Scaling Laws for Ad Hoc Wireless Networks: An Information Theoretic Approach

Xue, Feng

doi:10.1561/1300000002

Cited by 148 publications

(111 citation statements)

References 26 publications

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“…Proof: Our proof is similar to that of [10] except that we account for n− k unicast pairs in the network. The probability that the destination node j is x away from the source node is C 3 π(x+d n ) [10] where C 3 is a constant. Thus, the probability p that there is a line passing through the cell S which is with distance x from j is…”

Section: The Traffic Caused By Unicast Communicationsmentioning

confidence: 97%

“…The selection of sources for the access node i is based on the technique described in [10]. We randomly and uniformly select k locations in the network and choose the closest nodes to these k locations as sources for the access node.…”

Section: A the Routing Scheme And The Scheduling Protocolmentioning

confidence: 99%

“…For the scheduling scheme, we utilize a TDMA scheme similar to [10] with some modifications to take into account the heterogeneity of the traffic.…”

Section: A the Routing Scheme And The Scheduling Protocolmentioning

confidence: 99%

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Capacity of Wireless Networks with Heterogeneous Traffic

Wang

Sadjadpour

et al. 2009

GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference

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Abstract-We study the scaling laws for wireless ad hoc network in which the distribution of nodes in the network is homogeneous but the traffic is heterogeneous. More specifically, we consider the case in which a node is the sink to k sources sending different information, while the rest of the nodes are part of unicast communications with a uniform assignment of source-destination pairs. We prove that the capacity of these heterogeneous networks is Θ( n Tmax ), where Tmax and n denote the maximum traffic for a cell and the number of nodes in the network, respectively. Equivalently, our derivations reveal that, when n − k = constant, the network capacity is equal to Θ "q n log n " for k = O( √ n log n) and equal to Θ`n kf or k = Ω( √ n log n). Furthermore, the network capacity is Θ(1) when n − k = constant. These results demonstrate that the capacity of a heterogeneous network is dominated by the maximum congestion in any area of the network.

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Section: The Traffic Caused By Unicast Communicationsmentioning

confidence: 97%

Section: A the Routing Scheme And The Scheduling Protocolmentioning

confidence: 99%

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Capacity of Wireless Networks with Heterogeneous Traffic

Wang

Sadjadpour

et al. 2009

GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference

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“…We use the protocol model [11] to determine the success of communication in the presence of multiple access interference (MAI). In particular, if χ i , χ j and χ k denote the Cartesian positions in the unit square area for nodes v i , v j and v k , node v i can successfully transmit to node v j if |χ i −χ j | ≤ r(n), where r(n) is the common transmission range of all the nodes in the network, and for any node v k = v i , that transmits at the same time as v i , |χ k − χ j | ≥ (1 + ∆)r(n), with ∆ > 0 as the guard zone factor.…”

Section: Preliminariesmentioning

confidence: 99%

The impact of social groups on the capacity of wireless networks

Azimdoost

Sadjadpour

Garcia-Luna-Aceves

2011

2011 IEEE Network Science Workshop

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Abstract-The capacity of a wireless network with n nodes is studied when nodes communicate with one another in the context of social groups. Each node is assumed to have at least one local contact in each of the four directions of the plane in which the wireless network operates, and q(n) independent long-range social contacts forming its social group, one of which it selects randomly as its destination. The distance between source and the members of its social group follows a powerlaw distribution with parameter α, and communication between any two nodes takes place only within the physical transmission range; hence, source-destination communication takes place over multi-hop paths. The order capacity of such a composite network is derived as a function of the number of nodes (n), the socialgroup concentration (α), and the size of social groups (q(n)). It is shown that the maximum order capacity is attained when α ≥ 3, which makes social groups localized geographically, and that a wireless network can be scale-free when social groups are localized and independent of the number of nodes in the network, i.e., q(n) is independent of n.

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“…The protocol model defined in [7] is based on single-packet reception. The transmission range r(n) is common for all nodes in the network.…”

Section: Preliminariesmentioning

confidence: 99%

Impact of multi-packet transmission and reception on the throughput capacity of wireless ad hoc networks

Azimdoost

Hamid

Garcia-Luna-Aceves

2010

2010 - Milcom 2010 Military Communications Conference

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Abstract-We study the capacity of random wireless ad hoc networks when nodes are capable of multi-packet transmission and reception (MPTR). This paper extends the unified framework of (n, m, k)-cast by Wang et al. [6] for single-packet reception (SPR) at each node to the case of MPTR. (n, m, k)-cast considers all types of information dissemination including unicast routing, multicast routing, broadcasting and anycasting. In this context, n, m, and k represent the total number of nodes in the network, the number of destinations for each communication group and the actual number of destinations that receive the packets, respectively. We show that the capacity of a wireless ad hoc network of n nodes in which nodes have a communication range of r(n) and engage in an (n, m, k)-casting scales as Θ(n √ mr 3 (n)/k), Θ(nr 2 (n)/k) and Θ(nr 4 (n)) bits per second when m = O(1/r 2 (n)), Ω(k) = 1/r 2 (n) = O(m) and k = Ω(1/r 2 (n)), respectively. We show that the use of MPTR leads to a gain of Θ(logn) compared to the capacity attained with multi-packet reception (MPR), and to a gain of Θ ((logn) 2 ) compared to the capacity attained with SPR, when Ω( logn/n) = r(n) = O( loglogn/3logn).

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Scaling Laws for Ad Hoc Wireless Networks: An Information Theoretic Approach

Cited by 148 publications

References 26 publications

Capacity of Wireless Networks with Heterogeneous Traffic

Capacity of Wireless Networks with Heterogeneous Traffic

The impact of social groups on the capacity of wireless networks

Impact of multi-packet transmission and reception on the throughput capacity of wireless ad hoc networks

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