Sum capacity of Gaussian vector broadcast channels

By Wei Yu, John M. Cioffi. IEEE Transactions on Information Theory, 2004

784 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/5d2fa609a50445714d94d3d71ac1138f5bf1f0c9

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In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

Multiuser MIMO Achievable Rates With Downlink Training and Channel State Feedback (2007, background): “Under the assumption of perfect channel state information at the transmitter (CSIT) and at the receivers (CSIR), a combination of singleuser Gaussian codes, linear beamforming and “Dirty-Paper Coding” (DPC) [3] is known to achieve the capacity of the MIMO downlink channel [4], [5], [6], [7], [8].”
Weighted sum-rate maximization using weighted MMSE for MIMO-BC beamforming design (2008, methodology): “However, practical techniques to implement DPC [3], [4], [5], are in preliminary states of development and are dif ﬁ cult to implement in practice because of their high computational burden.”
Non-orthogonal Multiple Access (NOMA) with Successive Interference Cancellation for Future Radio Access (2015, background): “The optimal order for decoding in the downlink is in the order of the increasing channel gain normalized by the noise plus inter-cell interference power, |hi|2/N0,i [5], [6], [8]–[11].”
Interference Alignment and the Degrees of Freedom of Wireless $X$ Networks (2009, background): “Starting with the point to point MIMO channel [1], [2], the degrees of freedom have been character ized for MIMO multiple access channel (MAC) [3], MIMO broadcast channel (BC) [4]–[6], 2 user MIMO interferen ce channel [7], various distributed relay networks [8]–[10], 2 user MIMO X channel [11]–[15]”
Sum capacity of the vector Gaussian broadcast channel and uplink-downlink duality (2003, background): “An independent and different proof is given in [22], where the authors directly worked with the downlink channel and showed the existence of a noise covariance such that cooperating among the receivers did not provide any additional benefit.”
Fundamentals of Wireless Communication (2005, background): “The optimality of these schemes for the sum rate was shown in [17, 138, 151, 134].”
MIMO broadcast channels with finite rate feedback (2006, positive): “When perfect CSI is available at transmitter and receivers, the capacity region of the channel is achieved by dirty-paper coding [14] [1] [15] [16] [17], which is a tech nique that can be used to pre-cancel multiuser interference at the transmitter [18].”
MIMO Broadcast Channels With Finite-Rate Feedback (2006, methodology): “When perfect CSI is available at transmitter and receivers, the capacity region of the channel is achieved by dirty-paper coding [15], [1], [16]–[18], which is a technique that can be used to pre-cancel multiuser interference at the transmitter [19].”
Sub-Channel Assignment, Power Allocation, and User Scheduling for Non-Orthogonal Multiple Access Networks (2016, background): “The decoding order described above guarantees that the upp er bound on the capacity region can be reached [21], [22], i.”
Interference Alignment and Spatial Degrees of Freedom for the K User Interference Channel (2007, methodology): “(17) has linearly independent column vectors where D = (H̄([11]))H̄([12]) is a diagonal matrix.”