39 research outputs found
Performance Analysis for Near-Field MIMO: Discrete and Continuous Aperture Antennas
Performance analysis is carried out in a near-field multiple-input
multiple-output (MIMO) system for both discrete and continuous aperture
antennas. The effective degrees of freedom (EDoF) is first derived. It is shown
that near-field MIMO systems have a higher EDoF than free-space far-field ones.
Additionally, the near-field EDoF further depends on the communication
distance. Based on the derived EDoF, closed-form expressions of channel
capacity with a fixed distance are obtained. As a further advance, with
randomly deployed receivers, ergodic capacity is derived. Simulation results
reveal that near-field MIMO has an enhanced multiplexing gain even under
line-of-sight transmissions. In addition, the performance of discrete MIMO
converges to that of continuous-aperture MIMO.Comment: 5 pages, 3 figure
Physical Layer Security for STAR-RIS-NOMA in Large-Scale Networks
In this paper, an analytical framework for secure simultaneous transmitting
and reflecting reconfigurable intelligent surface (STAR-RIS) assisted
non-orthogonal multiple access (NOMA) transmissions in large-scale networks is
proposed, where users and eavesdroppers are randomly distributed. Both the
time-switching protocol (TS) and energy splitting (ES) protocol are considered
for the STAR-RIS. To characterize system performance, the channel statistics
are first provided, and the Gamma approximation is adopted for general cascaded
- fading. Afterward, the closed-form expressions for both the
secrecy outage probability and secrecy ergodic rate are derived. To obtain
further insights, the asymptotic performance for the secrecy diversity order
and the secrecy slope are deduced. The theoretical results show that 1) the
secrecy diversity orders of the strong user and the weak user depend on the
path loss exponent and the distribution of the received signal-to-noise ratio,
respectively; 2) the secrecy slope of the ES protocol achieves the value of
one, higher than the slope of the TS protocol which is the mode operation
parameter of TS. The numerical results demonstrate that: 1) there is an optimal
STAR-RIS mode operation parameter to maximize the system performance; 2) the
STAR-RIS-NOMA significantly outperforms the STAR-RIS-orthogonal multiple
access.Comment: 30 pages, 7 figure
Using Natural Language Explanations to Improve Robustness of In-context Learning for Natural Language Inference
Recent studies have demonstrated that large language models (LLMs) excel in
diverse tasks through in-context learning (ICL) facilitated by task-specific
prompts and examples. However, the existing literature shows that ICL
encounters performance deterioration when exposed to adversarial inputs.
Enhanced performance has been observed when ICL is augmented with natural
language explanations (NLEs) (we refer to it as X-ICL). Thus, this work
investigates whether X-ICL can improve the robustness of LLMs on a suite of
seven adversarial and challenging natural language inference datasets.
Moreover, we introduce a new approach to X-ICL by prompting an LLM (ChatGPT in
our case) with few human-generated NLEs to produce further NLEs (we call it
ChatGPT few-shot), which we show superior to both ChatGPT zero-shot and
human-generated NLEs alone. We evaluate five popular LLMs (GPT3.5-turbo,
LLaMa2, Vicuna, Zephyr, Mistral) and show that X-ICL with ChatGPT few-shot
yields over 6% improvement over ICL. Furthermore, while prompt selection
strategies were previously shown to significantly improve ICL on
in-distribution test sets, we show that these strategies do not match the
efficacy of the X-ICL paradigm in robustness-oriented evaluations.Comment: pre-prin
A Tightly Coupled Bi-Level Coordination Framework for CAVs at Road Intersections
Since the traffic administration at road intersections determines the
capacity bottleneck of modern transportation systems, intelligent cooperative
coordination for connected autonomous vehicles (CAVs) has shown to be an
effective solution. In this paper, we try to formulate a Bi-Level CAV
intersection coordination framework, where coordinators from High and Low
levels are tightly coupled. In the High-Level coordinator where vehicles from
multiple roads are involved, we take various metrics including throughput,
safety, fairness and comfort into consideration. Motivated by the time
consuming space-time resource allocation framework in [1], we try to give a low
complexity solution by transforming the complicated original problem into a
sequential linear programming one. Based on the "feasible tunnels" (FT)
generated from the High-Level coordinator, we then propose a rapid
gradient-based trajectory optimization strategy in the Low-Level planner, to
effectively avoid collisions beyond High-level considerations, such as the
pedestrian or bicycles. Simulation results and laboratory experiments show that
our proposed method outperforms existing strategies. Moreover, the most
impressive advantage is that the proposed strategy can plan vehicle trajectory
in milliseconds, which is promising in realworld deployments. A detailed
description include the coordination framework and experiment demo could be
found at the supplement materials, or online at https://youtu.be/MuhjhKfNIOg
CATER: Intellectual Property Protection on Text Generation APIs via Conditional Watermarks
Previous works have validated that text generation APIs can be stolen through
imitation attacks, causing IP violations. In order to protect the IP of text
generation APIs, a recent work has introduced a watermarking algorithm and
utilized the null-hypothesis test as a post-hoc ownership verification on the
imitation models. However, we find that it is possible to detect those
watermarks via sufficient statistics of the frequencies of candidate
watermarking words. To address this drawback, in this paper, we propose a novel
Conditional wATERmarking framework (CATER) for protecting the IP of text
generation APIs. An optimization method is proposed to decide the watermarking
rules that can minimize the distortion of overall word distributions while
maximizing the change of conditional word selections. Theoretically, we prove
that it is infeasible for even the savviest attacker (they know how CATER
works) to reveal the used watermarks from a large pool of potential word pairs
based on statistical inspection. Empirically, we observe that high-order
conditions lead to an exponential growth of suspicious (unused) watermarks,
making our crafted watermarks more stealthy. In addition, \cater can
effectively identify the IP infringement under architectural mismatch and
cross-domain imitation attacks, with negligible impairments on the generation
quality of victim APIs. We envision our work as a milestone for stealthily
protecting the IP of text generation APIs.Comment: accepted to NeurIPS 202
Is the Envelope Beneficial to Non-Orthogonal Multiple Access?
Non-orthogonal multiple access (NOMA) is capable of serving different numbers of users in the same time-frequency resource element, and this feature can be leveraged to carry additional information. In the orthogonal frequency division multiplexing (OFDM) system, a novel enhanced NOMA scheme called NOMA with informative envelope (NOMA-IE) is proposed to explore extra flexibility from the envelope of NOMA signals. In this scheme, data bits are conveyed by the quantified signal envelope in addition to classic signal constellations. The sub- carrier activation patterns of different users are jointly decided by the envelope former at the transmitter of NOMA-IE. At the receiver, successive interference cancellation (SIC) is employed, and the envelope detection coefficient is introduced to eliminate the error floor. Theoretical expressions of spectral efficiency, energy efficiency, and detection complexity are provided first. Then, considering the binary phase shift keying modulation, the block error rate and bit error rate are derived based on the two-subcarrier element. The analytical results reveal that the SIC error and the index error are the main factors degrading the error performance. The numerical results demonstrate the superiority of the NOMA-IE over the OFDM and OFDM-NOMA in terms of the error rate performance when all the schemes have the same spectral efficiency and energy efficiency
Physical Layer Security for STAR-RIS-NOMA: A Stochastic Geometry Approach
In this paper, a stochastic geometry based analytical framework is proposed for secure simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted non-orthogonal multiple access (NOMA) transmissions, where legitimate users (LUs) and eavesdroppers are randomly distributed. Both the time-switching protocol (TS) and energy splitting (ES) protocol are considered for the STAR-RIS. To characterize system performance, the channel statistics are first provided, and the Gamma approximation is adopted for general cascaded κ-μ fading. Afterward, the closed-form expressions for both the secrecy outage probability (SOP) and average secrecy capacity (ASC) are derived. To obtain further insights, the asymptotic performance for the secrecy diversity order and the secrecy slope are deduced. The theoretical results show that 1) the secrecy diversity orders of the strong LU and the weak LU depend on the path loss exponent and the distribution of the received signal-to-noise ratio, respectively; 2) the secrecy slope of the ES protocol achieves the value of one, higher than the slope of the TS protocol which is the mode operation parameter of TS. The numerical results demonstrate that: 1) there is an optimal STAR-RIS mode operation parameter to maximize the secrecy performance; 2) the STAR-RIS-NOMA significantly outperforms the STAR-RIS-orthogonal multiple access