A Network Information Theory for Wireless Communication: Scaling Laws and Optimal Operation

Xie, Liang-Liang; Kumar, P. R.

doi:10.1109/tit.2004.826631

Cited by 586 publications

(525 citation statements)

References 17 publications

Supporting

Mentioning

511

Contrasting

Order By: Relevance

“…The literature on scaling laws for wireless networks has concentrated on the two extremes where either the small-scale fading coefficient is not present in the model (h = 1) or is assumed to be independent and identically distributed across all node pairs in the wireless network. The results obtained can be roughly summarized as follows: for two-dimensional networks, the scaling law in (1) has been confirmed by information theoretic arguments for absorptive media (γ > 0) or under the assumption of large power path loss (α > 4), for both the cases where small scale fading is absent in the model (considered in [2], [4]) or is i.i.d across all node pairs in the network (considered in [3], [5]). For one-dimensional networks, (1) has been confirmed for α > 2.5.…”

Section: Introductionmentioning

confidence: 54%

“…2 We prove Theorem 2.1 in Section IV and Theorem 2.2 in Section V. The corresponding results for the transport capacity in Theorem 2.3 are discussed in Section VI. Section VII contains our conclusions.…”

Section: Theorem 23mentioning

confidence: 91%

“…In the present section, a more general result on the transport capacity of the network is obtained, without any prior assumption on the traffic demand. Our technique follows the approach developed in [2].…”

Section: Proof Of Proposition 52mentioning

confidence: 99%

“…With the motivation to study wireless networks without making any particular assumption on the way communication is established, there has been some subsequent work [2], [3], [4], [5] that tackles the problem from an information-theoretic point of view. These works have lead to the following partial answers to the problem.…”

Section: Introductionmentioning

confidence: 99%

“…(See [6, Chapter 2] for a detailed discussion on this model.) In (2), r is the distance between the transmitter and the receiver, α is called the power path loss exponent, γ is the absorption constant and thus the first term represents the attenuation of the signal due to electromagnetic propagation. The second term h models small scale fading due to constructive and destructive interference of multiple signal paths between the transmitter and the receiver.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Scaling Laws for One- and Two-Dimensional Random Wireless Networks in the Low-Attenuation Regime

Özgür¹,

Lévêque

Preissmann

2007

IEEE Trans. Inform. Theory

View full text Add to dashboard Cite

The capacity scaling of extended two-dimensional wireless networks is known in the high attenuation regime, i.e. when the power path loss exponent α is greater than 4. This has been accomplished by deriving information theoretic upper bounds for this regime that match the corresponding lower bounds. On the contrary, not much is known in the so-called low attenuation regime when 2 ≤ α ≤ 4. (For one-dimensional networks, the uncharacterized regime is 1 ≤ α ≤ 2.5.) The dichotomy is due to the fact that while communication is highly power-limited in the first case and power-based arguments suffice to get tight upper bounds, the study of the low attenuation regime requires a more precise analysis of the degrees of freedom involved. In this paper, we study the capacity scaling of extended wireless networks with an emphasis on the low attenuation regime and show that in the absence of small scale fading, the low attenuation regime does not behave significantly different from the high attenuation regime.

show abstract