197 research outputs found
Let Cognitive Radios Imitate: Imitation-based Spectrum Access for Cognitive Radio Networks
In this paper, we tackle the problem of opportunistic spectrum access in
large-scale cognitive radio networks, where the unlicensed Secondary Users (SU)
access the frequency channels partially occupied by the licensed Primary Users
(PU). Each channel is characterized by an availability probability unknown to
the SUs. We apply evolutionary game theory to model the spectrum access problem
and develop distributed spectrum access policies based on imitation, a behavior
rule widely applied in human societies consisting of imitating successful
behavior. We first develop two imitation-based spectrum access policies based
on the basic Proportional Imitation (PI) rule and the more advanced Double
Imitation (DI) rule given that a SU can imitate any other SUs. We then adapt
the proposed policies to a more practical scenario where a SU can only imitate
the other SUs operating on the same channel. A systematic theoretical analysis
is presented for both scenarios on the induced imitation dynamics and the
convergence properties of the proposed policies to an imitation-stable
equilibrium, which is also the -optimum of the system. Simple,
natural and incentive-compatible, the proposed imitation-based spectrum access
policies can be implemented distributedly based on solely local interactions
and thus is especially suited in decentralized adaptive learning environments
as cognitive radio networks
Sequential Decision Algorithms for Measurement-Based Impromptu Deployment of a Wireless Relay Network along a Line
We are motivated by the need, in some applications, for impromptu or
as-you-go deployment of wireless sensor networks. A person walks along a line,
starting from a sink node (e.g., a base-station), and proceeds towards a source
node (e.g., a sensor) which is at an a priori unknown location. At equally
spaced locations, he makes link quality measurements to the previous relay, and
deploys relays at some of these locations, with the aim to connect the source
to the sink by a multihop wireless path. In this paper, we consider two
approaches for impromptu deployment: (i) the deployment agent can only move
forward (which we call a pure as-you-go approach), and (ii) the deployment
agent can make measurements over several consecutive steps before selecting a
placement location among them (which we call an explore-forward approach). We
consider a light traffic regime, and formulate the problem as a Markov decision
process, where the trade-off is among the power used by the nodes, the outage
probabilities in the links, and the number of relays placed per unit distance.
We obtain the structures of the optimal policies for the pure as-you-go
approach as well as for the explore-forward approach. We also consider natural
heuristic algorithms, for comparison. Numerical examples show that the
explore-forward approach significantly outperforms the pure as-you-go approach.
Next, we propose two learning algorithms for the explore-forward approach,
based on Stochastic Approximation, which asymptotically converge to the set of
optimal policies, without using any knowledge of the radio propagation model.
We demonstrate numerically that the learning algorithms can converge (as
deployment progresses) to the set of optimal policies reasonably fast and,
hence, can be practical, model-free algorithms for deployment over large
regions.Comment: 29 pages. arXiv admin note: text overlap with arXiv:1308.068
Joint Subcarrier and Power Allocation in NOMA: Optimal and Approximate Algorithms
Non-orthogonal multiple access (NOMA) is a promising technology to increase
the spectral efficiency and enable massive connectivity in 5G and future
wireless networks. In contrast to orthogonal schemes, such as OFDMA, NOMA
multiplexes several users on the same frequency and time resource. Joint
subcarrier and power allocation problems (JSPA) in NOMA are NP-hard to solve in
general. In this family of problems, we consider the weighted sum-rate (WSR)
objective function as it can achieve various tradeoffs between sum-rate
performance and user fairness. Because of JSPA's intractability, a common
approach in the literature is to solve separately the power control and
subcarrier allocation (also known as user selection) problems, therefore
achieving sub-optimal result. In this work, we first improve the computational
complexity of existing single-carrier power control and user selection schemes.
These improved procedures are then used as basic building blocks to design new
algorithms, namely Opt-JSPA, -JSPA and Grad-JSPA. Opt-JSPA
computes an optimal solution with lower complexity than current optimal schemes
in the literature. It can be used as a benchmark for optimal WSR performance in
simulations. However, its pseudo-polynomial time complexity remains impractical
for real-world systems with low latency requirements. To further reduce the
complexity, we propose a fully polynomial-time approximation scheme called
-JSPA. Since, no approximation has been studied in the literature,
-JSPA stands out by allowing to control a tight trade-off between
performance guarantee and complexity. Finally, Grad-JSPA is a heuristic based
on gradient descent. Numerical results show that it achieves near-optimal WSR
with much lower complexity than existing optimal methods
Modeling and Analysis of HetNets with mm-Wave Multi-RAT Small Cells Deployed Along Roads
We characterize a multi tier network with classical macro cells, and multi
radio access technology (RAT) small cells, which are able to operate in
microwave and millimeter-wave (mm-wave) bands. The small cells are assumed to
be deployed along roads modeled as a Poisson line process. This
characterization is more realistic as compared to the classical Poisson point
processes typically used in literature. In this context, we derive the
association and RAT selection probabilities of the typical user under various
system parameters such as the small cell deployment density and mm-wave antenna
gain, and with varying street densities. Finally, we calculate the signal to
interference plus noise ratio (SINR) coverage probability for the typical user
considering a tractable dominant interference based model for mm-wave
interference. Our analysis reveals the need of deploying more small cells per
street in cities with more streets to maintain coverage, and highlights that
mm-wave RAT in small cells can help to improve the SINR performance of the
users.Comment: A 7-page version is submitted to IEEE GLOBECOM 201
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