Queue-Aware Distributive Resource Control for Delay-Sensitive Two-Hop MIMO Cooperative Systems

Wang, Rui; Lau, V.K.N.; Cui, Ying

doi:10.1109/tsp.2010.2086449

Cited by 18 publications

(7 citation statements)

References 29 publications

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“…However, it is difficult to apply MDP-based policies to large systems due to "curse of dimensionality." Wang et al [11] considered queue-based cooperative relaying by approximately solving MDP using a stochastic learning approach. The authors proposed a distributed online algorithm which is shown to be asymptotically optimal under the heavy-traffic limit.…”

Section: Related Workmentioning

confidence: 99%

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Delay‐Optimal Scheduling for Two‐Hop Relay Networks with Randomly Varying Connectivity: Join the Shortest Queue‐Longest Connected Queue Policy

Baek¹,

Park

2017

Mathematical Problems in Engineering

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We consider a scheduling problem for a two-hop queueing network where the queues have randomly varying connectivity. Customers arrive at the source queue and are later routed to multiple relay queues. A relay queue can be served only if it is in connected state, and the state changes randomly over time. The source queue and relay queues are served in a time-sharing manner; that is, only one customer can be served at any instant. We propose Join the Shortest Queue-Longest Connected Queue (JSQ-LCQ) policy as follows: (1) if there exist nonempty relay queues in connected state, serve the longest queue among them; (2) if there are no relay queues to serve, route a customer from the source queue to the shortest relay queue. For symmetric systems in which the connectivity has symmetric statistics across the relay queues, we show that JSQ-LCQ is strongly optimal, that is, minimizes the delay in the stochastic ordering sense. We use stochastic coupling and show that the systems under coupling exist in two distinct phases, due to dynamic interactions among source and relay queues. By careful construction of coupling in both phases, we establish the stochastic dominance in delay between JSQ-LCQ and any arbitrary policy.

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Section: Related Workmentioning

confidence: 99%

“…A related technique of utilizing multiple relays over timevarying channels, called cooperative relaying or opportunistic relaying, has been studied extensively [8][9][10][11][12][13]. Meanwhile, our model is applicable to the uplink transmission for cellular networks as well.…”

Section: Introductionmentioning

confidence: 99%

Delay‐Optimal Scheduling for Two‐Hop Relay Networks with Randomly Varying Connectivity: Join the Shortest Queue‐Longest Connected Queue Policy

Baek¹,

Park

2017

Mathematical Problems in Engineering

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“…OLSP refers to the Optimal Link Selection Policy for a two-hop system with an infinite relay buffer in [9,Theorem 2]. NOP refers to the NearOptimal Policy obtained based on approximate value iteration using aggregation [20,Chapter 6.3], which is similar to the approximate MDP technique used in [21] and [22]. Note that, OLSP depends on the CSI only, while the other four baseline schemes depend on both of the CSI and QSI.…”

Section: B Throughput Performancementioning

confidence: 99%

“…Generally, there exist only numerical solutions, which do not typically offer many design insights and are usually impractical for implementation due to the curse of dimensionality [20]. For example, in [21], [22], the authors consider delay-aware control problems for two-hop relaying systems with multiple relay nodes and propose suboptimal distributed numerical algorithms using approximate Markov Decision Process (MDP) and stochastic learning [20]. However, the obtained numerical algorithms may still be too complex for practical systems and do not offer many design insights.…”

Section: Introductionmentioning

confidence: 99%

Stochastic Throughput Optimization for Two-Hop Systems With Finite Relay Buffers

Zhou

Cui

Tao

2015

IEEE Trans. Signal Process.

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Abstract-Optimal queueing control of multi-hop networks remains a challenging problem even in the simplest scenarios. In this paper, we consider a two-hop half-duplex relaying system with random channel connectivity. The relay is equipped with a finite buffer. We focus on stochastic link selection and transmission rate control to maximize the average system throughput subject to a half-duplex constraint. We formulate this stochastic optimization problem as an infinite horizon average cost Markov decision process (MDP), which is well-known to be a difficult problem. By using sample-path analysis and exploiting the specific problem structure, we first obtain an equivalent Bellman equation with reduced state and action spaces. By using relative value iteration algorithm, we analyze the properties of the value function of the MDP. Then, we show that the optimal policy has a threshold-based structure by characterizing the supermodularity in the optimal control. Based on the threshold-based structure and Markov chain theory, we further simplify the original complex stochastic optimization problem to a static optimization problem over a small discrete feasible set and propose a lowcomplexity algorithm to solve the simplified static optimization problem by making use of its special structure. Furthermore, we obtain the closed-form optimal threshold for the symmetric case. The analytical results obtained in this paper also provide design insights for two-hop relaying systems with multiple relays equipped with finite relay buffers.Index Terms-Wireless relay system, finite buffer, throughput optimization, Markov decision process, Markov chain theory, matrix update, structural results.

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“…Often, even the basic structural properties of the delay optimal control policy are not known. While dynamic programming represents a systematic approach for delay optimal control, there generally exist only numerical solutions [1]- [5]. These solutions do not typically offer many design insights and are usually impractical for implementation in large-scale multi-hop networks, due to the curse of dimensionality [6].…”

Section: Introductionmentioning

confidence: 99%

Enhancing the Delay Performance of Dynamic Backpressure Algorithms

Cui

Yeh

Liu

2016

IEEE/ACM Trans. Networking

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Abstract-For general multi-hop queueing networks, delay optimal network control has unfortunately been an outstanding problem. The dynamic backpressure (BP) algorithm elegantly achieves throughput optimality, but does not yield good delay performance in general. In this paper, we obtain an asymptotically delay optimal control policy, which resembles the BP algorithm in basing resource allocation and routing on a backpressure calculation, but differs from the BP algorithm in the form of the backpressure calculation employed. The difference suggests a possible reason for the unsatisfactory delay performance of the BP algorithm, i.e., the myopic nature of the BP control. Motivated by this new connection, we introduce a new class of enhanced backpressure-based algorithms which incorporate a general queue-dependent bias function into the backpressure term of the traditional BP algorithm to improve delay performance. These enhanced algorithms exploit queue state information beyond one hop. We prove the throughput optimality and characterize the utility-delay tradeoff of the enhanced algorithms. We further focus on two specific distributed algorithms within this class, which have demonstrably improved delay performance as well as acceptable implementation complexity.Index Terms-dynamic backpressure algorithms, congestion control, delay optimal control, throughput optimal control, dynamic programming, Lyapunov drift.

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Queue-Aware Distributive Resource Control for Delay-Sensitive Two-Hop MIMO Cooperative Systems

Cited by 18 publications

References 29 publications

Delay‐Optimal Scheduling for Two‐Hop Relay Networks with Randomly Varying Connectivity: Join the Shortest Queue‐Longest Connected Queue Policy

Delay‐Optimal Scheduling for Two‐Hop Relay Networks with Randomly Varying Connectivity: Join the Shortest Queue‐Longest Connected Queue Policy

Stochastic Throughput Optimization for Two-Hop Systems With Finite Relay Buffers

Enhancing the Delay Performance of Dynamic Backpressure Algorithms

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