Non-orthogonal multiple access (NOMA) has been considered one of the most promising radio access techniques for next-generation cellular networks. In this paper, we study the joint user and power scheduling for downlink NOMA over fading channels. Specifically, we focus on a stochastic optimization problem to maximize the weighted average sum rate while ensuring given minimum average data rates of users. To address this problem, we first develop an opportunistic user and power scheduling algorithm (OUPS) based on the duality and stochastic optimization theory. By OUPS, the stochastic problem is transformed into a series of deterministic ones for the instantaneous weighted sum rate maximization for each slot. Thus, we additionally develop a heuristic algorithm with very low computational complexity, called user selection and power allocation algorithm (USPA), for the instantaneous weighted sum rate maximization problem. Via simulation results, we demonstrate that USPA provides near-optimal performance with very low computational complexity, and OUPS well guarantees given minimum average data rates.

In this paper, we investigate dynamic resource scheduling (i.e., joint user, subchannel, and power scheduling) for downlink multi-channel non-orthogonal multiple access (MC-NOMA) systems over time-varying fading channels. Specifically, we address the weighted average sum rate maximization problem with quality-of-service (QoS) constraints. In particular, to facilitate fast resource scheduling, we focus on developing a very low-complexity algorithm. To this end, by leveraging Lagrangian duality and the stochastic optimization theory, we first develop an opportunistic MC-NOMA scheduling algorithm whereby the original problem is decomposed into a series of subproblems, one for each time slot. Accordingly, resource scheduling works in an online manner by solving one subproblem per time slot, making it more applicable to practical systems. Then, we further develop a heuristic joint subchannel assignment and power allocation (Joint-SAPA) algorithm with very low computational complexity, called Joint-SAPA-LCC, that solves each subproblem. Finally, through simulation, we show that our Joint-SAPA-LCC algorithm provides good performance comparable to the existing Joint-SAPA algorithms despite requiring much lower computational complexity. We also demonstrate that our opportunistic MC-NOMA scheduling algorithm in which the Joint-SAPA-LCC algorithm is embedded works well while satisfying given QoS requirements.

In this paper, we investigate dynamic resource scheduling (i.e., joint user, subchannel, and power scheduling) for downlink multi-channel non-orthogonal multiple access (MC-NOMA) systems over time-varying fading channels. Specifically, we address the weighted average sum rate maximization problem with quality-of-service (QoS) constraints. In particular, to facilitate fast resource scheduling, we focus on developing a very low-complexity algorithm. To this end, by leveraging Lagrangian duality and the stochastic optimization theory, we first develop an opportunistic MC-NOMA scheduling algorithm whereby the original problem is decomposed into a series of subproblems, one for each time slot. Accordingly, resource scheduling works in an online manner by solving one subproblem per time slot, making it more applicable to practical systems. Then, we further develop a heuristic joint subchannel assignment and power allocation (Joint-SAPA) algorithm with very low computational complexity, called Joint-SAPA-LCC, that solves each subproblem. Finally, through simulation, we show that our Joint-SAPA-LCC algorithm provides good performance comparable to the existing Joint-SAPA algorithms despite requiring much lower computational complexity. We also demonstrate that our opportunistic MC-NOMA scheduling algorithm in which the Joint-SAPA-LCC algorithm is embedded works well while satisfying given QoS requirements.

Background

Myopathic changes are commonly described in hypothyroid and hyperthyroid patients, including muscular atrophy and weakness. Satellite cells (SCs) play a major role in skeletal muscle maintenance and regeneration after injury. A mouse model of resistance to thyroid hormone-TRα1PV demonstrated impaired skeletal muscle regeneration after injury with significant reduction of SCs, suggesting that exhaustion of the SC pool contributes to the impaired regeneration. To test this hypothesis, SC activation and proliferation were analyzed in vivo in response to skeletal muscle injury and during aging.

Methods

SCs of TRα1PV male mice were analyzed four days after cardiotoxin-induced muscle injury, and they were compared to wild-type (WT) male animals. TRα-knockdown C2C12 myoblasts were injected into injured skeletal muscle, and four days after transplantation, the in vivo behavior was compared to control C2C12 myoblasts. Skeletal muscle regeneration was compared in younger and older TRα1PV and WT animals.

Results

The total number of SCs in skeletal muscle of TRα1PV mice was significantly lower than control, both before and shortly after muscle injury, with significant impairment of SC activation, consistent with SC pool exhaustion. TRα-knockdown myoblasts showed impaired in vivo proliferation and migration. TRα1PV mice had skeletal muscle loss and significant impairment in skeletal muscle regeneration with aging. This translated to a significant reduction of the SC pool with aging compared to WT mice.

Conclusion

TRα plays an important role in the maintenance of the SC pool. Impaired skeletal muscle regeneration in TRα1PV mice is associated with insufficient SC activation and proliferation, as well as the progressive loss of the SC pool with aging. Regulation of the SC pool and SC proliferation provides a therapeutic target to enhance skeletal muscle regeneration and possibly slow age-associated sarcopenia.