243 research outputs found
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
Spectrum Sharing in mmWave Cellular Networks via Cell Association, Coordination, and Beamforming
This paper investigates the extent to which spectrum sharing in mmWave
networks with multiple cellular operators is a viable alternative to
traditional dedicated spectrum allocation. Specifically, we develop a general
mathematical framework by which to characterize the performance gain that can
be obtained when spectrum sharing is used, as a function of the underlying
beamforming, operator coordination, bandwidth, and infrastructure sharing
scenarios. The framework is based on joint beamforming and cell association
optimization, with the objective of maximizing the long-term throughput of the
users. Our asymptotic and non-asymptotic performance analyses reveal five key
points: (1) spectrum sharing with light on-demand intra- and inter-operator
coordination is feasible, especially at higher mmWave frequencies (for example,
73 GHz), (2) directional communications at the user equipment substantially
alleviate the potential disadvantages of spectrum sharing (such as higher
multiuser interference), (3) large numbers of antenna elements can reduce the
need for coordination and simplify the implementation of spectrum sharing, (4)
while inter-operator coordination can be neglected in the large-antenna regime,
intra-operator coordination can still bring gains by balancing the network
load, and (5) critical control signals among base stations, operators, and user
equipment should be protected from the adverse effects of spectrum sharing, for
example by means of exclusive resource allocation. The results of this paper,
and their extensions obtained by relaxing some ideal assumptions, can provide
important insights for future standardization and spectrum policy.Comment: 15 pages. To appear in IEEE JSAC Special Issue on Spectrum Sharing
and Aggregation for Future Wireless Network
Signal Processing and Learning for Next Generation Multiple Access in 6G
Wireless communication systems to date primarily rely on the orthogonality of
resources to facilitate the design and implementation, from user access to data
transmission. Emerging applications and scenarios in the sixth generation (6G)
wireless systems will require massive connectivity and transmission of a deluge
of data, which calls for more flexibility in the design concept that goes
beyond orthogonality. Furthermore, recent advances in signal processing and
learning have attracted considerable attention, as they provide promising
approaches to various complex and previously intractable problems of signal
processing in many fields. This article provides an overview of research
efforts to date in the field of signal processing and learning for
next-generation multiple access, with an emphasis on massive random access and
non-orthogonal multiple access. The promising interplay with new technologies
and the challenges in learning-based NGMA are discussed
Reliable Physical Layer Network Coding
When two or more users in a wireless network transmit simultaneously, their
electromagnetic signals are linearly superimposed on the channel. As a result,
a receiver that is interested in one of these signals sees the others as
unwanted interference. This property of the wireless medium is typically viewed
as a hindrance to reliable communication over a network. However, using a
recently developed coding strategy, interference can in fact be harnessed for
network coding. In a wired network, (linear) network coding refers to each
intermediate node taking its received packets, computing a linear combination
over a finite field, and forwarding the outcome towards the destinations. Then,
given an appropriate set of linear combinations, a destination can solve for
its desired packets. For certain topologies, this strategy can attain
significantly higher throughputs over routing-based strategies. Reliable
physical layer network coding takes this idea one step further: using
judiciously chosen linear error-correcting codes, intermediate nodes in a
wireless network can directly recover linear combinations of the packets from
the observed noisy superpositions of transmitted signals. Starting with some
simple examples, this survey explores the core ideas behind this new technique
and the possibilities it offers for communication over interference-limited
wireless networks.Comment: 19 pages, 14 figures, survey paper to appear in Proceedings of the
IEE
An Analysis of Two-User Uplink Asynchronous Non-Orthogonal Multiple Access Systems
Recent studies have numerically demonstrated the possible advantages of the
asynchronous non-orthogonal multiple access (ANOMA) over the conventional
synchronous non-orthogonal multiple access (NOMA). The ANOMA makes use of the
oversampling technique by intentionally introducing a timing mismatch between
symbols of different users. Focusing on a two-user uplink system, for the first
time, we analytically prove that the ANOMA with a sufficiently large frame
length can always outperform the NOMA in terms of the sum throughput. To this
end, we derive the expression for the sum throughput of the ANOMA as a function
of signal-to-noise ratio (SNR), frame length, and normalized timing mismatch.
Based on the derived expression, we find that users should transmit at full
powers to maximize the sum throughput. In addition, we obtain the optimal
timing mismatch as the frame length goes to infinity. Moreover, we
comprehensively study the impact of timing error on the ANOMA throughput
performance. Two types of timing error, i.e., the synchronization timing error
and the coordination timing error, are considered. We derive the throughput
loss incurred by both types of timing error and find that the synchronization
timing error has a greater impact on the throughput performance compared to the
coordination timing error
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