409 research outputs found
Relative Entropy-Based Waveform Optimization for Rician Target Detection with Dual-Function Radar Communication Systems
In this paper, we consider waveform design for dualfunction
radar-communication systems based on multiple-inputmultiple-out arrays. To
achieve better Rician target detection performance, we use the relative entropy
associated with the formulated detection problem as the design metric. We also
impose a multiuser interference energy constraint on the waveforms to ensure
the achievable sum-rate of the communications. Two algorithms are presented to
tackle the nonlinear non-convex waveform design problem. In the first
algorithm, we derive a quadratic function to minorize the objective function.
To tackle the quadratically constrained quadratic programming problem at each
iteration, a semidefinite relaxation approach followed by a rank-one
decomposition procedure and an efficient alternating direction method of
multipliers (ADMM) are proposed, respectively. In the second algorithm, we
present a novel ADMM algorithm to tackle the optimization problem and employ an
efficient minorization-maximization approach in the inner loop of the ADMM
algorithm. Numerical results demonstrate the superiority of both algorithms.
Moreover, the presented algorithms can be extended to synthesize
peak-to-average-power ratio constrained waveforms, which allows the radio
frequency amplifier to operate at an increased efficiency
On the Monotonicity of the Generalized Marcum and Nuttall Q-Functions
Monotonicity criteria are established for the generalized Marcum Q-function,
\emph{Q}_{M}, the standard Nuttall Q-function, \emph{Q}_{M,N}, and the
normalized Nuttall Q-function, , with respect to their real
order indices M,N. Besides, closed-form expressions are derived for the
computation of the standard and normalized Nuttall Q-functions for the case
when M,N are odd multiples of 0.5 and . By exploiting these results,
novel upper and lower bounds for \emph{Q}_{M,N} and are
proposed. Furthermore, specific tight upper and lower bounds for
\emph{Q}_{M}, previously reported in the literature, are extended for real
values of M. The offered theoretical results can be efficiently applied in the
study of digital communications over fading channels, in the
information-theoretic analysis of multiple-input multiple-output systems and in
the description of stochastic processes in probability theory, among others.Comment: Published in IEEE Transactions on Information Theory, August 2009.
Only slight formatting modification
Exact MIMO Zero-Forcing Detection Analysis for Transmit-Correlated Rician Fading
We analyze the performance of multiple input/multiple output (MIMO)
communications systems employing spatial multiplexing and zero-forcing
detection (ZF). The distribution of the ZF signal-to-noise ratio (SNR) is
characterized when either the intended stream or interfering streams experience
Rician fading, and when the fading may be correlated on the transmit side.
Previously, exact ZF analysis based on a well-known SNR expression has been
hindered by the noncentrality of the Wishart distribution involved. In
addition, approximation with a central-Wishart distribution has not proved
consistently accurate. In contrast, the following exact ZF study proceeds from
a lesser-known SNR expression that separates the intended and interfering
channel-gain vectors. By first conditioning on, and then averaging over the
interference, the ZF SNR distribution for Rician-Rayleigh fading is shown to be
an infinite linear combination of gamma distributions. On the other hand, for
Rayleigh-Rician fading, the ZF SNR is shown to be gamma-distributed. Based on
the SNR distribution, we derive new series expressions for the ZF average error
probability, outage probability, and ergodic capacity. Numerical results
confirm the accuracy of our new expressions, and reveal effects of interference
and channel statistics on performance.Comment: 14 pages, two-colum, 1 table, 10 figure
Sensing Aided Covert Communications: Turning Interference into Allies
In this paper, we investigate the realization of covert communication in a
general radar-communication cooperation system, which includes integrated
sensing and communications as a special example. We explore the possibility of
utilizing the sensing ability of radar to track and jam the aerial adversary
target attempting to detect the transmission. Based on the echoes from the
target, the extended Kalman filtering technique is employed to predict its
trajectory as well as the corresponding channels. Depending on the maneuvering
altitude of adversary target, two channel models are considered, with the aim
of maximizing the covert transmission rate by jointly designing the radar
waveform and communication transmit beamforming vector based on the constructed
channels. For the free-space propagation model, by decoupling the joint design,
we propose an efficient algorithm to guarantee that the target cannot detect
the transmission. For the Rician fading model, since the multi-path components
cannot be estimated, a robust joint transmission scheme is proposed based on
the property of the Kullback-Leibler divergence. The convergence behaviour,
tracking MSE, false alarm and missed detection probabilities, and covert
transmission rate are evaluated. Simulation results show that the proposed
algorithms achieve accurate tracking. For both channel models, the proposed
sensing-assisted covert transmission design is able to guarantee the
covertness, and significantly outperforms the conventional schemes.Comment: 13 pages, 12 figures, submitted to IEEE journals for potential
publicatio
Sensing-Assisted Eavesdropper Estimation: An ISAC Breakthrough in Physical Layer Security
In this paper, we investigate the sensing-aided physical layer security (PLS) towards Integrated Sensing and Communication (ISAC) systems. A well-known limitation of PLS is the need to have information about potential eavesdroppers (Eves). The sensing functionality of ISAC offers an enabling role here, by estimating the directions of potential Eves to inform PLS. In our approach, the ISAC base station (BS) firstly emits an omnidirectional waveform to search for potential Eves’ directions by employing the combined Capon and approximate maximum likelihood (CAML) technique. Using the resulting information about potential Eves, we formulate secrecy rate expressions, which is a function of the Eves’ estimation accuracy. We then formulate a weighted optimization problem to simultaneously maximize the secrecy rate with the aid of the artificial noise (AN), and minimize the Cramér-Rao Bound (CRB) of targets’/Eves’ estimation. By taking the possible estimation errors into account, we enforce a beampattern constraint with a wide main beam covering all possible directions of Eves. This implicates that security needs to be enforced in all these directions. By improving estimation accuracy, the sensing and security functionalities provide mutual benefits, resulting in improvement of the mutual performances with every iteration of the optimization, until convergence. Our results avail of these mutual benefits and reveal the usefulness of sensing as an enabler for practical PLS
6G Enabled Advanced Transportation Systems
The 6th generation (6G) wireless communication network is envisaged to be
able to change our lives drastically, including transportation. In this paper,
two ways of interactions between 6G communication networks and transportation
are introduced. With the new usage scenarios and capabilities 6G is going to
support, passengers on all sorts of transportation systems will be able to get
data more easily, even in the most remote areas on the planet. The quality of
communication will also be improved significantly, thanks to the advanced
capabilities of 6G. On top of providing seamless and ubiquitous connectivity to
all forms of transportation, 6G will also transform the transportation systems
to make them more intelligent, more efficient, and safer. Based on the latest
research and standardization progresses, technical analysis on how 6G can
empower advanced transportation systems are provided, as well as challenges and
insights for a possible road ahead.Comment: Submitted to an open access journa
Sensing-Assisted Eavesdropper Estimation: An ISAC Breakthrough in Physical Layer Security
In this paper, we investigate the sensing-aided
physical layer security (PLS) towards Integrated Sensing and
Communication (ISAC) systems. A well-known limitation of PLS
is the need to have information about potential eavesdroppers
(Eves). The sensing functionality of ISAC offers an enabling role
here, by estimating the directions of potential Eves to inform PLS.
In our approach, the ISAC base station (BS) firstly emits an omnidirectional waveform to search for potential Eves’ directions by
employing the combined Capon and approximate maximum likelihood (CAML) technique. Using the resulting information about
potential Eves, we formulate secrecy rate expressions, that are a
function of the Eves’ estimation accuracy. We then formulate a
weighted optimization problem to simultaneously maximize the
secrecy rate and minimize the CRB with the aid of the artificial
noise (AN), and minimize the CRB of targets’/Eves’ estimation.
By taking the possible estimation errors into account, we enforce
a beampattern constraint with a wide main beam covering all
possible directions of Eves. This implicates that security needs
to be enforced in all these directions. By improving estimation
accuracy, the sensing and security functionalities provide mutual
benefits, resulting in improvement of the mutual performances
with every iteration of the optimization, until convergence. Our
results avail of these mutual benefits and reveal the usefulness
of sensing as an enabler for practical PLS
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