A deterministic approach to throughput scaling in wireless networks

Abstract

Abstract-We address the problem of how throughput in a wireless network scales as the number of users grows. Following the model of Gupta and Kumar, we consider identical nodes placed in a fixed area. Pairs of transmitters and receivers wish to communicate but are subject to interference from other nodes. Throughput is measured in bit-meters per second.We provide a very elementary deterministic approach that gives achievability results in terms of three key properties of the node locations. As a special case, we obtain throughput for a general class of network configurations in a fixed area. Results for random node locations in a fixed area can also be derived as special cases of the general result by verifying the growth rate of three parameters. For example, as a simple corollary of our result we obtain a stronger (almost sure) version of the log throughput for random node locations in a fixed area obtained by Gupta and Kumar. Results for some other interesting non-independent and identically distributed (i.i.d.) node distributions are also provided.

Non-coherent hierarchical cooperation

“…(this argument can be made precise, see [17]). Finally, assume α ∈ (2, 3) and 0 ≤ τ < 2 log −1/2 (n).…”

On the exact multicast delay in mobile ad hoc networks with f-cast relay

“…Similar to previous studies [26,27], the transmission range of each node covers the cell where it resides and the eight neighbor cells (two cells are said to be neighbor cells if they share a common point). Therefore, the possible maximum distance r between any two nodes can be deter-…”

“…To schedule as many simultaneous transmissions as possible, a transmission-group based scheduling scheme [17,23,26,27,29] is adopted for the medium access control (MAC). With this scheduling scheme, all m 2 cells in the network are divided into a 2 transmission-groups.…”

Capacity of data collection in randomly-deployed wireless sensor networks

“…Lemma 1 [9] Given n random nodes in a unit square, dividing the square into micro cells of the size ffiffiffiffiffiffiffiffiffi 3 log n n q  ffiffiffiffiffiffiffiffiffi 3 log n n q , every micro cell is occupied with probability at least 1 À 1 n 2 . Therefore, if we set d ¼ ffiffiffiffiffiffiffiffiffi 3 log n n q i.e.…”