Efficient Approximation Algorithms for Multi-Antennae Largest Weight Data Retrieval

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 $δ$-antennae largest weight data retrieval ($δ$ALWDR) problem is to compute a schedule for downloading a subset of data items that has a maximum total weight using $δ$ antennae in a given time interval. In this paper, we propose a ratio $1-\frac{1}{e}-ε$ approximation algorithm for the $δ$-antennae largest weight data retrieval ($δ$ALWDR) problem that has the same ratio as the known result but a significantly improved time complexity of $O(2^{\frac{1}ε}\frac{1}εm^{7}T^{3.5}L)$ from $O(ε^{3.5}m^{\frac{3.5}ε}T^{3.5}L)$ when $δ=1$ \cite{lu2014data}. To our knowledge, our algorithm represents the first ratio $1-\frac{1}{e}-ε$ approximation solution to $δ$ALWDR for the general case of arbitrary $δ$. To achieve this, we first give a ratio $1-\frac{1}{e}$ algorithm for the $γ$-separated $δ$ALWDR ($δ$A$γ$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 $δ$A$γ$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 $δ$A$γ$LWDR without this assumption at the cost of increased time complexity to $O(2^γm^{7}T^{3.5}L)$. This result immediately yields an approximation solution of same ratio and time complexity for $δ$ALWDR, presenting a significant improvement of the known time complexity of ratio $1-\frac{1}{e}-ε$ approximation to the problem.