434 research outputs found
Adaptive Bit Partitioning for Multicell Intercell Interference Nulling with Delayed Limited Feedback
Base station cooperation can exploit knowledge of the users' channel state
information (CSI) at the transmitters to manage co-channel interference. Users
have to feedback CSI of the desired and interfering channels using
finite-bandwidth backhaul links. Existing codebook designs for single-cell
limited feedback can be used for multicell cooperation by partitioning the
available feedback resources between the multiple channels. In this paper, a
new feedback-bit allocation strategy is proposed, as a function of the delays
in the communication links and received signal strengths in the downlink.
Channel temporal correlation is modeled as a function of delay using the
Gauss-Markov model. Closed-form expressions for bit partitions are derived to
allocate more bits to quantize the stronger channels with smaller delays and
fewer bits to weaker channels with larger delays, assuming random vector
quantization. Cellular network simulations are used to show that the proposed
algorithm yields higher sum-rates than an equal-bit allocation technique.Comment: Submitted to IEEE Transactions on Signal Processing, July 201
Sum-Rate Maximization for Linearly Precoded Downlink Multiuser MISO Systems with Partial CSIT: A Rate-Splitting Approach
This paper considers the Sum-Rate (SR) maximization problem in downlink
MU-MISO systems under imperfect Channel State Information at the Transmitter
(CSIT). Contrary to existing works, we consider a rather unorthodox
transmission scheme. In particular, the message intended to one of the users is
split into two parts: a common part which can be recovered by all users, and a
private part recovered by the corresponding user. On the other hand, the rest
of users receive their information through private messages. This
Rate-Splitting (RS) approach was shown to boost the achievable Degrees of
Freedom (DoF) when CSIT errors decay with increased SNR. In this work, the RS
strategy is married with linear precoder design and optimization techniques to
achieve a maximized Ergodic SR (ESR) performance over the entire range of SNRs.
Precoders are designed based on partial CSIT knowledge by solving a stochastic
rate optimization problem using means of Sample Average Approximation (SAA)
coupled with the Weighted Minimum Mean Square Error (WMMSE) approach. Numerical
results show that in addition to the ESR gains, the benefits of RS also include
relaxed CSIT quality requirements and enhanced achievable rate regions compared
to conventional transmission with NoRS.Comment: accepted to IEEE Transactions on Communication
The DoF of Network MIMO with Backhaul Delays
We consider the problem of downlink precoding for Network (multi-cell) MIMO
networks where Transmitters (TXs) are provided with imperfect Channel State
Information (CSI). Specifically, each TX receives a delayed channel estimate
with the delay being specific to each channel component. This model is
particularly adapted to the scenarios where a user feeds back its CSI to its
serving base only as it is envisioned in future LTE networks. We analyze the
impact of the delay during the backhaul-based CSI exchange on the rate
performance achieved by Network MIMO. We highlight how delay can dramatically
degrade system performance if existing precoding methods are to be used. We
propose an alternative robust beamforming strategy which achieves the maximal
performance, in DoF sense. We verify by simulations that the theoretical DoF
improvement translates into a performance increase at finite Signal-to-Noise
Ratio (SNR) as well
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