925 research outputs found
On the capacity of MIMO broadcast channels with partial side information
In multiple-antenna broadcast channels, unlike point-to-point multiple-antenna channels, the multiuser capacity depends heavily on whether the transmitter knows the channel coefficients to each user. For instance, in a Gaussian broadcast channel with M transmit antennas and n single-antenna users, the sum rate capacity scales like Mloglogn for large n if perfect channel state information (CSI) is available at the transmitter, yet only logarithmically with M if it is not. In systems with large n, obtaining full CSI from all users may not be feasible. Since lack of CSI does not lead to multiuser gains, it is therefore of interest to investigate transmission schemes that employ only partial CSI. We propose a scheme that constructs M random beams and that transmits information to the users with the highest signal-to-noise-plus-interference ratios (SINRs), which can be made available to the transmitter with very little feedback. For fixed M and n increasing, the throughput of our scheme scales as MloglognN, where N is the number of receive antennas of each user. This is precisely the same scaling obtained with perfect CSI using dirty paper coding. We furthermore show that a linear increase in throughput with M can be obtained provided that M does not not grow faster than logn. We also study the fairness of our scheduling in a heterogeneous network and show that, when M is large enough, the system becomes interference dominated and the probability of transmitting to any user converges to 1/n, irrespective of its path loss. In fact, using M=αlogn transmit antennas emerges as a desirable operating point, both in terms of providing linear scaling of the throughput with M as well as in guaranteeing fairness
Performance of Orthogonal Beamforming for SDMA with Limited Feedback
On the multi-antenna broadcast channel, the spatial degrees of freedom
support simultaneous transmission to multiple users. The optimal multiuser
transmission, known as dirty paper coding, is not directly realizable.
Moreover, close-to-optimal solutions such as Tomlinson-Harashima precoding are
sensitive to CSI inaccuracy. This paper considers a more practical design
called per user unitary and rate control (PU2RC), which has been proposed for
emerging cellular standards. PU2RC supports multiuser simultaneous
transmission, enables limited feedback, and is capable of exploiting multiuser
diversity. Its key feature is an orthogonal beamforming (or precoding)
constraint, where each user selects a beamformer (or precoder) from a codebook
of multiple orthonormal bases. In this paper, the asymptotic throughput scaling
laws for PU2RC with a large user pool are derived for different regimes of the
signal-to-noise ratio (SNR). In the multiuser-interference-limited regime, the
throughput of PU2RC is shown to scale logarithmically with the number of users.
In the normal SNR and noise-limited regimes, the throughput is found to scale
double logarithmically with the number of users and also linearly with the
number of antennas at the base station. In addition, numerical results show
that PU2RC achieves higher throughput and is more robust against CSI
quantization errors than the popular alternative of zero-forcing beamforming if
the number of users is sufficiently large.Comment: 27 pages; to appear in IEEE Transactions on Vehicular Technolog
How much feedback is required in MIMO Broadcast Channels?
In this paper, a downlink communication system, in which a Base Station (BS)
equipped with M antennas communicates with N users each equipped with K receive
antennas (), is considered. It is assumed that the receivers have
perfect Channel State Information (CSI), while the BS only knows the partial
CSI, provided by the receivers via feedback. The minimum amount of feedback
required at the BS, to achieve the maximum sum-rate capacity in the asymptotic
case of and different ranges of SNR is studied. In the fixed and
low SNR regimes, it is demonstrated that to achieve the maximum sum-rate, an
infinite amount of feedback is required. Moreover, in order to reduce the gap
to the optimum sum-rate to zero, in the fixed SNR regime, the minimum amount of
feedback scales as , which is achievable by the Random
Beam-Forming scheme proposed in [14]. In the high SNR regime, two cases are
considered; in the case of , it is proved that the minimum amount of
feedback bits to reduce the gap between the achievable sum-rate and the maximum
sum-rate to zero grows logaritmically with SNR, which is achievable by the
"Generalized Random Beam-Forming" scheme, proposed in [18]. In the case of , it is shown that by using the Random Beam-Forming scheme and the total
amount of feedback not growing with SNR, the maximum sum-rate capacity is
achieved.Comment: Submitted to IEEE Trans. on Inform. Theor
Interference Alignment Through User Cooperation for Two-cell MIMO Interfering Broadcast Channels
This paper focuses on two-cell multiple-input multiple-output (MIMO) Gaussian
interfering broadcast channels (MIMO-IFBC) with cooperating users on the
cell-boundary of each BS. It corresponds to a downlink scenario for cellular
networks with two base stations (BSs), and users equipped with Wi-Fi
interfaces enabling to cooperate among users on a peer-to-peer basis. In this
scenario, we propose a novel interference alignment (IA) technique exploiting
user cooperation. Our proposed algorithm obtains the achievable degrees of
freedom (DoF) of 2K when each BS and user have transmit antennas and
receive antennas, respectively. Furthermore, the algorithm requires only
a small amount of channel feedback information with the aid of the user
cooperation channels. The simulations demonstrate that not only are the
analytical results valid, but the achievable DoF of our proposed algorithm also
outperforms those of conventional techniques.Comment: This paper will appear in IEEE GLOBECOM 201
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