90 research outputs found
The Price of Updating the Control Plane in Information-Centric Networks
We are studying some fundamental properties of the interface between control
and data planes in Information-Centric Networks. We try to evaluate the traffic
between these two planes based on allowing a minimum level of acceptable
distortion in the network state representation in the control plane. We apply
our framework to content distribution, and see how we can compute the overhead
of maintaining the location of content in the control plane. This is of
importance to evaluate content-oriented network architectures: we identify
scenarios where the cost of updating the control plane for content routing
overwhelms the benefit of fetching a nearby copy. We also show how to minimize
the cost of this overhead when associating costs to peering traffic and to
internal traffic for operator-driven CDNs.Comment: 10 pages, 12 figure
Capacity of Cellular Networks with Femtocache
The capacity of next generation of cellular networks using femtocaches is
studied when multihop communications and decentralized cache placement are
considered. We show that the storage capability of future network User
Terminals (UT) can be effectively used to increase the capacity in random
decentralized uncoded caching. We further propose a random decentralized coded
caching scheme which achieves higher capacity results than the random
decentralized uncoded caching. The result shows that coded caching which is
suitable for systems with limited storage capabilities can improve the capacity
of cellular networks by a factor of log(n) where n is the number of nodes
served by the femtocache.Comment: 6 pages, 2 figures, presented at Infocom Workshops on 5G and beyond,
San Francisco, CA, April 201
On the Power Allocation Limits for Downlink Multi-user NOMA with QoS
The fundamental power allocation requirements for NOMA systems with minimum
quality of service (QoS) requirements are investigated. For any minimum QoS
rate , the limits on the power allocation coefficients for each user are
derived, such that any power allocation coefficient outside of these limits
creates an outage with probability equal to 1. The power allocation
coefficients that facilitate each user's success of performing successive
interference cancellation (SIC) and decoding its own signal are derived, and
are found to depend only on the target rate and the number of total users
. It is then proven that using these power allocation coefficients create
the same outage event as if using orthogonal multiple access (OMA), which
proves that the outage performance of NOMA with a fixed-power scheme can
matched that of OMA for all users simultaneously. Simulations confirm the
theoretical results, and also demonstrate that a power allocation strategy
exists that can improve the outage performance of NOMA over OMA, even with a
fixed-power strategy.Comment: Presented at Internation Conference on Communications (ICC) 2018
Wireless Communication Symposium, 5 pages long, 2 figure
An ML-assisted OTFS vs. OFDM adaptable modem
The Orthogonal-Time-Frequency-Space (OTFS) signaling is known to be resilient
to doubly-dispersive channels, which impacts high mobility scenarios. On the
other hand, the Orthogonal-Frequency-Division-Multiplexing (OFDM) waveforms
enjoy the benefits of the reuse of legacy architectures, simplicity of receiver
design, and low-complexity detection. Several studies that compare the
performance of OFDM and OTFS have indicated mixed outcomes due to the plethora
of system parameters at play beyond high-mobility conditions. In this work, we
exemplify this observation using simulations and propose a deep neural network
(DNN)-based adaptation scheme to switch between using either an OTFS or OFDM
signal processing chain at the transmitter and receiver for optimal
mean-squared-error (MSE) performance. The DNN classifier is trained to switch
between the two schemes by observing the channel condition, received SNR, and
modulation format. We compare the performance of the OTFS, OFDM, and the
proposed switched-waveform scheme. The simulations indicate superior
performance with the proposed scheme with a well-trained DNN, thus improving
the MSE performance of the communication significantly
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