4 research outputs found
Information Exchange Limits in Cooperative MIMO Networks
Concurrent presence of inter-cell and intra-cell interferences constitutes a
major impediment to reliable downlink transmission in multi-cell multiuser
networks. Harnessing such interferences largely hinges on two levels of
information exchange in the network: one from the users to the base-stations
(feedback) and the other one among the base-stations (cooperation). We
demonstrate that exchanging a finite number of bits across the network, in the
form of feedback and cooperation, is adequate for achieving the optimal
capacity scaling. We also show that the average level of information exchange
is independent of the number of users in the network. This level of information
exchange is considerably less than that required by the existing coordination
strategies which necessitate exchanging infinite bits across the network for
achieving the optimal sum-rate capacity scaling. The results provided rely on a
constructive proof.Comment: 35 pages, 5 figur
An Analytical Framework for Heterogeneous Partial Feedback Design in Heterogeneous Multicell OFDMA Networks
The inherent heterogeneous structure resulting from user densities and large
scale channel effects motivates heterogeneous partial feedback design in
heterogeneous networks. In such emerging networks, a distributed scheduling
policy which enjoys multiuser diversity as well as maintains fairness among
users is favored for individual user rate enhancement and guarantees. For a
system employing the cumulative distribution function based scheduling, which
satisfies the two above mentioned desired features, we develop an analytical
framework to investigate heterogeneous partial feedback in a general
OFDMA-based heterogeneous multicell employing the best-M partial feedback
strategy. Exact sum rate analysis is first carried out and closed form
expressions are obtained by a novel decomposition of the probability density
function of the selected user's signal-to-interference-plus-noise ratio. To
draw further insight, we perform asymptotic analysis using extreme value theory
to examine the effect of partial feedback on the randomness of multiuser
diversity, show the asymptotic optimality of best-1 feedback, and derive an
asymptotic approximation for the sum rate in order to determine the minimum
required partial feedback.Comment: To appear in IEEE Trans. on Signal Processin