  In a mobile network, wireless data broadcast over $m$ channels (frequencies)
is a powerful means for distributed dissemination of data to clients who access
the channels through multi-antennae equipped on their mobile devices. The
$\delta$-antennae largest weight data retrieval ($\delta$ALWDR) problem is to
compute a schedule for downloading a subset of data items that has a maximum
total weight using $\delta$ antennae in a given time interval. In this paper,
we propose a ratio $1-\frac{1}{e}-\epsilon$ approximation algorithm for the
$\delta$-antennae largest weight data retrieval ($\delta$ALWDR) problem that
has the same ratio as the known result but a significantly improved time
complexity of $O(2^{\frac{1}{\epsilon}}\frac{1}{\epsilon}m^{7}T^{3.5}L)$ from
$O(\epsilon^{3.5}m^{\frac{3.5}{\epsilon}}T^{3.5}L)$ when $\delta=1$
\cite{lu2014data}. To our knowledge, our algorithm represents the first ratio
$1-\frac{1}{e}-\epsilon$ approximation solution to $\delta$ALWDR for the
general case of arbitrary $\delta$. To achieve this, we first give a ratio
$1-\frac{1}{e}$ algorithm for the $\gamma$-separated $\delta$ALWDR
($\delta$A$\gamma$LWDR) with runtime $O(m^{7}T^{3.5}L)$, under the assumption
that every data item appears at most once in each segment of
$\delta$A$\gamma$LWDR, for any input of maximum length $L$ on $m$ channels in
$T$ time slots. Then, we show that we can retain the same ratio for
$\delta$A$\gamma$LWDR without this assumption at the cost of increased time
complexity to $O(2^{\gamma}m^{7}T^{3.5}L)$. This result immediately yields an
approximation solution of same ratio and time complexity for $\delta$ALWDR,
presenting a significant improvement of the known time complexity of ratio
$1-\frac{1}{e}-\epsilon$ approximation to the problem.

Data Structures and Algorithms