In this paper, we derive the capacity of a continuous-time, single-input single-output (SISO), frequency-selective, band-limited, linear time-invariant (LTI) channel, whose output is corrupted by a second-order cyclos...
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In this paper, we derive the capacity of a continuous-time, single-input single-output (SISO), frequency-selective, band-limited, linear time-invariant (LTI) channel, whose output is corrupted by a second-order cyclostationary (SOCS) complex Gaussian noise. By using a pair of invertible, linear-conjugate linear time-varying operators called a properizing FREquency SHift (p-FRESH) vectorizer and a p-FRESH scalarizer, it is shown that, whether the complex noise is proper or improper, the SISO channel can always be converted to an equivalent multiple-inputmultiple-output (MIMO) LTI channel whose output is now corrupted by a proper-complex vector wide-sense stationary noise. A variational problem is then formulated in the frequency domain to find the optimal input distribution that maximizes the throughput of the equivalent MIMO channel. It turns out that the optimal input to the SISO channel, obtained through a procedure similar to the water filling, is an SOCS complex Gaussian random process with the same cycle period as the noise. It is shown that this procedure, named cyclic water filling, significantly outperforms ordinary water filling by effectively utilizing the spectral correlation of the cyclostationary noise.
In this paper, we consider a downlink (DL) multiuser (MU) multi-input-multi-output (MIMO) channel with linear precoding where the base station simultaneously schedules several user terminals on the same frequency sub-...
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ISBN:
(纸本)9781457713484
In this paper, we consider a downlink (DL) multiuser (MU) multi-input-multi-output (MIMO) channel with linear precoding where the base station simultaneously schedules several user terminals on the same frequency sub-band. We assume imperfect (or quantized) per-user channel state information at the base station and present two types of channel state information (CSI) reports from user terminals, namely, the CSI report that assumes the single-user (SU) MIMO transmissions and the enhanced CSI feedback report that assumes the MU-MIMO transmissions, and in the latter case we consider both uniform and nonuniform power allocations. To improve the MU-MIMO system performance, we propose signal-to-interference-plus-noise ratio (SINR) approximation techniques that utilize the quantized CSI available at the base station and improve the rate matching. We also introduce user pooling techniques which enable a reduction in feedback signaling overhead via per-user feedback mode selection. The proposed techniques also allow unconstrained user pairing at the base station scheduler and hence enable dynamic switching between SU and MU MIMO transmissions. The simulation results demonstrate the efficiency of the proposed MU-MIMO enhancement techniques.
This paper discusses a method for increasing the eigenmode SNR by using a space-time linear precoder designed on a maximum likelihood (ML) basis (henceforth called the space-time linear ML precoder). First, the effect...
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This paper discusses a method for increasing the eigenmode SNR by using a space-time linear precoder designed on a maximum likelihood (ML) basis (henceforth called the space-time linear ML precoder). First, the effect of the length of the precoded signal generated in the ML precoder on the eigenmode SNR is studied. It is shown that the eigenmode SNR can be increased by varying the precoded signal length depending on the condition of the channel. Next, a transceiver configuration for increasing the eigenmode SNR by the space-time linear ML precoder is presented. In the proposed method, error propagation may be generated due to the transceiver configuration and the BER characteristics may be degraded, even if the eigenmode SNR is increased. In this paper, in order to reduce the effect of the error propagation the BER characteristics, the relationship between the average length of the error propagation can be minimized by limiting the region of search for the precoded signal length. Finally, the effectiveness of the proposed method is verified by numerical simulation. (C) 2007 Wiley Periodicals, Inc.
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