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Wikipedia / Zero-forcing precoding

Zero-forcing (or null-steering) precoding is a method of spatial signal processing by which a multiple antenna transmitter can null the multiuser interference in a multi-user MIMO wireless communication system. When the channel state information is perfectly known at the transmitter, the zero-forcing precoder is given by the pseudo-inverse of the channel matrix. Zero-forcing has been used in LTE mobile networks.

Mathematical description

is described as

.

The above signal model can be more compactly re-written as

where

  1. received signal vector,

  2. channel matrix,

  3. precoding matrix,

  4. diagonal power matrix, and

  5. transmit signal.

A zero-forcing precoder. That is,

Thus the interference caused by the signal meant for one user is effectively nullified for rest of the users via zero-forcing precoder.

From the fact that each beam generated by zero-forcing precoder is orthogonal to all the other user channel vectors, one can rewrite the received signal as

The orthogonality condition can be expressed in matrix form as

diagonal matrix is selected to be an identity matrix the right Moore-Penrose pseudo-inverse given by

Given this zero-forcing precoder design, the received signal at each user is decoupled from each other as

Quantify the feedback amount

Quantify the amount of the feedback resource required to maintain at least a given throughput performance gap between zero-forcing with perfect feedback and with limited feedback, i.e.,

  1. .

Jindal showed that the required feedback bits of a spatially uncorrelated channel should be scaled according to SNR of the downlink channel, which is given by:

where M is the SNR of the downlink channel.

To feed back B bits though the uplink channel, the throughput performance of the uplink channel should be larger than or equal to 'B'

is

  1. .

is constant and both SNRs are sufficiently high. Then, the feedback resource will be only proportional to the number of transmit antennas

  1. .

) is not necessary to scale according to SNR of the downlink channel, which is almost contradict to the case of the feedback bits. One, hence, sees that the whole systematic analysis can reverse the facts resulted from each reductioned situation.

Performance

If the transmitter knows the downlink channel state information (CSI) perfectly, ZF-precoding can achieve almost the system capacity when the number of users is large. On the other hand, with limited channel state information at the transmitter (CSIT) the performance of ZF-precoding decreases depending on the accuracy of CSIT. ZF-precoding requires the significant feedback overhead with respect to signal-to-noise-ratio (SNR) so as to achieve the full multiplexing gain. Inaccurate CSIT results in the significant throughput loss because of residual multiuser interferences. Multiuser interferences remain since they can not be nulled with beams generated by imperfect CSIT.

See also

References