In this paper, we present the delay-constrained performance analysis of a multi-antenna-assisted multiuser non-orthogonal multiple access (NOMA) based spectrum sharing system over Rayleigh fading channels. We derive analytical expressions for the sum
effective rate (ER) for the downlink NOMA system under a peak interference constraint. In particular, we show the effect of the availability of different levels of channel state information (instantaneous and statistical) on the system performance. We also show the effect of different parameters of interest, including the peak tolerable interference power, the delay exponent, the number of antennas and the number of users, on the sum ER of the system under consideration. An excellent agreement between simulation and theoretical results confirms the accuracy of the analysis.
To mitigate computational power gap between the network core and edges, mobile edge computing (MEC) is poised to play a fundamental role in future generations of wireless networks. In this letter, we consider a non-orthogonal multiple access (NOMA) t
ransmission model to maximize the worst task to be offloaded among all users to the network edge server. A provably convergent and efficient algorithm is developed to solve the considered non-convex optimization problem for maximizing the minimum number of offloaded bits in a multi-user NOMAMEC system. Compared to the approach of optimized orthogonal multiple access (OMA), for given MEC delay, power and energy limits, the NOMA-based system considerably outperforms its OMA-based counterpart in MEC settings. Numerical results demonstrate that the proposed algorithm for NOMA-based MEC is particularly useful for delay sensitive applications.
Reconfigurable intelligent surface (RIS) assisted radio is considered as an enabling technology with great potential for the sixth-generation (6G) wireless communications standard. The achievable secrecy rate (ASR) is one of the most fundamental metr
ics to evaluate the capability of facilitating secure communication for RIS-assisted systems. However, the definition of ASR is based on Shannons information theory, which generally requires long codewords and thus fails to quantify the secrecy of emerging delay-critical services. Motivated by this, in this paper we investigate the problem of maximizing the secrecy rate under a delay-limited quality-of-service (QoS) constraint, termed as the effective secrecy rate (ESR), for an RIS-assisted multiple-input single-output (MISO) wiretap channel subject to a transmit power constraint. We propose an iterative method to find a stationary solution to the formulated non-convex optimization problem using a block coordinate ascent method (BCAM), where both the beamforming vector at the transmitter as well as the phase shifts at the RIS are obtained in closed forms in each iteration. We also present a convergence proof, an efficient implementation, and the associated complexity analysis for the proposed method. Our numerical results demonstrate that the proposed optimization algorithm converges significantly faster that an existing solution. The simulation results also confirm that the secrecy rate performance of the system with stringent delay requirements reduce significantly compared to the system without any delay constraints, and that this reduction can be significantly mitigated by an appropriately placed large-size RIS.
In this paper, we present the ergodic sum secrecy rate (ESSR) analysis of an underlay spectrum sharing non-orthogonal multiple access (NOMA) system. We consider the scenario where the power transmitted by the secondary transmitter (ST) is constrained
by the peak tolerable interference at multiple primary receivers (PRs) as well as the maximum transmit power of the ST. The effect of channel estimation error is also taken into account in our analysis. We derive exact and asymptotic closed-form expressions for the ESSR of the downlink NOMA system, and show that the performance can be classified into two distinct regimes, i.e., it is dictated either by the interference constraint or by the power constraint. Our results confirm the superiority of the NOMA-based system over its orthogonal multiple access (OMA) based counterpart. More interestingly, our results show that NOMA helps in maintaining the secrecy rate of the strong user while significantly enhancing the secrecy performance of the weak user as compared to OMA. The correctness of the proposed investigation is corroborated through Monte Carlo simulation.
Non-orthogonal multiple access (NOMA) is being widely considered as a potential candidate to enhance the spectrum utilization in beyond fifth-generation (B5G) communications. In this paper, we derive closed-form expressions for the ergodic rate and o
utage probability of a multiple-antenna-assisted NOMA-based cooperative relaying system (CRS-NOMA). We present the performance analysis of the system for two different receive diversity schemes - selection combining (SC) and maximal-ratio combining (MRC), in Nakagami-m fading. We also evaluate the asymptotic behavior of the CRS-NOMA to determine the slope of the ergodic rate and diversity order. Our results show that in contrast to the existing CRS-NOMA systems, the CRS-NOMA with receive diversity outperforms its orthogonal multiple access (OMA) based counterpart even in the low-SNR regime, by achieving higher ergodic rate. Diversity analysis confirms that the CRS-NOMA achieves full diversity order using both SC and MRC schemes, and this diversity order depends on both the shape parameter m and the number of receive antennas. We also discuss the problem of optimal power allocation for the minimization of the outage probability of the system, and subsequently use this optimal value to obtain the ergodic rate. An excellent match is observed between the numerical and the analytical results, confirming the correctness of the derived analytical expressions.
Non-orthogonal multiple access (NOMA) and spectrum sharing are two potential technologies for providing massive connectivity in beyond fifth-generation (B5G) networks. In this paper, we present the performance analysis of a multi-antenna-assisted two
-user downlink NOMA system in an underlay spectrum sharing system. We derive closed-form expressions for the average achievable sum-rate and outage probability of the secondary network under a peak interference constraint and/or peak power constraint, depending on the availability of channel state information (CSI) of the interference link between secondary transmitter (ST) and primary receiver (PR). For the case where the ST has a fixed power budget, we show that performance can be divided into two specific regimes, where either the interference constraint or the power constraint primarily dictates the performance. Our results confirm that the NOMA-based underlay spectrum sharing system significantly outperforms its orthogonal multiple access (OMA) based counterpart, by achieving higher average sum-rate and lower outage probability. We also show the effect of information loss at the ST in terms of CSI of the link between the ST and PR on the system performance. Moreover, we also present closed-form expressions for the optimal power allocation coefficient that minimizes the outage probability of the NOMA system for the special case where the secondary users are each equipped with a single antenna. A close agreement between the simulation and analytical results confirms the correctness of the presented analysis.
Given a natural language query, teaching machines to ask clarifying questions is of immense utility in practical natural language processing systems. Such interactions could help in filling information gaps for better machine comprehension of the que
ry. For the task of ranking clarification questions, we hypothesize that determining whether a clarification question pertains to a missing entry in a given post (on QA forums such as StackExchange) could be considered as a special case of Natural Language Inference (NLI), where both the post and the most relevant clarification question point to a shared latent piece of information or context. We validate this hypothesis by incorporating representations from a Siamese BERT model fine-tuned on NLI and Multi-NLI datasets into our models and demonstrate that our best performing model obtains a relative performance improvement of 40 percent and 60 percent respectively (on the key metric of Precision@1), over the state-of-the-art baseline(s) on the two evaluation sets of the StackExchange dataset, thereby, significantly surpassing the state-of-the-art.
Non-orthogonal multiple access (NOMA) is a potential candidate to further enhance the spectrum utilization efficiency in beyond fifth-generation (B5G) standards. However, there has been little attention on the quantification of the delay-limited perf
ormance of downlink NOMA systems. In this paper, we analyze the performance of a two-user downlink NOMA system over generalized {alpha}-{mu} fading in terms of delay violation probability (DVP) and effective rate (ER). In particular, we derive an analytical expression for an upper bound on the DVP and we derive the exact sum ER of the downlink NOMA system. We also derive analytical expressions for high and low signal-to-noise ratio (SNR) approximations to the sum ER, as well as a fundamental upper bound on the sum ER which represents the ergodic sum-rate for the downlink NOMA system. We also analyze the sum ER of a corresponding time-division-multiplexed orthogonal multiple access (OMA) system. Our results show that while NOMA consistently outperforms OMA over the practical SNR range, the relative gain becomes smaller in more severe fading conditions, and is also smaller in the presence a more strict delay quality-of-service (QoS) constraint.
In this article, we present a novel Carleman estimate for ultrahyperbolic operators, in $ R^m_t times R^n_x $. Then, we use a special case of this estimate to obtain improved observability results for wave equations with time-dependent lower order te
rms. The key improvements are: (1) we obtain smaller observation regions compared to standard Carleman estimate results, and (2) we also prove observability when the observation point lies inside the domain. Finally, as a corollary of the observability result, we obtain improved interior controllability for the wave equation.
Question answering and conversational systems are often baffled and need help clarifying certain ambiguities. However, limitations of existing datasets hinder the development of large-scale models capable of generating and utilising clarification que
stions. In order to overcome these limitations, we devise a novel bootstrapping framework (based on self-supervision) that assists in the creation of a diverse, large-scale dataset of clarification questions based on post-comment tuples extracted from stackexchange. The framework utilises a neural network based architecture for classifying clarification questions. It is a two-step method where the first aims to increase the precision of the classifier and second aims to increase its recall. We quantitatively demonstrate the utility of the newly created dataset by applying it to the downstream task of question-answering. The final dataset, ClarQ, consists of ~2M examples distributed across 173 domains of stackexchange. We release this dataset in order to foster research into the field of clarification question generation with the larger goal of enhancing dialog and question answering systems.
