arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 0905.3858cs.ITmath.IT
收藏

大型无线网络中的多播:每比特最小能量的界限

Multicasting in Large Wireless Networks: Bounds on the Minimum Energy per Bit

Aman Jain, Sanjeev R. Kulkarni, Sergio Verdu

摘要:

我们考虑缩放定律的最大能量效率的通信消息的所有节点在无线网络中,网络中的节点的数量变得很大。研究了两种情况下的大型无线网络-密集随机网络和恒定密度(扩展)随机网络。此外,我们还研究了有限大小的规则网络,以了解节点放置的规则性如何影响能量消耗。首先,我们建立了一个信息理论上的最小能量每比特的任意无线网络中的多播时,信道状态信息是不可用的发射机。通过构造一个简单的洪泛方案,不需要在接收器的信道状态或节点的位置和身份的信息,得到上界。对于稠密随机网络和规则网络,上界和下界之间的差距只是一个常数因子,而对于扩展随机网络,上界和下界之间的差距相差一个多对数因子。此外,我们表明,随机网络的建议的上限和下限举行几乎肯定在节点的位置,节点的数量接近无穷大。

英文摘要:

We consider scaling laws for maximal energy efficiency of communicating a message to all the nodes in a wireless network, as the number of nodes in the network becomes large. Two cases of large wireless networks are studied -- dense random networks and constant density (extended) random networks. In addition, we also study finite size regular networks in order to understand how regularity in node placement affects energy consumption. We first establish an information-theoretic lower bound on the minimum energy per bit for multicasting in arbitrary wireless networks when the channel state information is not available at the transmitters. Upper bounds are obtained by constructing a simple flooding scheme that requires no information at the receivers about the channel states or the locations and identities of the nodes. The gap between the upper and lower bounds is only a constant factor for dense random networks and regular networks, and differs by a poly-logarithmic factor for extended random networks. Furthermore, we show that the proposed upper and lower bounds for random networks hold almost surely in the node locations as the number of nodes approaches infinity.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑