  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.
