26,407 research outputs found
Resource Allocation with Reverse Pricing for Communication Networks
Reverse pricing has been recognized as an effective tool to handle demand
uncertainty in the travel industry (e.g., airlines and hotels). To investigate
its viability for communication networks, we study the practical limitations of
(operator-driven) time-dependent pricing that has been recently introduced,
taking into account demand uncertainty. Compared to (operator-driven)
time-dependent pricing, we show that the proposed pricing scheme can achieve
"triple-win" solutions: an increase in the total average revenue of the
operator; higher average resource utilization efficiency; and an increment in
the total average payoff of the users. Our findings provide a new outlook on
resource allocation, and design guidelines for adopting the reverse pricing
scheme.Comment: to appear in IEEE International Conference on Communications (ICC)
2016, Kuala Lumpur, Malaysia (6 pages, 3 figures
Efficiency Resource Allocation for Device-to-Device Underlay Communication Systems: A Reverse Iterative Combinatorial Auction Based Approach
Peer-to-peer communication has been recently considered as a popular issue
for local area services. An innovative resource allocation scheme is proposed
to improve the performance of mobile peer-to-peer, i.e., device-to-device
(D2D), communications as an underlay in the downlink (DL) cellular networks. To
optimize the system sum rate over the resource sharing of both D2D and cellular
modes, we introduce a reverse iterative combinatorial auction as the allocation
mechanism. In the auction, all the spectrum resources are considered as a set
of resource units, which as bidders compete to obtain business while the
packages of the D2D pairs are auctioned off as goods in each auction round. We
first formulate the valuation of each resource unit, as a basis of the proposed
auction. And then a detailed non-monotonic descending price auction algorithm
is explained depending on the utility function that accounts for the channel
gain from D2D and the costs for the system. Further, we prove that the proposed
auction-based scheme is cheat-proof, and converges in a finite number of
iteration rounds. We explain non-monotonicity in the price update process and
show lower complexity compared to a traditional combinatorial allocation. The
simulation results demonstrate that the algorithm efficiently leads to a good
performance on the system sum rate.Comment: 26 pages, 6 fgures; IEEE Journals on Selected Areas in
Communications, 201
Reciprocity-driven Sparse Network Formation
A resource exchange network is considered, where exchanges among nodes are
based on reciprocity. Peers receive from the network an amount of resources
commensurate with their contribution. We assume the network is fully connected,
and impose sparsity constraints on peer interactions. Finding the sparsest
exchanges that achieve a desired level of reciprocity is in general NP-hard. To
capture near-optimal allocations, we introduce variants of the Eisenberg-Gale
convex program with sparsity penalties. We derive decentralized algorithms,
whereby peers approximately compute the sparsest allocations, by reweighted l1
minimization. The algorithms implement new proportional-response dynamics, with
nonlinear pricing. The trade-off between sparsity and reciprocity and the
properties of graphs induced by sparse exchanges are examined.Comment: 19 page
Energy-Efficient Resource Allocation in Wireless Networks: An Overview of Game-Theoretic Approaches
An overview of game-theoretic approaches to energy-efficient resource
allocation in wireless networks is presented. Focusing on multiple-access
networks, it is demonstrated that game theory can be used as an effective tool
to study resource allocation in wireless networks with quality-of-service (QoS)
constraints. A family of non-cooperative (distributed) games is presented in
which each user seeks to choose a strategy that maximizes its own utility while
satisfying its QoS requirements. The utility function considered here measures
the number of reliable bits that are transmitted per joule of energy consumed
and, hence, is particulary suitable for energy-constrained networks. The
actions available to each user in trying to maximize its own utility are at
least the choice of the transmit power and, depending on the situation, the
user may also be able to choose its transmission rate, modulation, packet size,
multiuser receiver, multi-antenna processing algorithm, or carrier allocation
strategy. The best-response strategy and Nash equilibrium for each game is
presented. Using this game-theoretic framework, the effects of power control,
rate control, modulation, temporal and spatial signal processing, carrier
allocation strategy and delay QoS constraints on energy efficiency and network
capacity are quantified.Comment: To appear in the IEEE Signal Processing Magazine: Special Issue on
Resource-Constrained Signal Processing, Communications and Networking, May
200
Game-theoretic Resource Allocation Methods for Device-to-Device (D2D) Communication
Device-to-device (D2D) communication underlaying cellular networks allows
mobile devices such as smartphones and tablets to use the licensed spectrum
allocated to cellular services for direct peer-to-peer transmission. D2D
communication can use either one-hop transmission (i.e., in D2D direct
communication) or multi-hop cluster-based transmission (i.e., in D2D local area
networks). The D2D devices can compete or cooperate with each other to reuse
the radio resources in D2D networks. Therefore, resource allocation and access
for D2D communication can be treated as games. The theories behind these games
provide a variety of mathematical tools to effectively model and analyze the
individual or group behaviors of D2D users. In addition, game models can
provide distributed solutions to the resource allocation problems for D2D
communication. The aim of this article is to demonstrate the applications of
game-theoretic models to study the radio resource allocation issues in D2D
communication. The article also outlines several key open research directions.Comment: Accepted. IEEE Wireless Comms Mag. 201
- …