63,074 research outputs found
Near Optimal Channel Assignment for Interference Mitigation in Wireless Mesh Networks
In multi-radio multi-channel (MRMC) WMNs, interference alleviation is
affected through several network design techniques e.g., channel assignment
(CA), link scheduling, routing etc., intelligent CA schemes being the most
effective tool for interference mitigation. CA in WMNs is an NP-Hard problem,
and makes optimality a desired yet elusive goal in real-time deployments which
are characterized by fast transmission and switching times and minimal
end-to-end latency. The trade-off between optimal performance and minimal
response times is often achieved through CA schemes that employ heuristics to
propose efficient solutions. WMN configuration and physical layout are also
crucial factors which decide network performance, and it has been demonstrated
in numerous research works that rectangular/square grid WMNs outperform random
or unplanned WMN deployments in terms of network capacity, latency, and network
resilience. In this work, we propose a smart heuristic approach to devise a
near-optimal CA algorithm for grid WMNs (NOCAG). We demonstrate the efficacy of
NOCAG by evaluating its performance against the minimal-interference CA
generated through a rudimentary brute-force technique (BFCA), for the same WMN
configuration. We assess its ability to mitigate interference both,
theoretically (through interference estimation metrics) and experimentally (by
running rigorous simulations in NS-3). We demonstrate that the performance of
NOCAG is almost as good as the BFCA, at a minimal computational overhead of
O(n) compared to the exponential of BFCA
Message and time efficient multi-broadcast schemes
We consider message and time efficient broadcasting and multi-broadcasting in
wireless ad-hoc networks, where a subset of nodes, each with a unique rumor,
wish to broadcast their rumors to all destinations while minimizing the total
number of transmissions and total time until all rumors arrive to their
destination. Under centralized settings, we introduce a novel approximation
algorithm that provides almost optimal results with respect to the number of
transmissions and total time, separately. Later on, we show how to efficiently
implement this algorithm under distributed settings, where the nodes have only
local information about their surroundings. In addition, we show multiple
approximation techniques based on the network collision detection capabilities
and explain how to calibrate the algorithms' parameters to produce optimal
results for time and messages.Comment: In Proceedings FOMC 2013, arXiv:1310.459
On the Feasibility of Linear Interference Alignment for MIMO Interference Broadcast Channels with Constant Coefficients
In this paper, we analyze the feasibility of linear interference alignment
(IA) for multi-input-multi-output (MIMO) interference broadcast channel
(MIMO-IBC) with constant coefficients. We pose and prove the necessary
conditions of linear IA feasibility for general MIMO-IBC. Except for the proper
condition, we find another necessary condition to ensure a kind of irreducible
interference to be eliminated. We then prove the necessary and sufficient
conditions for a special class of MIMO-IBC, where the numbers of antennas are
divisible by the number of data streams per user. Since finding an invertible
Jacobian matrix is crucial for the sufficiency proof, we first analyze the
impact of sparse structure and repeated structure of the Jacobian matrix.
Considering that for the MIMO-IBC the sub-matrices of the Jacobian matrix
corresponding to the transmit and receive matrices have different repeated
structure, we find an invertible Jacobian matrix by constructing the two
sub-matrices separately. We show that for the MIMO-IBC where each user has one
desired data stream, a proper system is feasible. For symmetric MIMO-IBC, we
provide proper but infeasible region of antenna configurations by analyzing the
difference between the necessary conditions and the sufficient conditions of
linear IA feasibility.Comment: 14 pages, 3 figures, accepted by IEEE Trans. on Signal Processin
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