9,698 research outputs found
Beamforming and Rate Allocation in MISO Cognitive Radio Networks
We consider decentralized multi-antenna cognitive radio networks where
secondary (cognitive) users are granted simultaneous spectrum access along with
license-holding (primary) users. We treat the problem of distributed
beamforming and rate allocation for the secondary users such that the minimum
weighted secondary rate is maximized. Such an optimization is subject to (1) a
limited weighted sum-power budget for the secondary users and (2) guaranteed
protection for the primary users in the sense that the interference level
imposed on each primary receiver does not exceed a specified level. Based on
the decoding method deployed by the secondary receivers, we consider three
scenarios for solving this problem. In the first scenario each secondary
receiver decodes only its designated transmitter while suppressing the rest as
Gaussian interferers (single-user decoding). In the second case each secondary
receiver employs the maximum likelihood decoder (MLD) to jointly decode all
secondary transmissions, and in the third one each secondary receiver uses the
unconstrained group decoder (UGD). By deploying the UGD, each secondary user is
allowed to decode any arbitrary subset of users (which contains its designated
user) after suppressing or canceling the remaining users.Comment: 32 pages, 6 figure
Controlled Matching Game for Resource Allocation and User Association in WLANs
In multi-rate IEEE 802.11 WLANs, the traditional user association based on
the strongest received signal and the well known anomaly of the MAC protocol
can lead to overloaded Access Points (APs), and poor or heterogeneous
performance. Our goal is to propose an alternative game-theoretic approach for
association. We model the joint resource allocation and user association as a
matching game with complementarities and peer effects consisting of selfish
players solely interested in their individual throughputs. Using recent
game-theoretic results we first show that various resource sharing protocols
actually fall in the scope of the set of stability-inducing resource allocation
schemes. The game makes an extensive use of the Nash bargaining and some of its
related properties that allow to control the incentives of the players. We show
that the proposed mechanism can greatly improve the efficiency of 802.11 with
heterogeneous nodes and reduce the negative impact of peer effects such as its
MAC anomaly. The mechanism can be implemented as a virtual connectivity
management layer to achieve efficient APs-user associations without
modification of the MAC layer
Decentralized Adaptive Helper Selection in Multi-channel P2P Streaming Systems
In Peer-to-Peer (P2P) multichannel live streaming, helper peers with surplus
bandwidth resources act as micro-servers to compensate the server deficiencies
in balancing the resources between different channel overlays. With deployment
of helper level between server and peers, optimizing the user/helper topology
becomes a challenging task since applying well-known reciprocity-based choking
algorithms is impossible due to the one-directional nature of video streaming
from helpers to users. Because of selfish behavior of peers and lack of central
authority among them, selection of helpers requires coordination. In this
paper, we design a distributed online helper selection mechanism which is
adaptable to supply and demand pattern of various video channels. Our solution
for strategic peers' exploitation from the shared resources of helpers is to
guarantee the convergence to correlated equilibria (CE) among the helper
selection strategies. Online convergence to the set of CE is achieved through
the regret-tracking algorithm which tracks the equilibrium in the presence of
stochastic dynamics of helpers' bandwidth. The resulting CE can help us select
proper cooperation policies. Simulation results demonstrate that our algorithm
achieves good convergence, load distribution on helpers and sustainable
streaming rates for peers
Minimal Envy and Popular Matchings
We study ex-post fairness in the object allocation problem where objects are
valuable and commonly owned. A matching is fair from individual perspective if
it has only inevitable envy towards agents who received most preferred objects
-- minimal envy matching. A matching is fair from social perspective if it is
supported by majority against any other matching -- popular matching.
Surprisingly, the two perspectives give the same outcome: when a popular
matching exists it is equivalent to a minimal envy matching.
We show the equivalence between global and local popularity: a matching is
popular if and only if there does not exist a group of size up to 3 agents that
decides to exchange their objects by majority, keeping the remaining matching
fixed. We algorithmically show that an arbitrary matching is path-connected to
a popular matching where along the path groups of up to 3 agents exchange their
objects by majority. A market where random groups exchange objects by majority
converges to a popular matching given such matching exists.
When popular matching might not exist we define most popular matching as a
matching that is popular among the largest subset of agents. We show that each
minimal envy matching is a most popular matching and propose a polynomial-time
algorithm to find them
Optimality of Treating Interference as Noise: A Combinatorial Perspective
For single-antenna Gaussian interference channels, we re-formulate the
problem of determining the Generalized Degrees of Freedom (GDoF) region
achievable by treating interference as Gaussian noise (TIN) derived in [3] from
a combinatorial perspective. We show that the TIN power control problem can be
cast into an assignment problem, such that the globally optimal power
allocation variables can be obtained by well-known polynomial time algorithms.
Furthermore, the expression of the TIN-Achievable GDoF region (TINA region) can
be substantially simplified with the aid of maximum weighted matchings. We also
provide conditions under which the TINA region is a convex polytope that relax
those in [3]. For these new conditions, together with a channel connectivity
(i.e., interference topology) condition, we show TIN optimality for a new class
of interference networks that is not included, nor includes, the class found in
[3].
Building on the above insights, we consider the problem of joint link
scheduling and power control in wireless networks, which has been widely
studied as a basic physical layer mechanism for device-to-device (D2D)
communications. Inspired by the relaxed TIN channel strength condition as well
as the assignment-based power allocation, we propose a low-complexity
GDoF-based distributed link scheduling and power control mechanism (ITLinQ+)
that improves upon the ITLinQ scheme proposed in [4] and further improves over
the heuristic approach known as FlashLinQ. It is demonstrated by simulation
that ITLinQ+ provides significant average network throughput gains over both
ITLinQ and FlashLinQ, and yet still maintains the same level of implementation
complexity. More notably, the energy efficiency of the newly proposed ITLinQ+
is substantially larger than that of ITLinQ and FlashLinQ, which is desirable
for D2D networks formed by battery-powered devices.Comment: A short version has been presented at IEEE International Symposium on
Information Theory (ISIT 2015), Hong Kon
An Exchange Mechanism to Coordinate Flexibility in Residential Energy Cooperatives
Energy cooperatives (ECs) such as residential and industrial microgrids have
the potential to mitigate increasing fluctuations in renewable electricity
generation, but only if their joint response is coordinated. However, the
coordination and control of independently operated flexible resources (e.g.,
storage, demand response) imposes critical challenges arising from the
heterogeneity of the resources, conflict of interests, and impact on the grid.
Correspondingly, overcoming these challenges with a general and fair yet
efficient exchange mechanism that coordinates these distributed resources will
accommodate renewable fluctuations on a local level, thereby supporting the
energy transition. In this paper, we introduce such an exchange mechanism. It
incorporates a payment structure that encourages prosumers to participate in
the exchange by increasing their utility above baseline alternatives. The
allocation from the proposed mechanism increases the system efficiency
(utilitarian social welfare) and distributes profits more fairly (measured by
Nash social welfare) than individual flexibility activation. A case study
analyzing the mechanism performance and resulting payments in numerical
experiments over real demand and generation profiles of the Pecan Street
dataset elucidates the efficacy to promote cooperation between co-located
flexibilities in residential cooperatives through local exchange.Comment: Accepted in IEEE ICIT 201
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