309 research outputs found
Simplified Cooperative Detection for Multi-Receiver Molecular Communication
Diffusion-based molecular communication (MC) systems experience significant
reliability losses. To boost the reliability, an MC scheme where multiple
receivers (RXs) work cooperatively to decide the signal of a transmitter (TX)
by sending the same type of molecules to a fusion center (FC) is proposed in
this paper. The FC observes the total number of molecules received and compares
this number with a threshold to determine the TX's signal. The proposed scheme
is more bio-realistic and requires relatively low computational complexity
compared to existing cooperative schemes where the RXs send and the FC
recognizes different types of molecules. Asymmetric and symmetric topologies
are considered, and closed-form expressions are derived for the global error
probability for both topologies. Results show that the trade-off for simplified
computations leads to a slight reduction in error performance, compared to the
existing cooperative schemes.Comment: 5 pages, 4 figures, Will be presented as an invited paper at the 2017
IEEE Information Theory Workshop in November 2017 in Kaohsiung, Taiwa
Channel characterization for 1D molecular communication with two absorbing receivers
This letter develops a one-dimensional (1D) diffusion-based molecular communication system to analyze channel responses between a single transmitter (TX) and two fully-absorbing receivers (RXs). Incorporating molecular degradation in the environment, rigorous analytical formulas for i) the fraction of molecules absorbed, ii) the corresponding hitting rate, and iii) the asymptotic fraction of absorbed molecules as time approaches infinity at each RX are derived when an impulse of molecules are released at the TX. By using particle-based simulations, the derived analytical expressions are validated. Simulations also present the distance ranges of two RXs that do not impact molecular absorption of each other, and demonstrate that the mutual influence of two active RXs reduces with the increase in the degradation rate
Parameter Estimation in a Noisy 1D Environment via Two Absorbing Receivers
This paper investigates the estimation of different parameters, e.g.,
propagation distance and flow velocity, by utilizing two fully-absorbing
receivers (RXs) in a one-dimensional (1D) environment. The time-varying number
of absorbed molecules at each RX and the number of absorbed molecules in a time
interval as time approaches infinity are derived. Noisy molecules in this
environment, that are released by sources in addition to the transmitter, are
also considered. A novel estimation method, namely difference estimation (DE),
is proposed to eliminate the effect of noise by using the difference of
received signals at the two RXs. For DE, the Cramer-Rao lower bound (CRLB) on
the variance of estimation is derived. Independent maximum likelihood
estimation is also considered at each RX as a benchmark to show the performance
advantage of DE. Aided by particle-based simulation, the derived analytical
results are verified. Furthermore, numerical results show that DE attains the
CRLB and is less sensitive to the change of noise than independent estimation
at each RX.Comment: 7 pages, 5 figures, accepted by Globecom 202
Effect of Local Population Uncertainty on Cooperation in Bacteria
Bacteria populations rely on mechanisms such as quorum sensing to coordinate
complex tasks that cannot be achieved by a single bacterium. Quorum sensing is
used to measure the local bacteria population density, and it controls
cooperation by ensuring that a bacterium only commits the resources for
cooperation when it expects its neighbors to reciprocate. This paper proposes a
simple model for sharing a resource in a bacterial environment, where knowledge
of the population influences each bacterium's behavior. Game theory is used to
model the behavioral dynamics, where the net payoff (i.e., utility) for each
bacterium is a function of its current behavior and that of the other bacteria.
The game is first evaluated with perfect knowledge of the population. Then, the
unreliability of diffusion introduces uncertainty in the local population
estimate and changes the perceived payoffs. The results demonstrate the
sensitivity to the system parameters and how population uncertainty can
overcome a lack of explicit coordination.Comment: 5 pages, 6 figures. Will be presented as an invited paper at the 2017
IEEE Information Theory Workshop in November 2017 in Kaohsiung, Taiwa
Maximum Likelihood Detection for Cooperative Molecular Communication
In this paper, symbol-by-symbol maximum likelihood (ML) detection is proposed
for a cooperative diffusion-based molecular communication (MC) system. In this
system, a fusion center (FC) chooses the transmitter's symbol that is more
likely, given the likelihood of the observations from multiple receivers (RXs).
We propose three different ML detection variants according to different
constraints on the information available to the FC, which enables us to
demonstrate trade-offs in their performance versus the information available.
The system error probability for one variant is derived in closed form.
Numerical and simulation results show that the ML detection variants provide
lower bounds on the error performance of the simpler cooperative variants and
demonstrate that majority rule detection has performance comparable to ML
detection when the reporting is noisy.Comment: 7 pages, 4 figurs. This work has been accepted by the IEEE ICC 201
Optimum Reconfigurable Intelligent Surface Selection for Indoor and Outdoor Communications
The reconfigurable intelligent surface (RIS) is a promising technology that
is anticipated to enable high spectrum and energy efficiencies in future
wireless communication networks. This paper investigates optimum location-based
RIS selection policies in RIS-aided wireless networks to maximize the signal-to
noise ratio (SNR) for a power path-loss model in outdoor communications and an
exponential path-loss model in indoor communications. The random locations of
all available RISs are modeled as a Poisson point process (PPP). To quantify
the network performance, the outage probabilities and average rates attained by
the proposed RIS selection policies are evaluated by deriving the distance
distribution of the chosen RIS node as per the selection policies for both
power and exponential path-loss models. Feedback could incur heavy signaling
overhead. To reduce the overhead, we also propose limited-feedback RIS
selection policies by limiting the average number of RISs that feed back their
location information to the source. The outage probabilities and average rates
obtained by the limited-feedback RIS selection policies are derived for both
path-loss models. The numerical results show notable performance gains obtained
by the proposed RIS selection policies and demonstrate that the conventional
relay selection policies are not suitable for RIS-aided wireless networks
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