋ฅผ ์ค๊ณํ๋ค. ์ ์ ๊ธฐ๋ฒ์ ์ฌ์ฉ์๋ค์ ์ฑ๋ ์ ๋ณด์ ๊ณต๊ฐ ์๊ด๋ ํ๋ ฌ์ ์ ํ ๊ฒฐํฉ์ ๊ณ ์ ๋ฐฉํฅ(eigen-direction)์ผ๋ก ์ ํธ๋ฅผ ์ ์กํ๋ค. ๋ํ ์ ์ ๊ธฐ๋ฒ์ ์ฌ์ฉํ ๋์ ์ ํธ ๋ ๊ฐ์ญ ๋ฐ ์ก์๋น(signal-to-interference-plus-noise ratio)๋ฅผ ๋ถ์ํ๊ณ , ์ด๋ฅผ ๊ธฐ๋ฐ์ผ๋ก ํ๋ ์ ์ก ์ ๋ ฅ ๋ถ๋ฐฐ ๋ฐฉ๋ฒ์ ์ ์ํ๋ค.
๋์ผ๋ก, ์ฌ์ฉ์ ์ด๋์ฑ์ ๋ฐ๋ฅธ ์ฑ๋ ๋ณํ๋ฅผ ๊ณ ๋ คํ๋ ์์ ํ ๋น ๋ฐฉ๋ฒ์ ์ ์ํ๋ค. ์ด๋ฅผ ์ํ์ฌ, ์๊ธฐ ์ฑ๋ ๋ณํ๋ฅผ ๊ณ ๋ คํ์ฌ ์์คํ
์ ์ก ์ฑ๋ฅ(sum-rate)์ ์ต๋ํํ๋ ํ์(greedy) ์๊ณ ๋ฆฌ๋ฌ ๊ธฐ๋ฐ์ ์์ ํ ๋น ๊ธฐ์ ์ ์ค๊ณํ๋ค. ๊ณ ์ ์ด๋ ํ๊ฒฝ์์ ์์คํ
์ ์ก ์ฑ๋ฅ์ ์ถ์ ํ๊ธฐ ์ํด์๋ ์ฌ์ฉ์๋ค์ ๋ํ ์ ์ก ๋น ๊ฐ์ค์น์ ํ๋ ฌ์ ๋ํ ์ด๊ธฐํ ํจ์(hypergeometric function of a matrix argument)์ ๊ด๋ จ๋ ๋ณต์กํ ์ฐ์ฐ์ด ํ์ํ๋ค. ์ด ๋ฌธ์ ๋ฅผ ํด๊ฒฐํ๊ธฐ ์ํ์ฌ, ๋น ๊ฐ์ค์น๋ฅผ ๊ณต๊ฐ ์๊ด๋ ํ๋ ฌ์ ๊ณ ์ ๋ฐฉํฅ์ผ๋ก ๊ฒฐ์ ํ๊ณ , ์ด๊ธฐํ ํจ์๋ฅผ ์ฑ๋ ์๊ฐ ์๊ด๋์ ๋ํ ํจ์๋ก ๊ทผ์ฌํ๋ค. ์๊ธฐ ์ ์ก ์ฑ๋ฅ ์ถ์ ๋ฐฉ๋ฒ์ด ์ฑ๋์ ๊ณต๊ฐ ๋ฐ ์๊ฐ ์๊ด๋์๋ง ์์กดํ๋ค๋ ์ ์ ํ์ฉํ์ฌ, ์ฑ๋ ๊ณต๊ฐ ๋ฐ ์๊ฐ ์๊ด๋๊ฐ ํฌ๊ฒ ๋ณํํ ์ฌ์ฉ์๊ฐ ์กด์ฌํ ๋์ ํํ์ฌ ์ฌ์ฉ์๋ค์ ๋ํ ์์ ํ ๋น ์ํ๋ฅผ ๊ฐฑ์ ํ๋ ๋ฐฉ๋ฒ์ ์ ์ํ๋ค. ์คํ์ ํตํ์ฌ, ์ ์ ๊ธฐ๋ฒ์ด ๋ณต์กํ ์์คํ
์ ์ก ์ฑ๋ฅ์ ๊ธฐ๋ฐ์ผ๋ก ํ๋ ์์ ํ ๋น ๋ฐฉ๋ฒ๊ณผ ์ ์ฌํ ์์ ํ ๋น ์ฑ๋ฅ์ ๋ณด์ด๋ฉด์๋ ๊ณ์ฐ ๋ณต์ก๋๋ฅผ ํ๊ธฐ์ ์ผ๋ก ์ค์ด๋ ๊ฒ์ ๋ณด์ธ๋ค.Abstract i
Contents v
List of Figures vii
List of Tables ix
Chapter 1. Introduction 1
Chapter 2. M-MIMO systems in the presence of channel aging effect 9
Chapter 3. Estimation of channel correlation matrix 13
3.1. Previous works 14
3.2. Proposed scheme 19
3.3. Performance evaluation 29
Chapter 4. Mobility-aware signal transmission in m-MIMO systems 43
4.1. Previous works 44
4.2. Proposed scheme 46
4.3. Performance evaluation 62
Chapter 5. Mobility-aware resource allocation in m-MIMO systems 73
5.1. Sum-rate-based greedy algorithm 74
5.2. Proposed scheme 76
5.3. Performance evaluation 88
Chapter 6. Conclusions 99
Appendix 103
References 105
Korean Abstract 115
Acknowledgement 119Docto
The Road to Next-Generation Multiple Access: A 50-Year Tutorial Review
The evolution of wireless communications has been significantly influenced by
remarkable advancements in multiple access (MA) technologies over the past five
decades, shaping the landscape of modern connectivity. Within this context, a
comprehensive tutorial review is presented, focusing on representative MA
techniques developed over the past 50 years. The following areas are explored:
i) The foundational principles and information-theoretic capacity limits of
power-domain non-orthogonal multiple access (NOMA) are characterized, along
with its extension to multiple-input multiple-output (MIMO)-NOMA. ii) Several
MA transmission schemes exploiting the spatial domain are investigated,
encompassing both conventional space-division multiple access (SDMA)/MIMO-NOMA
systems and near-field MA systems utilizing spherical-wave propagation models.
iii) The application of NOMA to integrated sensing and communications (ISAC)
systems is studied. This includes an introduction to typical NOMA-based
downlink/uplink ISAC frameworks, followed by an evaluation of their performance
limits using a mutual information (MI)-based analytical framework. iv) Major
issues and research opportunities associated with the integration of MA with
other emerging technologies are identified to facilitate MA in next-generation
networks, i.e., next-generation multiple access (NGMA). Throughout the paper,
promising directions are highlighted to inspire future research endeavors in
the realm of MA and NGMA.Comment: 43 pages, 38 figures; Submitted to Proceedings of the IEE
MIMO designs for filter bank multicarrier and multiantenna systems based on OQAM
From the perspective of increasingly data rate requirements in mobile communications, it is deemed necessary to do further research so that the future goals can be reached. To that end, the radio-based communications are resorting to multicarrier modulations and spatial diversity. Until today, the orthogonal frequency division multiplexing (OFDM) modulation is regarded as the dominant technology. On one hand, the OFDM modulation is able to accommodate multiantenna configurations in a very straightforward manner. On the other hand, the poor stopband attenuation exhibited by the OFDM modulation, highlights that a definitely tight synchronization is required. In addition, the cyclic prefix (CP) has to be sufficiently long to avoid inter-block interference, which may substantially reduce the spectral efficiency.
In order to overcome the OFDM drawbacks, the filter bank multicarrier modulation based on OQAM (FBMC/OQAM) is introduced. This modulation does not need any CP and benefits from pulse shaping techniques. This aspect becomes crucial in cognitive radio networks and communication systems where nodes are unlikely to be synchronized. In principle, the poor frequency confinement exhibited by OFDM should tip the balance towards FBMC/OQAM. However, the perfect reconstruction property of FBMC/OQAM systems does not hold in presence of multipath fading. This means that the FBMC/OQAM modulation is affected by inter-symbol and inter-carrier interference, unless the channel is equalized to some extent. This observation highlights that the FBMC/OQAM extension to MIMO architectures becomes a big challenge due to the need to cope with both modulation- and multiantenna-induced interference.
The goal of this thesis is to study how the FBMC/OQAM modulation scheme can benefit from the degrees of freedom provided by the spatial dimension. In this regard, the first attempt to put the research on track is based on designing signal processing techniques at reception. In this case the emphasis is on single-input-multiple-output (SIMO) architectures. Next, the possibility of pre-equalizing the channel at transmission is investigated. It is considered that multiple antennas are placed at the transmit side giving rise to a multiple-input-single-output (MISO) configuration. In this scenario, the research is not only focused on counteracting the channel but also on distributing the power among subcarriers. Finally, the joint transmitter and receiver design in multiple-input-multiple-output (MIMO) communication systems is covered.
From the theory developed in this thesis, it is possible to conclude that the techniques originally devised in the OFDM context can be easily adapted to FBMC/OQAM systems if the channel frequency response is flat within the subchannels. However, metrics such as the peak to average power ratio or the sensitivity to the carrier frequency offset constraint the number of subcarriers, so that the frequency selectivity may be appreciable at the subcarrier level. Then, the flat fading assumption is not satisfied and the specificities of FBMC/OQAM systems have to be considered. In this situation, the proposed techniques allow FBMC/OQAM to remain competitive with OFDM. In addition, for some multiantenna configurations and propagation conditions FBMC/OQAM turns out to be the best choice. The simulation-based results together with the theoretical analysis conducted in this thesis contribute to make progress towards the application of FBMC/OQAM to MIMO channels. The signal processing techniques that are described in this dissertation allow designers to exploit the potentials of FBMC/OQAM and MIMO to improve the link reliability as well as the spectral efficiency
Downlink Achievable Rate Analysis for FDD Massive MIMO Systems
Multiple-Input Multiple-Output (MIMO) systems with large-scale transmit antenna arrays, often called massive MIMO, are a very promising direction for 5G due to their ability to increase capacity and enhance both spectrum and energy efficiency. To get the benefit of massive MIMO systems, accurate downlink channel state information at the transmitter (CSIT) is essential for downlink beamforming and resource allocation. Conventional approaches to obtain CSIT for FDD massive MIMO systems require downlink training and CSI feedback. However, such training will cause a large overhead for massive MIMO systems because of the large dimensionality of the channel matrix. In this dissertation, we improve the performance of FDD massive MIMO networks in terms of downlink training overhead reduction, by designing an efficient downlink beamforming method and developing a new algorithm to estimate the channel state information based on compressive sensing techniques. First, we design an efficient downlink beamforming method based on partial CSI. By exploiting the relationship between uplink direction of arrivals (DoAs) and downlink direction of departures (DoDs), we derive an expression for estimated downlink DoDs, which will be used for downlink beamforming. Second, By exploiting the sparsity structure of downlink channel matrix, we develop an algorithm that selects the best features from the measurement matrix to obtain efficient CSIT acquisition that can reduce the downlink training overhead compared with conventional LS/MMSE estimators. In both cases, we compare the performance of our proposed beamforming method with traditional methods in terms of downlink achievable rate and simulation results show that our proposed method outperform the traditional beamforming methods
Advanced Signal Processing Techniques for Two-Way Relaying Networks and Full-Duplex Communication Systems
๏ปฟSehr hohe Datenraten und stรคndig verfรผgbare Netzabdeckung in
zukรผnftigen drahtlosen Netzwerken erfordern neue Algorithmen auf der
physischen Schicht. Die Nutzung von Relais stellt ein vielversprechendes
Verfahren dar, da die Netzabdeckung gesteigert werden kann. Zusรคtzlich
steht hierdurch im Vergleich zu Kupfer- oder Glasfaserleitungen eine
preiswerte Lรถsung zur Anbindung an die Netzinfrastruktur zur Verfรผgung.
Traditionelle Einwege-Relais-Techniken (One-Way Relaying [OWR]) nutzen
Halbduplex-Verfahren (HD-Verfahren), welche das รbertragungssystem
ausbremst und zu spektralen Verlusten fรผhrt. Einerseits erlauben es
Zweiwege-Relais-Techniken (Two-Way Relaying [TWR]), simultan sowohl an das
Relais zu senden als auch von diesem zu empfangen, wodurch im Vergleich zu
OWR das Spektrum effizienter genutzt wird. Aus diesem Grunde untersuchen
wir Zweiwege-Relais und im Speziellen TWR-Systeme fรผr den
Mehrpaar-/Mehrnutzer-Betrieb unter Nutzung von Amplify-and-forward-Relais
(AF-Relais). Derartige Szenarien leiden unter Interferenzen zwischen Paaren
bzw. zwischen Nutzern. Um diesen Interferenzen Herr zu werden, werden
hochentwickelte Signalverarbeitungsalgorithmen โ oder in anderen Worten
rรคumliche Mehrfachzugriffsverfahren (Spatial Division Multiple Access
[SDMA]) โ benรถtigt. Andererseits kann der spektrale Verlust durch den
HD-Betrieb auch kompensiert werden, wenn das Relais im Vollduplexbetrieb
arbeitet. Nichtsdestotrotz ist ein FD-Gerรคt in der Praxis aufgrund starker
interner Selbstinterferenz (SI) und begrenztem Dynamikumfang des
Tranceivers schwer zu realisieren. Aus diesem Grunde sollten
fortschrittliche Verfahren zur SI-รnterdrรผckung entwickelt werden. Diese
Dissertation trรคgt diesen beiden Zielen Rechnung, indem optimale und/oder
effiziente algebraische Lรถsungen entwickelt werden, welche verschiedenen
Nutzenfunktionen, wie Summenrate und minimale Sendeleistung, maximieren.Im
ersten Teil studieren wir zunรคchst Mehrpaar-TWR-Netzwerke mit einem
einzelnen Mehrantennen-AF-Relais. Dieser Anwendungsfall kann auch so
betrachtet werden, dass sich mehrere verschiedene Dienstoperatoren Relais
und Spektrum teilen, wobei verschiedene Nutzerpaare zu verschiedenen
Dienstoperatoren gehรถren. Aktuelle Ansรคtzen zielen auf
Interferenzunterdrรผckung ab. Wir schlagen ein auf Projektion basiertes
Verfahren zur Trennung mehrerer Dienstoperatoren (projection based
separation of multiple operators [ProBaSeMO]) vor. ProBaSeMO ist leicht
anpassbar fรผr den Fall, dass jeder Nutzer mehrere Antennen besitzt oder
unterschiedliche Systemdesignkriterien angewendet werden mรผssen. Als
Bewertungsmaรstab fรผr ProBaSeMO entwickeln wir optimale Algorithmen zur
Maximierung der Summenrate, zur Minimierung der Sendeleistung am Relais
oder zur Maximierung des minimalen
Signal-zu-Interferenz-und-Rausch-Verhรคltnisses (Signal to Interference and
Noise Ratio [SINR]) am Nutzer. Zur Maximierung der Summenrate wurden
spezifische gradientenbasierte Methoden entwickelt, die unabhรคngig davon
sind, ob ein Nutzer mit einer oder mehr Antennen ausgestattet ist. Um im
Falle eines โWorst-Caseโ immer noch eine polynomielle Laufzeit zu
garantieren, entwickelten wir einen Algorithmus mit polynomieller Laufzeit.
Dieser ist inspiriert von der โPolynomial Time Difference of Convex
Functionsโ-Methode (POTDC-Methode). Bezรผglich der Summenrate des Systems
untersuchen wir zuletzt, welche Bedingungen erfรผllt sein mรผssen, um einen
Gewinn durch gemeinsames Nutzen zu erhalten. Hiernach untersuchen wir die
Maximierung der Summenrate eines Mehrpaar-TWR-Netzwerkes mit mehreren
Einantennen-AF-Relais und Einantennen-Nutzern. Das daraus resultierende
Problem der Summenraten-Maximierung, gebunden an eine bestimmte
Gesamtsendeleistung aller Relais im Netzwerk, ist รคhnlich dem des
vorangegangenen Szenarios. Dementsprechend kann eine optimale Lรถsung fรผr
das eine Szenario auch fรผr das jeweils andere Szenario genutzt werden.
Weiterhin werden basierend auf dem Polynomialzeitalgorithmus global
optimale Lรถsungen entwickelt. Diese Lรถsungen sind entweder an eine
maximale Gesamtsendeleistung aller Relais oder an eine maximale
Sendeleistung jedes einzelnen Relais gebunden. Zusรคtzlich entwickeln wir
suboptimale Lรถsungen, die effizient in ihrer Laufzeit sind und eine
Approximation der optimalen Lรถsung darstellen. Hiernach verlegen wir unser
Augenmerk auf ein Mehrpaar-TWR-Netzwerk mit mehreren Mehrantennen-AF-Relais
und mehreren Repeatern. Solch ein Szenario ist allgemeiner, da die
vorherigen beiden Szenarien als spezielle Realisierungen dieses Szenarios
aufgefasst werden kรถnnen. Das Interferenz-Management in diesem Szenario
ist herausfordernder aufgrund der vorhandenen Repeater.
Interferenzneutralisierung (IN) stellt eine Lรถsung dar, um diese Art
Interferenz zu handhaben. Im Zuge dessen werden notwendige und ausreichende
Bedingungen zur Aufhebung der Interferenz hergeleitet. Weiterhin wird ein
Framework entwickelt, dass verschiedene Systemnutzenfunktionen optimiert,
wobei IN im jeweiligen Netzwerk vorhanden sein kann oder auch nicht. Dies
ist unabhรคngig davon, ob die Relais einer maximalen Gesamtsendeleistung
oder einer individuellen maximalen Sendeleistung unterliegen. Letztendlich
entwickeln wir ein รbertragungsverfahren sowie ein Vorkodier- und
Dekodierverfahren fรผr Basisstationen (BS) in einem TWR-assistierten
Mehrbenutzer-MIMO-Downlink-Kanal. Im Vergleich mit dem
Mehrpaar-TWR-Netzwerk leidet dieses Szenario unter Interferenzen zwischen
den Kanรคlen. Wir entwickeln drei suboptimale Algorithmen, welche auf
Kanalinversion basieren. ProBaSeMO und โZero-Forcing Dirty Paper
Codingโ (ZFDPC), welche eine geringe Zeitkomplexitรคt aufweisen, schaffen
eine Balance zwischen Leistungsfรคhigkeit und Komplexitรคt. Zusรคtzlich
gibt es jeweils nur geringe Einbrรผche in stark beanspruchten
Kommunikationssystemen.Im zweiten Teil untersuchen wir Techniken zur
SI-Unterdrรผckung, um den FD-Gewinn in einem Punkt-zu-Punkt-System
auszunutzen. Zunรคchst entwickeln wir ein รbertragungsverfahren, dass auf
SI Rรผcksicht nimmt und die SI-Unterdrรผckung gegen den Multiplexgewinn
abwรคgt. Die besten Ergebnisse werden durch die perfekte Kenntnis des
Kanals erzielt, was praktisch nicht genau der Fall ist. Aus diesem Grund
werden รbertragungstechniken fรผr den โWorst Caseโ entwickelt, die den
Kanalschรคtzfehlern Rechnung tragen. Diese Fehler werden deterministisch
modelliert und durch Ellipsoide beschrรคnkt. In praktischen Szenarien ist
der HF-Schaltkreise nicht perfekt. Dies hat Einfluss auf die Verfahren zur
SI-Unterdrรผckung und fรผhrt zu einer Restselbstinterferenz. Wir entwickeln
effiziente รbertragungstechniken mittels Beamforming, welche auf dem
Signal-zu-Verlust-und-Rausch-Verhรคltnis (signal to leakage plus noise
ratio [SLNR]) aufbauen, um Unvollkommenheiten der HF-Schaltkreise
auszugleichen. Zusรคtzlich kรถnnen alle Designkonzepte auf FD-OWR-Systeme
erweitert werden.To enable ultra-high data rate and ubiquitous coverage in future wireless
networks, new physical layer techniques are desired. Relaying is a
promising technique for future wireless networks since it can boost the
coverage and can provide low cost wireless backhauling solutions, as
compared to traditional wired backhauling solutions via fiber and copper.
Traditional one-way relaying (OWR) techniques suffer from the spectral loss
due to the half-duplex (HD) operation at the relay. On one hand, two-way
relaying (TWR) allows the communication partners to transmit to and/or
receive from the relay simultaneously and thus uses the spectrum more
efficiently than OWR. Therefore, we study two-way relays and more
specifically multi-pair/multi-user TWR systems with amplify-and-forward
(AF) relays. These scenarios suffer from inter-pair or inter-user
interference. To deal with the interference, advanced signal processing
algorithms, in other words, spatial division multiple access (SDMA)
techniques, are desired. On the other hand, if the relay is a full-duplex
(FD) relay, the spectral loss due to a HD operation can also be
compensated. However, in practice, a FD device is hard to realize due to
the strong loop-back self-interference and the limited dynamic range at the
transceiver. Thus, advanced self-interference suppression techniques should
be developed. This thesis contributes to the two goals by developing
optimal and/or efficient algebraic solutions for different scenarios
subject to different utility functions of the system, e.g., sum rate
maximization and transmit power minimization. In the first part of this
thesis, we first study a multi-pair TWR network with a multi-antenna AF
relay. This scenario can be also treated as the sharing of the relay and
the spectrum among multiple operators assuming that different pairs of
users belong to different operators. Existing approaches focus on
interference suppression. We propose a projection based separation of
multiple operators (ProBaSeMO) scheme, which can be easily extended when
each user has multiple antennas or when different system design criteria
are applied. To benchmark the ProBaSeMO scheme, we develop optimal relay
transmit strategies to maximize the system sum rate, minimize the required
transmit power at the relay, or maximize the minimum signal to interference
plus noise ratio (SINR) of the users. Specifically for the sum rate
maximization problem, gradient based methods are developed regardless
whether each user has a single antenna or multiple antennas. To guarantee a
worst-case polynomial time solution, we also develop a polynomial time
algorithm which has been inspired by the polynomial time difference of
convex functions (POTDC) method. Finally, we analyze the conditions for
obtaining the sharing gain in terms of the sum rate. Then we study the sum
rate maximization problem of a multi-pair TWR network with multiple single
antenna AF relays and single antenna users. The resulting sum rate
maximization problem, subject to a total transmit power constraint of the
relays in the network, yields a similar problem structure as in the
previous scenario. Therefore the optimal solution for one scenario can be
used for the other. Moreover, a global optimal solution, which is based on
the polyblock approach, and several suboptimal solutions, which are more
computationally efficient and approximate the optimal solution, are
developed when there is a total transmit power constraint of the relays in
the network or each relay has its own transmit power constraint. We then
shift our focus to a multi-pair TWR network with multiple multi-antenna AF
relays and multiple dumb repeaters. This scenario is more general because
the previous two scenarios can be seen as special realizations of this
scenario. The interference management in this scenario is more challenging
due to the existence of the repeaters. Interference neutralization (IN) is
a solution for dealing with this kind of interference. Thereby, necessary
and sufficient conditions for neutralizing the interference are derived.
Moreover, a general framework to optimize different system utility
functions in this network with or without IN is developed regardless
whether the AF relays in the network have a total transmit power limit or
individual transmit power limits. Finally, we develop the relay transmit
strategy as well as base station (BS) precoding and decoding schemes for a
TWR assisted multi-user MIMO (MU-MIMO) downlink channel. Compared to the
multi-pair TWR network, this scenario suffers from the co-channel
interference. We develop three suboptimal algorithms which are based on
channel inversion, ProBaSeMO and zero-forcing dirty paper coding (ZFDPC),
which has a low computational complexity, provides a balance between the
performance and the complexity, and suffers only a little when the system
is heavily loaded, respectively.In the second part of this thesis, we
investigate self-interference (SI) suppression techniques to exploit the FD
gain for a point-to-point MIMO system. We first develop SI aware transmit
strategies, which provide a balance between the SI suppression and the
multiplexing gain of the system. To get the best performance, perfect
channel state information (CSI) is needed, which is imperfect in practice.
Thus, worst case transmit strategies to combat the imperfect CSI are
developed, where the CSI errors are modeled deterministically and bounded
by ellipsoids. In real word applications, the RF chain is imperfect. This
affects the performance of the SI suppression techniques and thus results
in residual SI. We develop efficient transmit beamforming techniques, which
are based on the signal to leakage plus noise ratio (SLNR) criterion, to
deal with the imperfections in the RF chain. All the proposed design
concepts can be extended to FD OWR systems
Resource Allocation in Multi-user MIMO Networks: Interference Management and Cooperative Communications
Nowadays, wireless communications are becoming so tightly integrated in our daily lives, especially with the global spread of laptops, tablets and smartphones. This has paved the way to dramatically increasing wireless network dimensions in terms of subscribers and amount of flowing data. Therefore, the two important fundamental requirements for the future 5G wireless networks are abilities to support high data traffic and exceedingly low latency. A likely candidate to fulfill these requirements is multicell multi-user multi-input multiple-output (MU-MIMO); also termed as coordinated multi-point (CoMP) transmission and reception. To achieve the highest possible performance in MU-MIMO networks, a properly designed resource allocation algorithm is needed. Moreover, with the rapidly growing data traffic, interference has become a major limitation in wireless networks. Interference alignment (IA) has been shown to significantly manage the interference and improve the network performance. However, how practically use IA to mitigate interference in a downlink MU-MIMO network still remains an open problem. In this dissertation, we improve the performance of MU-MIMO networks in terms of spectral efficiency, by designing and developing new beamforming algorithms that can efficiently mitigate the interference and allocate the resources. Then we mathematically analyze the performance improvement of MUMIMO networks employing proposed techniques. Fundamental relationships between network parameters and the network performance is revealed, which provide guidance on the wireless networks design. Finally, system level simulations are conducted to investigate the performance of the proposed strategies