2013
DOI: 10.1109/tit.2013.2253153
|View full text |Cite
|
Sign up to set email alerts
|

Fundamental Limits of Cooperation

Abstract: Cooperation is viewed as a key ingredient for interference management in wireless systems. This paper shows that cooperation has fundamental limitations. The main result is that even full cooperation between transmitters cannot in general change an interference-limited network to a noise-limited network. The key idea is that there exists a spectral efficiency upper bound that is independent of the transmit power. First, a spectral efficiency upper bound is established for systems that rely on pilot-assisted ch… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

13
297
0

Year Published

2013
2013
2021
2021

Publication Types

Select...
5
3

Relationship

0
8

Authors

Journals

citations
Cited by 309 publications
(315 citation statements)
references
References 56 publications
13
297
0
Order By: Relevance
“…The inequality is obtained by using Cauchy-Schwarz' inequality, which holds with equality when a a a k = cΛ Λ Λ −1 k g g g k , for any c ∈ C. This corresponds to the MMSE detector (see (23)). This implies that the MMSE detector is optimal in the sense that it maximizes the achievable rate given by (12).…”
Section: ) Minimum Mean-squared Error Receiver: For Mmse the Detectmentioning
confidence: 99%
See 1 more Smart Citation
“…The inequality is obtained by using Cauchy-Schwarz' inequality, which holds with equality when a a a k = cΛ Λ Λ −1 k g g g k , for any c ∈ C. This corresponds to the MMSE detector (see (23)). This implies that the MMSE detector is optimal in the sense that it maximizes the achievable rate given by (12).…”
Section: ) Minimum Mean-squared Error Receiver: For Mmse the Detectmentioning
confidence: 99%
“…When shrinking the cell size, one typically also cuts back on the power. Hence, the relation between signal and interference power would not be substantially different in systems with smaller cells and in that sense, the analysis is largely independent of the actual physical size of the cell [23]. Note that, setting L = 7 means that we consider the performance of a given cell with the interference from 6 nearest-neighbor cells.…”
Section: B Multicell Mu-mimo Systemsmentioning
confidence: 99%
“…In our studies, we have seen that this is due to the approximations made when calculatingĒ [ H * V * V H] in (14) by using (7), (15) and (16). This overestimates the variance of the prediction error as discussed in Section 3.2.…”
Section: Precoding Performancementioning
confidence: 77%
“…Investigations in [11,14] show that a cluster size above 7 to 9 cells will not provide large additional gains for systems with MIMO links. In [15], for few base station antennas, a cluster that used transmitters at three separate sites was adequate to attain most of the achievable CoMP gains (see also [16]). Our evaluations in Sections 6 and 7 focus on a cluster size of three sites, partially motivated by the results of [15] and partially due to the limitations of our measurements.…”
Section: Assumptions Design Choices and Related Workmentioning
confidence: 99%
“…9 It is worth pointing out that σ 2 k is implicitly coupled with the power constraints; if the system-wide power usage is increased, then the uncoordinated interference will also increase. This relationship has no particular impact on this tutorial since our power constraints are fixed, but is of paramount importance in any asymptotic analysis because multi-cell systems are fundamentally interference-limited in the high-SNR regime [164]. When nothing else is said, BS j is assumed to know the channels h jk and variances σ 2 k perfectly to all users k ∈C j .…”
mentioning
confidence: 99%