Age-optimal Power Allocation Policies for NOMA and Hybrid NOMA/OMA Systems

Guo, Chaofan; Wu, Shaohua; Deng, Zhihong; Jiao, Jian; Zhang, Ning; Zhang, Qinyu

doi:10.1109/icc42927.2021.9500896

Cited by 7 publications

(4 citation statements)

References 12 publications

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“…In (34), we have 𝜃 N ∈ [P min (i,j) , P max (i,j) ], as presented in Theorem 3. Therefore, the resultant {P ′ i,(i,j) , P ′ j,(i,j) } in (34) cannot be directly used as the final power allocation decision.…”

Section: Discussionmentioning

confidence: 99%

“…The studies on latency-constrained communications with hybrid NOMA in FBL regime mainly consider delay metrics such as average latency, 22 AoI, 19,20,[34][35][36] packet block-length, 37,38 and packet deadline. 28,31 Thus, there is a lack of study on maximizing the timely throughput for given strict deadlines using hybrid NOMA in the FBL regime.…”

Section: Related Workmentioning

confidence: 99%

“…In Reference 20, Hybrid MA is considered for AoI. In Reference 34, hybrid MA with NOMA and OMA under FBL is considered for optimizing AoI in cellular networks. The hybrid NOMA/OMA policy is based on Lyapunov stochastic optimization.…”

Section: Introductionmentioning

confidence: 99%

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Satisfying strict deadlines for cellular Internet of Things through hybrid multiple access

Gamgam

Karasan

2023

Trans Emerging Tel Tech

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Latency‐constrained aspects of cellular Internet of Things (IoT) applications rely on Ultra‐Reliable and Low Latency Communications (URLLC), which highlight research on satisfying strict deadlines. In this study, we address the problem of latency‐constrained communications with strict deadlines under average power constraint using Hybrid Multiple Access (MA), which consists of both Orthogonal MA (OMA) and power domain Non‐Orthogonal MA (NOMA) as transmission scheme options. We aim to maximize the timely throughput, which represents the average number of successfully transmitted packets before deadline expiration, where expired packets are dropped from the buffer. We use Lyapunov stochastic optimization methods to develop a dynamic power assignment algorithm for minimizing the packet drop rate while satisfying time average power constraints. Moreover, we propose a flexible packet dropping mechanism called Early Packet Dropping (EPD) to detect likely to become expired packets and drop them immediately. Numerical results show that Hybrid MA improves the timely throughput compared to conventional OMA by up to 46%$$ 46\% $$ and on average by more than 21%$$ 21\% $$. With EPD, these timely throughput gains improve to 53%$$ 53\% $$ and 24.5%$$ 24.5\% $$, respectively.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Satisfying strict deadlines for cellular Internet of Things through hybrid multiple access

Gamgam

Karasan

2023

Trans Emerging Tel Tech

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“…Moreover, due to the expected large number of deployments of communication devices, most emerging networks may be powered from energy harvesting sources. Accordingly, AoI and semantic-aware communications in energy harvesting systems has also been considered [16]- [21], including communications over pointto-point [22], multiple access [23], [24] and broadcast [18] channels.…”

Section: Introductionmentioning

confidence: 99%

Importance-Aware Fresh Delivery of Versions over Energy Harvesting MACs

Karevvanavar¹,

Bhat²

2023

Preprint

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We consider a scenario where multiple users, powered by energy harvesting, send version updates over a fading multiple access channel (MAC) to an access point (AP). Version updates having random importance weights arrive at a user according to an exogenous arrival process, and a new version renders all previous versions obsolete. As energy harvesting imposes a time-varying peak power constraint, it is not possible to deliver all the bits of a version instantaneously. Accordingly, the AP chooses the objective of minimizing a finite-horizon time average expectation of the product of importance weight and a convex increasing function of the number of remaining bits of a version to be transmitted at each time instant. The objective enables importance-aware delivery of as many bits, as soon as possible. In this setup, the AP optimizes the objective function subject to an achievable rate-region constraint of the MAC and energy constraints at the users, by deciding the transmit power and the number of bits to be transmitted by each user. We obtain a Markov Decision Process (MDP)-based optimal online policy to the problem and derive structural properties of the policy. We then develop a neural network (NN)-based online heuristic policy, for which we train an NN on the optimal offline policy derived for different sample paths of energy, version arrival and channel power gain processes. Via numerical simulations, we observe that the NN-based online policy performs competitively with respect to the MDP-based online policy.

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