3,094 research outputs found
Restricted Mobility Improves Delay-Throughput Trade-offs in Mobile Ad-Hoc Networks
In this paper we revisit two classes of mobility models which are widely used to repre-sent users ’ mobility in wireless networks: Random Waypoint (RWP) and Random Direction (RD). For both models we obtain systems of partial differential equations which describe the evolution of the users ’ distribution. For the RD model, we show how the equations can be solved analytically both in the stationary and transient regime adopting standard mathematical techniques. Our main contributions are i) simple expressions which relate the transient dura-tion to the model parameters; ii) the definition of a generalized random direction model whose stationary distribution of mobiles in the physical space corresponds to an assigned distribution
Adaptive Network Coding for Scheduling Real-time Traffic with Hard Deadlines
We study adaptive network coding (NC) for scheduling real-time traffic over a
single-hop wireless network. To meet the hard deadlines of real-time traffic,
it is critical to strike a balance between maximizing the throughput and
minimizing the risk that the entire block of coded packets may not be decodable
by the deadline. Thus motivated, we explore adaptive NC, where the block size
is adapted based on the remaining time to the deadline, by casting this
sequential block size adaptation problem as a finite-horizon Markov decision
process. One interesting finding is that the optimal block size and its
corresponding action space monotonically decrease as the deadline approaches,
and the optimal block size is bounded by the "greedy" block size. These unique
structures make it possible to narrow down the search space of dynamic
programming, building on which we develop a monotonicity-based backward
induction algorithm (MBIA) that can solve for the optimal block size in
polynomial time. Since channel erasure probabilities would be time-varying in a
mobile network, we further develop a joint real-time scheduling and channel
learning scheme with adaptive NC that can adapt to channel dynamics. We also
generalize the analysis to multiple flows with hard deadlines and long-term
delivery ratio constraints, devise a low-complexity online scheduling algorithm
integrated with the MBIA, and then establish its asymptotical
throughput-optimality. In addition to analysis and simulation results, we
perform high fidelity wireless emulation tests with real radio transmissions to
demonstrate the feasibility of the MBIA in finding the optimal block size in
real time.Comment: 11 pages, 13 figure
A Game-Theoretic Approach to Energy-Efficient Modulation in CDMA Networks with Delay QoS Constraints
A game-theoretic framework is used to study the effect of constellation size
on the energy efficiency of wireless networks for M-QAM modulation. A
non-cooperative game is proposed in which each user seeks to choose its
transmit power (and possibly transmit symbol rate) as well as the constellation
size in order to maximize its own utility while satisfying its delay
quality-of-service (QoS) constraint. The utility function used here measures
the number of reliable bits transmitted per joule of energy consumed, and is
particularly suitable for energy-constrained networks. The best-response
strategies and Nash equilibrium solution for the proposed game are derived. It
is shown that in order to maximize its utility (in bits per joule), a user must
choose the lowest constellation size that can accommodate the user's delay
constraint. This strategy is different from one that would maximize spectral
efficiency. Using this framework, the tradeoffs among energy efficiency, delay,
throughput and constellation size are also studied and quantified. In addition,
the effect of trellis-coded modulation on energy efficiency is discussed.Comment: To appear in the IEEE Journal on Selected Areas in Communications
(JSAC): Special Issue on Non-Cooperative Behavior in Networking, August 200
Network Formation Games Among Relay Stations in Next Generation Wireless Networks
The introduction of relay station (RS) nodes is a key feature in next
generation wireless networks such as 3GPP's long term evolution advanced
(LTE-Advanced), or the forthcoming IEEE 802.16j WiMAX standard. This paper
presents, using game theory, a novel approach for the formation of the tree
architecture that connects the RSs and their serving base station in the
\emph{uplink} of the next generation wireless multi-hop systems. Unlike
existing literature which mainly focused on performance analysis, we propose a
distributed algorithm for studying the \emph{structure} and \emph{dynamics} of
the network. We formulate a network formation game among the RSs whereby each
RS aims to maximize a cross-layer utility function that takes into account the
benefit from cooperative transmission, in terms of reduced bit error rate, and
the costs in terms of the delay due to multi-hop transmission. For forming the
tree structure, a distributed myopic algorithm is devised. Using the proposed
algorithm, each RS can individually select the path that connects it to the BS
through other RSs while optimizing its utility. We show the convergence of the
algorithm into a Nash tree network, and we study how the RSs can adapt the
network's topology to environmental changes such as mobility or the deployment
of new mobile stations. Simulation results show that the proposed algorithm
presents significant gains in terms of average utility per mobile station which
is at least 17.1% better relatively to the case with no RSs and reaches up to
40.3% improvement compared to a nearest neighbor algorithm (for a network with
10 RSs). The results also show that the average number of hops does not exceed
3 even for a network with up to 25 RSs.Comment: IEEE Transactions on Communications, vol. 59, no. 9, pp. 2528-2542,
September 201
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