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Ayfer Ozgur

Publications and source records attributed to Ayfer Ozgur.

40 records · Page 3Linked to original sources

Linear Capacity Scaling in Wireless Networks: Beyond Physical Limits?

We investigate the role of cooperation in wireless networks subject to a spatial degrees of freedom limitation. To address the worst case scenario, we consider a free-space line-of-sight type environment with no scattering and no fading. We identify three qualitatively different operating regimes that are determined by how the area of the network A, normalized with respect to the wavelength lambda, compares to the number of users n. In networks with sqrt{A}/lambda < sqrt{n}, the limitation in spatial degrees of freedom does not allow to achieve a capacity scaling better than sqrt{n} and this performance can be readily achieved by multi-hopping. This result has been recently shown by Franceschetti et al. However, for networks with sqrt{A}/lambda > sqrt{n}, the number of available degrees of freedom is min(n, sqrt{A}/lambda), larger that what can be achieved by multi-hopping. We show that the optimal capacity scaling in this regime is achieved by hierarchical cooperation. In particular, in networks with sqrt{A}/lambda> n, hierarchical cooperation can achieve linear scaling.

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Information Theoretic Operating Regimes of Large Wireless Networks

In analyzing the point-to-point wireless channel, insights about two qualitatively different operating regimes--bandwidth- and power-limited--have proven indispensable in the design of good communication schemes. In this paper, we propose a new scaling law formulation for wireless networks that allows us to develop a theory that is analogous to the point-to-point case. We identify fundamental operating regimes of wireless networks and derive architectural guidelines for the design of optimal schemes. Our analysis shows that in a given wireless network with arbitrary size, area, power, bandwidth, etc., there are three parameters of importance: the short-distance SNR, the long-distance SNR, and the power path loss exponent of the environment. Depending on these parameters we identify four qualitatively different regimes. One of these regimes is especially interesting since it is fundamentally a consequence of the heterogeneous nature of links in a network and does not occur in the point-to-point case; the network capacity is {\em both} power and bandwidth limited. This regime has thus far remained hidden due to the limitations of the existing formulation. Existing schemes, either multihop transmission or hierarchical cooperation, fail to achieve capacity in this regime; we propose a new hybrid scheme that achieves capacity.

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Throughput-Delay Trade-off for Hierarchical Cooperation in Ad Hoc Wireless Networks

Hierarchical cooperation has recently been shown to achieve better throughput scaling than classical multihop schemes under certain assumptions on the channel model in static wireless networks. However, the end-to-end delay of this scheme turns out to be significantly larger than those of multihop schemes. A modification of the scheme is proposed here that achieves a throughput-delay trade-off $D(n)=(\log n)^2 T(n)$ for T(n) between $Θ(\sqrt{n}/\log n)$ and $Θ(n/\log n)$, where D(n) and T(n) are respectively the average delay per bit and the aggregate throughput in a network of n nodes. This trade-off complements the previous results of El Gamal et al., which show that the throughput-delay trade-off for multihop schemes is given by D(n)=T(n) where T(n) lies between $Θ(1)$ and $Θ(\sqrt{n})$. Meanwhile, the present paper considers the network multiple-access problem, which may be of interest in its own right.

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Hierarchical Cooperation Achieves Optimal Capacity Scaling in Ad Hoc Networks

n source and destination pairs randomly located in an area want to communicate with each other. Signals transmitted from one user to another at distance r apart are subject to a power loss of r^{-alpha}, as well as a random phase. We identify the scaling laws of the information theoretic capacity of the network. In the case of dense networks, where the area is fixed and the density of nodes increasing, we show that the total capacity of the network scales linearly with n. This improves on the best known achievability result of n^{2/3} of Aeron and Saligrama, 2006. In the case of extended networks, where the density of nodes is fixed and the area increasing linearly with n, we show that this capacity scales as n^{2-alpha/2} for 2 3. The best known earlier result (Xie and Kumar 2006) identified the scaling law for alpha > 4. Thus, much better scaling than multihop can be achieved in dense networks, as well as in extended networks with low attenuation. The performance gain is achieved by intelligent node cooperation and distributed MIMO communication. The key ingredient is a hierarchical and digital architecture for nodal exchange of information for realizing the cooperation.

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