2,030 research outputs found
Survey of Spectrum Sharing for Inter-Technology Coexistence
Increasing capacity demands in emerging wireless technologies are expected to
be met by network densification and spectrum bands open to multiple
technologies. These will, in turn, increase the level of interference and also
result in more complex inter-technology interactions, which will need to be
managed through spectrum sharing mechanisms. Consequently, novel spectrum
sharing mechanisms should be designed to allow spectrum access for multiple
technologies, while efficiently utilizing the spectrum resources overall.
Importantly, it is not trivial to design such efficient mechanisms, not only
due to technical aspects, but also due to regulatory and business model
constraints. In this survey we address spectrum sharing mechanisms for wireless
inter-technology coexistence by means of a technology circle that incorporates
in a unified, system-level view the technical and non-technical aspects. We
thus systematically explore the spectrum sharing design space consisting of
parameters at different layers. Using this framework, we present a literature
review on inter-technology coexistence with a focus on wireless technologies
with equal spectrum access rights, i.e. (i) primary/primary, (ii)
secondary/secondary, and (iii) technologies operating in a spectrum commons.
Moreover, we reflect on our literature review to identify possible spectrum
sharing design solutions and performance evaluation approaches useful for
future coexistence cases. Finally, we discuss spectrum sharing design
challenges and suggest future research directions
Distributed power allocation for D2D communications underlaying/overlaying OFDMA cellular networks
The implementation of device-to-device (D2D) underlaying or overlaying
pre-existing cellular networks has received much attention due to the potential
of enhancing the total cell throughput, reducing power consumption and
increasing the instantaneous data rate. In this paper we propose a distributed
power allocation scheme for D2D OFDMA communications and, in particular, we
consider the two operating modes amenable to a distributed implementation:
dedicated and reuse modes. The proposed schemes address the problem of
maximizing the users' sum rate subject to power constraints, which is known to
be nonconvex and, as such, extremely difficult to be solved exactly. We propose
here a fresh approach to this well-known problem, capitalizing on the fact that
the power allocation problem can be modeled as a potential game. Exploiting the
potential games property of converging under better response dynamics, we
propose two fully distributed iterative algorithms, one for each operation mode
considered, where each user updates sequentially and autonomously its power
allocation. Numerical results, computed for several different user scenarios,
show that the proposed methods, which converge to one of the local maxima of
the objective function, exhibit performance close to the maximum achievable
optimum and outperform other schemes presented in the literature
Distributed Optimization of Multi-Cell Uplink Co-operation with Backhaul Constraints
We address the problem of uplink co-operative reception with constraints on
both backhaul bandwidth and the receiver aperture, or number of antenna signals
that can be processed. The problem is cast as a network utility (weighted sum
rate) maximization subject to computational complexity and architectural
bandwidth sharing constraints. We show that a relaxed version of the problem is
convex, and can be solved via a dual-decomposition. The proposed solution is
distributed in that each cell broadcasts a set of {\em demand prices} based on
the data sharing requests they receive. Given the demand prices, the algorithm
determines an antenna/cell ordering and antenna-selection for each scheduled
user in a cell. This algorithm, referred to as {\em LiquidMAAS}, iterates
between the preceding two steps. Simulations of realistic network scenarios
show that the algorithm exhibits fast convergence even for systems with large
number of cells.Comment: IEEE ICC Conference, 201
Efficient Heuristic for Resource Allocation in Zero-forcing OFDMA-SDMA Systems with Minimum Rate Constraints
4G wireless access systems require high spectral efficiency to support the
ever increasing number of users and data rates for real time applications.
Multi-antenna OFDM-SDMA systems can provide the required high spectral
efficiency and dynamic usage of the channel, but the resource allocation
process becomes extremely complex because of the augmented degrees of freedom.
In this paper, we propose two heuristics to solve the resource allocation
problem that have very low computational complexity and give performances not
far from the optimal. The proposed heuristics select a set of users for each
subchannel, but contrary to the reported methods that solve the throughput
maximization problem, our heuristics consider the set of real-time (RT) users
to ensure that their minimum rate requirements are met. We compare the
heuristics' performance against an upper bound and other methods proposed in
the literature and find that they give a somewhat lower performance, but
support a wider range of minimum rates while reducing the computational
complexity. The gap between the objective achieved by the heuristics and the
upper bound is not large. In our experiments this gap is 10.7% averaging over
all performed numerical evaluations for all system configurations. The increase
in the range of the supported minimum rates when compared with a method
reported in the literature is 14.6% on average.Comment: 8 figure
Coalitional Games with Overlapping Coalitions for Interference Management in Small Cell Networks
In this paper, we study the problem of cooperative interference management in
an OFDMA two-tier small cell network. In particular, we propose a novel
approach for allowing the small cells to cooperate, so as to optimize their
sum-rate, while cooperatively satisfying their maximum transmit power
constraints. Unlike existing work which assumes that only disjoint groups of
cooperative small cells can emerge, we formulate the small cells' cooperation
problem as a coalition formation game with overlapping coalitions. In this
game, each small cell base station can choose to participate in one or more
cooperative groups (or coalitions) simultaneously, so as to optimize the
tradeoff between the benefits and costs associated with cooperation. We study
the properties of the proposed overlapping coalition formation game and we show
that it exhibits negative externalities due to interference. Then, we propose a
novel decentralized algorithm that allows the small cell base stations to
interact and self-organize into a stable overlapping coalitional structure.
Simulation results show that the proposed algorithm results in a notable
performance advantage in terms of the total system sum-rate, relative to the
noncooperative case and the classical algorithms for coalitional games with
non-overlapping coalitions
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