60 research outputs found
Secure Massive MIMO Communication with Low-resolution DACs
In this paper, we investigate secure transmission in a massive multiple-input
multiple-output (MIMO) system adopting low-resolution digital-to-analog
converters (DACs). Artificial noise (AN) is deliberately transmitted
simultaneously with the confidential signals to degrade the eavesdropper's
channel quality. By applying the Bussgang theorem, a DAC quantization model is
developed which facilitates the analysis of the asymptotic achievable secrecy
rate. Interestingly, for a fixed power allocation factor , low-resolution
DACs typically result in a secrecy rate loss, but in certain cases they provide
superior performance, e.g., at low signal-to-noise ratio (SNR). Specifically,
we derive a closed-form SNR threshold which determines whether low-resolution
or high-resolution DACs are preferable for improving the secrecy rate.
Furthermore, a closed-form expression for the optimal is derived. With
AN generated in the null-space of the user channel and the optimal ,
low-resolution DACs inevitably cause secrecy rate loss. On the other hand, for
random AN with the optimal , the secrecy rate is hardly affected by the
DAC resolution because the negative impact of the quantization noise can be
compensated for by reducing the AN power. All the derived analytical results
are verified by numerical simulations.Comment: 14 pages, 10 figure
A Universal Framework of Superimposed RIS-Phase Modulation for MISO Communication
To fully exploit the additional dimension brought by reconfigurable
intelligent surface (RIS), it is recently suggested by information theory that
modulating information upon RIS phases is able to send extra information with
increased communication rate. In this paper, we propose a novel superimposed
RIS-phase modulation (SRPM) scheme to transfer extra messages by superimposing
information-bearing phase offsets to conventionally optimized RIS phases. The
proposed SRPM is interpreted as a universal framework for RIS phase modulation.
Theoretical union bound of the average bit error rate (ABER) of the proposed
SRPM is also derived with the maximum likelihood (ML) detection. The diversity
order is characterized as 0.5 for all parameter settings, which is useful for
determining the optimal choice of the phase modulation parameters. Furthermore,
we discover that doubling the number of either RIS reflecting elements or the
transmit antennas is equivalent to a 3 dB increment in the transmit power for
SRPM. Numerical results demonstrate the effectiveness of SRPM and reveal that
it achieves reliable communication of more bits than existing schemes.Comment: Accepted by IEEE Transactions on Vehicular Technolog
Superimposed RIS-phase Modulation for MIMO Communications: A Novel Paradigm of Information Transfer
Reconfigurable intelligent surface (RIS) is regarded as an important enabling
technology for the sixth-generation (6G) network. Recently, modulating
information in reflection patterns of RIS, referred to as reflection modulation
(RM), has been proven in theory to have the potential of achieving higher
transmission rate than existing passive beamforming (PBF) schemes of RIS. To
fully unlock this potential of RM, we propose a novel superimposed RIS-phase
modulation (SRPM) scheme for multiple-input multiple-output (MIMO) systems,
where tunable phase offsets are superimposed onto predetermined RIS phases to
bear extra information messages. The proposed SRPM establishes a universal
framework for RM, which retrieves various existing RM-based schemes as special
cases. Moreover, the advantages and applicability of the SRPM in practice is
also validated in theory by analytical characterization of its performance in
terms of average bit error rate (ABER) and ergodic capacity. To maximize the
performance gain, we formulate a general precoding optimization at the base
station (BS) for a single-stream case with uncorrelated channels and obtain the
optimal SRPM design via the semidefinite relaxation (SDR) technique.
Furthermore, to avoid extremely high complexity in maximum likelihood (ML)
detection for the SRPM, we propose a sphere decoding (SD)-based layered
detection method with near-ML performance and much lower complexity. Numerical
results demonstrate the effectiveness of SRPM, precoding optimization, and
detection design. It is verified that the proposed SRPM achieves a higher
diversity order than that of existing RM-based schemes and outperforms PBF
significantly especially when the transmitter is equipped with limited
radio-frequency (RF) chains.Comment: Submitted to IEEE for possible publicatio
- …