5,412 research outputs found
Asymptotically Optimal Multiple-access Communication via Distributed Rate Splitting
We consider the multiple-access communication problem in a distributed
setting for both the additive white Gaussian noise channel and the discrete
memoryless channel. We propose a scheme called Distributed Rate Splitting to
achieve the optimal rates allowed by information theory in a distributed
manner. In this scheme, each real user creates a number of virtual users via a
power/rate splitting mechanism in the M-user Gaussian channel or via a random
switching mechanism in the M-user discrete memoryless channel. At the receiver,
all virtual users are successively decoded. Compared with other multiple-access
techniques, Distributed Rate Splitting can be implemented with lower complexity
and less coordination. Furthermore, in a symmetric setting, we show that the
rate tuple achieved by this scheme converges to the maximum equal rate point
allowed by the information-theoretic bound as the number of virtual users per
real user tends to infinity. When the capacity regions are asymmetric, we show
that a point on the dominant face can be achieved asymptotically. Finally, when
there is an unequal number of virtual users per real user, we show that
differential user rate requirements can be accommodated in a distributed
fashion.Comment: Submitted to the IEEE Transactions on Information Theory. 15 Page
Throughput Optimization for Massive MIMO Systems Powered by Wireless Energy Transfer
This paper studies a wireless-energy-transfer (WET) enabled massive
multiple-input-multiple-output (MIMO) system (MM) consisting of a hybrid
data-and-energy access point (H-AP) and multiple single-antenna users. In the
WET-MM system, the H-AP is equipped with a large number of antennas and
functions like a conventional AP in receiving data from users, but additionally
supplies wireless power to the users. We consider frame-based transmissions.
Each frame is divided into three phases: the uplink channel estimation (CE)
phase, the downlink WET phase, as well as the uplink wireless information
transmission (WIT) phase. Firstly, users use a fraction of the previously
harvested energy to send pilots, while the H-AP estimates the uplink channels
and obtains the downlink channels by exploiting channel reciprocity. Next, the
H-AP utilizes the channel estimates just obtained to transfer wireless energy
to all users in the downlink via energy beamforming. Finally, the users use a
portion of the harvested energy to send data to the H-AP simultaneously in the
uplink (reserving some harvested energy for sending pilots in the next frame).
To optimize the throughput and ensure rate fairness, we consider the problem of
maximizing the minimum rate among all users. In the large- regime, we obtain
the asymptotically optimal solutions and some interesting insights for the
optimal design of WET-MM system. We define a metric, namely, the massive MIMO
degree-of-rate-gain (MM-DoRG), as the asymptotic UL rate normalized by
. We show that the proposed WET-MM system is optimal in terms of
MM-DoRG, i.e., it achieves the same MM-DoRG as the case with ideal CE.Comment: 15 double-column pages, 6 figures, 1 table, to appear in IEEE JSAC in
February 2015, special issue on wireless communications powered by energy
harvesting and wireless energy transfe
Multiple Description Quantization via Gram-Schmidt Orthogonalization
The multiple description (MD) problem has received considerable attention as
a model of information transmission over unreliable channels. A general
framework for designing efficient multiple description quantization schemes is
proposed in this paper. We provide a systematic treatment of the El Gamal-Cover
(EGC) achievable MD rate-distortion region, and show that any point in the EGC
region can be achieved via a successive quantization scheme along with
quantization splitting. For the quadratic Gaussian case, the proposed scheme
has an intrinsic connection with the Gram-Schmidt orthogonalization, which
implies that the whole Gaussian MD rate-distortion region is achievable with a
sequential dithered lattice-based quantization scheme as the dimension of the
(optimal) lattice quantizers becomes large. Moreover, this scheme is shown to
be universal for all i.i.d. smooth sources with performance no worse than that
for an i.i.d. Gaussian source with the same variance and asymptotically optimal
at high resolution. A class of low-complexity MD scalar quantizers in the
proposed general framework also is constructed and is illustrated
geometrically; the performance is analyzed in the high resolution regime, which
exhibits a noticeable improvement over the existing MD scalar quantization
schemes.Comment: 48 pages; submitted to IEEE Transactions on Information Theor
Distributed Full-duplex via Wireless Side Channels: Bounds and Protocols
In this paper, we study a three-node full-duplex network, where a base
station is engaged in simultaneous up- and downlink communication in the same
frequency band with two half-duplex mobile nodes. To reduce the impact of
inter- node interference between the two mobile nodes on the system capacity,
we study how an orthogonal side-channel between the two mobile nodes can be
leveraged to achieve full-duplex-like multiplexing gains. We propose and
characterize the achievable rates of four distributed full-duplex schemes,
labeled bin-and- cancel, compress-and-cancel, estimate-and-cancel and decode-
and-cancel. Of the four, bin-and-cancel is shown to achieve within 1 bit/s/Hz
of the capacity region for all values of channel parameters. In contrast, the
other three schemes achieve the near-optimal performance only in certain
regimes of channel values. Asymptotic multiplexing gains of all proposed
schemes are derived to show that the side-channel is extremely effective in
regimes where inter-node interference has the highest impact.Comment: Published in IEEE Transactions on Wireless Communications, August
201
Cooperative Multi-Cell Networks: Impact of Limited-Capacity Backhaul and Inter-Users Links
Cooperative technology is expected to have a great impact on the performance
of cellular or, more generally, infrastructure networks. Both multicell
processing (cooperation among base stations) and relaying (cooperation at the
user level) are currently being investigated. In this presentation, recent
results regarding the performance of multicell processing and user cooperation
under the assumption of limited-capacity interbase station and inter-user
links, respectively, are reviewed. The survey focuses on related results
derived for non-fading uplink and downlink channels of simple cellular system
models. The analytical treatment, facilitated by these simple setups, enhances
the insight into the limitations imposed by limited-capacity constraints on the
gains achievable by cooperative techniques
Sign-Compute-Resolve for Tree Splitting Random Access
We present a framework for random access that is based on three elements:
physical-layer network coding (PLNC), signature codes and tree splitting. In
presence of a collision, physical-layer network coding enables the receiver to
decode, i.e. compute, the sum of the packets that were transmitted by the
individual users. For each user, the packet consists of the user's signature,
as well as the data that the user wants to communicate. As long as no more than
K users collide, their identities can be recovered from the sum of their
signatures. This framework for creating and transmitting packets can be used as
a fundamental building block in random access algorithms, since it helps to
deal efficiently with the uncertainty of the set of contending terminals. In
this paper we show how to apply the framework in conjunction with a
tree-splitting algorithm, which is required to deal with the case that more
than K users collide. We demonstrate that our approach achieves throughput that
tends to 1 rapidly as K increases. We also present results on net data-rate of
the system, showing the impact of the overheads of the constituent elements of
the proposed protocol. We compare the performance of our scheme with an upper
bound that is obtained under the assumption that the active users are a priori
known. Also, we consider an upper bound on the net data-rate for any PLNC based
strategy in which one linear equation per slot is decoded. We show that already
at modest packet lengths, the net data-rate of our scheme becomes close to the
second upper bound, i.e. the overhead of the contention resolution algorithm
and the signature codes vanishes.Comment: This is an extended version of arXiv:1409.6902. Accepted for
publication in the IEEE Transactions on Information Theor
A Rate-Splitting Approach to Fading Channels with Imperfect Channel-State Information
As shown by M\'edard, the capacity of fading channels with imperfect
channel-state information (CSI) can be lower-bounded by assuming a Gaussian
channel input with power and by upper-bounding the conditional entropy
by the entropy of a Gaussian random variable with variance
equal to the linear minimum mean-square error in estimating from
. We demonstrate that, using a rate-splitting approach, this lower
bound can be sharpened: by expressing the Gaussian input as the sum of two
independent Gaussian variables and and by applying M\'edard's lower
bound first to bound the mutual information between and while
treating as noise, and by applying it a second time to the mutual
information between and while assuming to be known, we obtain a
capacity lower bound that is strictly larger than M\'edard's lower bound. We
then generalize this approach to an arbitrary number of layers, where
is expressed as the sum of independent Gaussian random variables of
respective variances , summing up to . Among
all such rate-splitting bounds, we determine the supremum over power
allocations and total number of layers . This supremum is achieved
for and gives rise to an analytically expressible capacity lower
bound. For Gaussian fading, this novel bound is shown to converge to the
Gaussian-input mutual information as the signal-to-noise ratio (SNR) grows,
provided that the variance of the channel estimation error tends to
zero as the SNR tends to infinity.Comment: 28 pages, 8 figures, submitted to IEEE Transactions on Information
Theory. Revised according to first round of review
Multiple-Description Coding by Dithered Delta-Sigma Quantization
We address the connection between the multiple-description (MD) problem and
Delta-Sigma quantization. The inherent redundancy due to oversampling in
Delta-Sigma quantization, and the simple linear-additive noise model resulting
from dithered lattice quantization, allow us to construct a symmetric and
time-invariant MD coding scheme. We show that the use of a noise shaping filter
makes it possible to trade off central distortion for side distortion.
Asymptotically as the dimension of the lattice vector quantizer and order of
the noise shaping filter approach infinity, the entropy rate of the dithered
Delta-Sigma quantization scheme approaches the symmetric two-channel MD
rate-distortion function for a memoryless Gaussian source and MSE fidelity
criterion, at any side-to-central distortion ratio and any resolution. In the
optimal scheme, the infinite-order noise shaping filter must be minimum phase
and have a piece-wise flat power spectrum with a single jump discontinuity. An
important advantage of the proposed design is that it is symmetric in rate and
distortion by construction, so the coding rates of the descriptions are
identical and there is therefore no need for source splitting.Comment: Revised, restructured, significantly shortened and minor typos has
been fixed. Accepted for publication in the IEEE Transactions on Information
Theor
Sign-Compute-Resolve for Random Access
We present an approach to random access that is based on three elements:
physical-layer network coding, signature codes and tree splitting. Upon
occurrence of a collision, physical-layer network coding enables the receiver
to decode the sum of the information that was transmitted by the individual
users. For each user this information consists of the data that the user wants
to communicate as well as the user's signature. As long as no more than
users collide, their identities can be recovered from the sum of their
signatures. A splitting protocol is used to deal with the case that more than
users collide. We measure the performance of the proposed method in terms
of user resolution rate as well as overall throughput of the system. The
results show that our approach significantly increases the performance of the
system even compared to coded random access, where collisions are not wasted,
but are reused in successive interference cancellation.Comment: Accepted for presentation at 52nd Annual Allerton Conference on
Communication, Control, and Computin
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