9 research outputs found
On Achievable Rates of Line Networks with Generalized Batched Network Coding
To better understand the wireless network design with a large number of hops,
we investigate a line network formed by general discrete memoryless channels
(DMCs), which may not be identical. Our focus lies on Generalized Batched
Network Coding (GBNC) that encompasses most existing schemes as special cases
and achieves the min-cut upper bounds as the parameters batch size and inner
block length tend to infinity. The inner blocklength of GBNC provides upper
bounds on the required latency and buffer size at intermediate network nodes.
By employing a bottleneck status technique, we derive new upper bounds on the
achievable rates of GBNCs These bounds surpass the min-cut bound for large
network lengths when the inner blocklength and batch size are small. For line
networks of canonical channels, certain upper bounds hold even with relaxed
inner blocklength constraints. Additionally, we employ a channel reduction
technique to generalize the existing achievability results for line networks
with identical DMCs to networks with non-identical DMCs. For line networks with
packet erasure channels, we make refinement in both the upper bound and the
coding scheme, and showcase their proximity through numerical evaluations.Comment: This paper was presented in part at ISIT 2019 and 2020, and is
accepted by a JSAC special issu
Optimizing the Age-of-Information for Mobile Users in Adversarial and Stochastic Environments
We study a multi-user downlink scheduling problem for optimizing the
freshness of information available to users roaming across multiple cells. We
consider both adversarial and stochastic settings and design scheduling
policies that optimize two distinct information freshness metrics, namely the
average age-of-information and the peak age-of-information. We show that a
natural greedy scheduling policy is competitive with the optimal offline policy
in the adversarial setting. We also derive fundamental lower bounds to the
competitive ratio achievable by any online policy. In the stochastic
environment, we show that a Max-Weight scheduling policy that takes into
account the channel statistics achieves an approximation factor of for
minimizing the average age of information in two extreme mobility scenarios. We
conclude the paper by establishing a large-deviation optimality result achieved
by the greedy policy for minimizing the peak age of information for static
users situated at a single cell.Comment: arXiv admin note: text overlap with arXiv:2001.0547