520 research outputs found
Multipath Multiplexing for Capacity Enhancement in SIMO Wireless Systems
This paper proposes a novel and simple orthogonal faster than Nyquist (OFTN)
data transmission and detection approach for a single input multiple output
(SIMO) system. It is assumed that the signal having a bandwidth is
transmitted through a wireless channel with multipath components. Under
this assumption, the current paper provides a novel and simple OFTN
transmission and symbol-by-symbol detection approach that exploits the
multiplexing gain obtained by the multipath characteristic of wideband wireless
channels. It is shown that the proposed design can achieve a higher
transmission rate than the existing one (i.e., orthogonal frequency division
multiplexing (OFDM)). Furthermore, the achievable rate gap between the proposed
approach and that of the OFDM increases as the number of receiver antennas
increases for a fixed value of . This implies that the performance gain of
the proposed approach can be very significant for a large-scale multi-antenna
wireless system. The superiority of the proposed approach is shown
theoretically and confirmed via numerical simulations. {Specifically, we have
found {upper-bound average} rates of 15 bps/Hz and 28 bps/Hz with the OFDM and
proposed approaches, respectively, in a Rayleigh fading channel with 32 receive
antennas and signal to noise ratio (SNR) of 15.3 dB. The extension of the
proposed approach for different system setups and associated research problems
is also discussed.Comment: IEEE Transactions on Wireless Communication
A Vision and Framework for the High Altitude Platform Station (HAPS) Networks of the Future
A High Altitude Platform Station (HAPS) is a network node that operates in
the stratosphere at an of altitude around 20 km and is instrumental for
providing communication services. Precipitated by technological innovations in
the areas of autonomous avionics, array antennas, solar panel efficiency
levels, and battery energy densities, and fueled by flourishing industry
ecosystems, the HAPS has emerged as an indispensable component of
next-generations of wireless networks. In this article, we provide a vision and
framework for the HAPS networks of the future supported by a comprehensive and
state-of-the-art literature review. We highlight the unrealized potential of
HAPS systems and elaborate on their unique ability to serve metropolitan areas.
The latest advancements and promising technologies in the HAPS energy and
payload systems are discussed. The integration of the emerging Reconfigurable
Smart Surface (RSS) technology in the communications payload of HAPS systems
for providing a cost-effective deployment is proposed. A detailed overview of
the radio resource management in HAPS systems is presented along with
synergistic physical layer techniques, including Faster-Than-Nyquist (FTN)
signaling. Numerous aspects of handoff management in HAPS systems are
described. The notable contributions of Artificial Intelligence (AI) in HAPS,
including machine learning in the design, topology management, handoff, and
resource allocation aspects are emphasized. The extensive overview of the
literature we provide is crucial for substantiating our vision that depicts the
expected deployment opportunities and challenges in the next 10 years
(next-generation networks), as well as in the subsequent 10 years
(next-next-generation networks).Comment: To appear in IEEE Communications Surveys & Tutorial
Waveform Advancements and Synchronization Techniques for Generalized Frequency Division Multiplexing
To enable a new level of connectivity among machines as well as between people and machines, future wireless applications will demand higher requirements on data rates, response time, and reliability from the communication system. This will lead to a different system design, comprising a wide range of deployment scenarios. One important aspect is the evolution of physical layer (PHY), specifically the waveform modulation. The novel generalized frequency division multiplexing (GFDM) technique is a prominent proposal for a flexible block filtered multicarrier modulation.
This thesis introduces an advanced GFDM concept that enables the emulation of other prominent waveform candidates in scenarios where they perform best. Hence, a unique modulation framework is presented that is capable of addressing a wide range of scenarios and to upgrade the PHY for 5G networks. In particular, for a subset of system parameters of the modulation framework, the problem of symbol time offset (STO) and carrier frequency offset (CFO) estimation is investigated and synchronization approaches, which can operate in burst and continuous transmissions, are designed.
The first part of this work presents the modulation principles of prominent 5G candidate waveforms and then focuses on the GFDM basic and advanced attributes. The GFDM concept is extended towards the use of OQAM, introducing the novel frequency-shift OQAM-GFDM, and a new low complexity model based on signal processing carried out in the time domain. A new prototype filter proposal highlights the benefits obtained in terms of a reduced out-of-band (OOB) radiation and more attractive hardware implementation cost. With proper parameterization of the advanced GFDM, the achieved gains are applicable to other filtered OFDM waveforms.
In the second part, a search approach for estimating STO and CFO in GFDM is evaluated. A self-interference metric is proposed to quantify the effective SNR penalty caused by the residual time and frequency misalignment or intrinsic inter-symbol interference (ISI) and inter-carrier interference (ICI) for arbitrary pulse shape design in GFDM. In particular, the ICI can be used as a non-data aided approach for frequency estimation. Then, GFDM training sequences, defined either as an isolated preamble or embedded as a midamble or pseudo-circular pre/post-amble, are designed. Simulations show better OOB emission and good estimation results, either comparable or superior, to state-of-the-art OFDM system in wireless channels
Is FFT Fast Enough for Beyond-5G Communications?
This paper studies the impact of computational complexity on the throughput
limits of different Discrete Fourier Transform (DFT) algorithms (such as FFT
and straightforward DFT) in the context of OFDM-based waveforms. Based on the
spectro-computational complexity (SC) analysis, it is verified that the
complexity of an -point FFT grows faster than the number of bits in the OFDM
symbol. Thus, the useful throughput of FFT nullifies on . Also, because FFT
demands to be a power of two (), the spectrum widening leads to
an exponential complexity on , i.e. . To overcome these
limitations, we consider the alternative frequency-time transform formulation
of Vector OFDM (V-OFDM), in which an -point FFT is replaced by
() smaller -point FFTs to mitigate the cyclic prefix overhead of
OFDM. Building on that, we replace FFT by the straightforward DFT algorithm to
release the V-OFDM parameters from growing as powers of two and to benefit from
flexible numerology (e.g., , ). Besides, by setting to
, the resulting solution can run linearly on (rather than
exponentially on ) while sustaining a non null throughput as grows.Comment: This work has been submitted to the IEEE for possible publication.
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Spectrally and Energy Efficient Wireless Communications: Signal and System Design, Mathematical Modelling and Optimisation
This thesis explores engineering studies and designs aiming to meeting the requirements of enhancing capacity and energy efficiency for next generation communication networks. Challenges of spectrum scarcity and energy constraints are addressed and new technologies are proposed, analytically investigated and examined.
The thesis commences by reviewing studies on spectrally and energy-efficient techniques, with a special focus on non-orthogonal multicarrier modulation, particularly spectrally efficient frequency division multiplexing (SEFDM). Rigorous theoretical and mathematical modelling studies of SEFDM are presented. Moreover, to address the potential application of SEFDM under the 5th generation new radio (5G NR) heterogeneous numerologies, simulation-based studies of SEFDM coexisting with orthogonal frequency division multiplexing (OFDM) are conducted. New signal formats and corresponding transceiver structure are designed, using a Hilbert transform filter pair for shaping pulses. Detailed modelling and numerical investigations show that the proposed signal doubles spectral efficiency without performance degradation, with studies of two signal formats; uncoded narrow-band internet of things (NB-IoT) signals and unframed turbo coded multi-carrier signals. The thesis also considers using constellation shaping techniques and SEFDM for capacity enhancement in 5G system. Probabilistic shaping for SEFDM is proposed and modelled to show both transmission energy reduction and bandwidth saving with advantageous flexibility for data rate adaptation. Expanding on constellation shaping to improve performance further, a comparative study of multidimensional modulation techniques is carried out. A four-dimensional signal, with better noise immunity is investigated, for which metaheuristic optimisation algorithms are studied, developed, and conducted to optimise bit-to-symbol mapping. Finally, a specially designed machine learning technique for signal and system design in physical layer communications is proposed, utilising the application of autoencoder-based end-to-end learning. Multidimensional signal modulation with multidimensional constellation shaping is proposed and optimised by using machine learning techniques, demonstrating significant improvement in spectral and energy efficiencies
Multidimensional Index Modulation for 5G and Beyond Wireless Networks
This study examines the flexible utilization of existing IM techniques in a
comprehensive manner to satisfy the challenging and diverse requirements of 5G
and beyond services. After spatial modulation (SM), which transmits information
bits through antenna indices, application of IM to orthogonal frequency
division multiplexing (OFDM) subcarriers has opened the door for the extension
of IM into different dimensions, such as radio frequency (RF) mirrors, time
slots, codes, and dispersion matrices. Recent studies have introduced the
concept of multidimensional IM by various combinations of one-dimensional IM
techniques to provide higher spectral efficiency (SE) and better bit error rate
(BER) performance at the expense of higher transmitter (Tx) and receiver (Rx)
complexity. Despite the ongoing research on the design of new IM techniques and
their implementation challenges, proper use of the available IM techniques to
address different requirements of 5G and beyond networks is an open research
area in the literature. For this reason, we first provide the dimensional-based
categorization of available IM domains and review the existing IM types
regarding this categorization. Then, we develop a framework that investigates
the efficient utilization of these techniques and establishes a link between
the IM schemes and 5G services, namely enhanced mobile broadband (eMBB),
massive machine-type communications (mMTC), and ultra-reliable low-latency
communication (URLLC). Additionally, this work defines key performance
indicators (KPIs) to quantify the advantages and disadvantages of IM techniques
in time, frequency, space, and code dimensions. Finally, future recommendations
are given regarding the design of flexible IM-based communication systems for
5G and beyond wireless networks.Comment: This work has been submitted to Proceedings of the IEEE for possible
publicatio
Sparse Signal Processing Concepts for Efficient 5G System Design
As it becomes increasingly apparent that 4G will not be able to meet the
emerging demands of future mobile communication systems, the question what
could make up a 5G system, what are the crucial challenges and what are the key
drivers is part of intensive, ongoing discussions. Partly due to the advent of
compressive sensing, methods that can optimally exploit sparsity in signals
have received tremendous attention in recent years. In this paper we will
describe a variety of scenarios in which signal sparsity arises naturally in 5G
wireless systems. Signal sparsity and the associated rich collection of tools
and algorithms will thus be a viable source for innovation in 5G wireless
system design. We will discribe applications of this sparse signal processing
paradigm in MIMO random access, cloud radio access networks, compressive
channel-source network coding, and embedded security. We will also emphasize
important open problem that may arise in 5G system design, for which sparsity
will potentially play a key role in their solution.Comment: 18 pages, 5 figures, accepted for publication in IEEE Acces
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