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Cited by 554 publications
(546 citation statements)
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References 28 publications
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“…In Figure 4, the lower boundsẼ k , k = 1, · · · , K in (18), are compared with the simulation results obtained by (5) using 500 small-scale fading channel realizations, under the uniform power control, i.e., η l,k = 1/K, ∀l, k. It is seen that the gap between the lower-boundẼ k and the simulation result is less than 10%. This is because (17) as N is large. In Figure 5, the closed-form Γ k in (19) is compared with the simulation results obtained by (9) using 500 small-scale fading channel realizations with full transmit power, i.e.…”
Section: Numerical Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…In Figure 4, the lower boundsẼ k , k = 1, · · · , K in (18), are compared with the simulation results obtained by (5) using 500 small-scale fading channel realizations, under the uniform power control, i.e., η l,k = 1/K, ∀l, k. It is seen that the gap between the lower-boundẼ k and the simulation result is less than 10%. This is because (17) as N is large. In Figure 5, the closed-form Γ k in (19) is compared with the simulation results obtained by (9) using 500 small-scale fading channel realizations with full transmit power, i.e.…”
Section: Numerical Resultsmentioning
confidence: 99%
“…In cell-free massive MIMO, a large number of access points (APs) are distributed over a large area. These APs collaboratively serve a large number of terminals using the same time-frequency resource [16], [17]. In contrast to collocated (cellular) massive MIMO, cell-free massive MIMO is a user-centric architecture [18], since each terminal is served by the adjacent distributed APs.…”
mentioning
confidence: 99%
“…The performance variations within the coverage area can consequently be greatly reduced as compared to cellular networks. The same effect cannot be achieved by densifying a cellular network [17,18], following the fact that the transmitted and received signals are coherently processed among the distributed antennas to achieve array gains and spatial interference suppression.…”
Section: Cell-free Network: Concept and Value For Radioweavesmentioning
confidence: 99%
“…Recent works have developed new tools to analyze cellfree massive MIMO performance under practical channel state information [17,18] and developed distributed signal processing algorithms and resource allocation protocols that are scalable for large-scale deployment [19]. While a central network entity is needed to control a cell-free network, it is desirable to distribute the computations as much as possible over the network infrastructure, to limit the required signaling between the antennas and from the antennas to the central entity.…”
Section: Cell-free Network: Concept and Value For Radioweavesmentioning
confidence: 99%
“…However, inter-cell interference is inherent in all cell-centric systems and becomes a major performance limiting factor [7]. To overcome this, while preserving the main benefits of massive MIMO (m-MIMO), cell-free (CF) mMIMO has been proposed [8], [9]. The basic premise of it is that a large number of spatially-distributed APs serve many single-antenna users in the same time-frequency resources [8].…”
Section: Introductionmentioning
confidence: 99%