106 research outputs found
Spectrum Sharing Opportunities of Full-Duplex Systems using Improper Gaussian Signaling
Sharing the licensed spectrum of full-duplex (FD) primary users (PU) brings
strict limitations on the underlay cognitive radio operation. Particularly, the
self interference may overwhelm the PU receiver and limit the opportunity of
secondary users (SU) to access the spectrum. Improper Gaussian signaling (IGS)
has demonstrated its superiority in improving the performance of interference
channel systems. Throughout this paper, we assume a FD PU pair that uses proper
Gaussian signaling (PGS), and a half-duplex SU pair that uses IGS. The
objective is to maximize the SU instantaneous achievable rate while meeting the
PU quality-of-service. To this end, we propose a simplified algorithm that
optimizes the SU signal parameters, i.e, the transmit power and the circularity
coefficient, which is a measure of the degree of impropriety of the SU signal,
to achieve the design objective. Numerical results show the merits of adopting
IGS compared with PGS for the SU especially with the existence of week PU
direct channels and/or strong SU interference channels
Robust Transceiver Design for IRS-Assisted Cascaded MIMO Systems
{Robust transceiver design against unresolvable system uncertainties is of
crucial importance for reliable communication. We consider a MIMO multi-hop
system, where the source, the relay, and the destination are equipped with
multiple antennas. Further, an intelligent reconfigurable surface (IRS) is
established to cancel the RSI as much as possible. The considered
decode-and-forward (DF) hybrid relay can operate in either half-duplex or
full-duplex mode, and the mode changes adaptively depending on the RSI
strength. We investigate a robust transceiver design problem, which maximizes
the throughput rate corresponding to the worst-case RSI under a
self-interference channel uncertainty bound constraint. To the best of our
knowledge, this is the first work that uses the IRS for RSI cancellation in
MIMO full-duplex DF relay systems. The yielded problem turns out to be a
non-convex optimization problem, where the non-convex objective is optimized
over the cone of semidefinite matrices. We propose a closed-from lower bound
for the IRS worst case RSI cancellation. Eventually, we show an important
result that, for the worst case scenario, IRS can be helpful only if the number
of IRS elements are at least as large as the size of the interference channel.
Moreover, a novel method based on majorization theory is proposed to find the
best response of the transmitters and relay against worst case RSI.
Furthermore, we propose a multi-level water-filling algorithm to obtain a
locally optimal solution iteratively. Finally, we obtain insights on the
optimal antenna allocation at the relay input-frontend and output-frontend, for
relay reception and transmission, respectively.Comment: arXiv admin note: substantial text overlap with arXiv:1912.1283
- …