Optimal energy allocation for delay-constrained data transmission over a time-varying channel

Fu, A.; Modiano, Eytan; Tsitsiklis, John N.

doi:10.1109/infcom.2003.1208946

Cited by 118 publications

(102 citation statements)

References 11 publications

(11 reference statements)

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“…Previous work on power control for wireless systems is found in [1][2][3][4][5][6][7], [23], [25][26][27]. In [1], a stabilizing power allocation strategy is developed for a satellite downlink with random inputs and time varying channels.…”

Section: µ(P S)mentioning

confidence: 99%

“…Routing over finite buffer downlinks is considered in [2]. In [3,4], optimal power allocation policies are developed for minimizing the energy expended to transmit data arriving to a downlink node with a single transmitter. Scheduling and allocation strategies for networks are considered in [5][6][7], where static power allocation policies are developed to support flows with known traffic rates λ ij .…”

Section: µ(P S)mentioning

confidence: 99%

“…4 Thus, a rate matrix R = (R ab ) is in graph family Γ if and only if R can be represented as R = S π S R S , where each matrix R S is inside the convex hull of the set of rates achievable by power allocation under channel state S. In the proof of Theorem 1, we show that graph family Γ can be viewed as the set of all long-term transmission rates (R ab ) that the network can support on the single-hop wireless links connecting node pairs (a, b). A particular power allocation policy gives rise to a particular rate matrix R = (R ab ).…”

Section: B the Capacity Region λmentioning

confidence: 99%

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Dynamic power allocation and routing for time varying wireless networks

Neely¹,

Modiano²,

Rohrs³

IEEE INFOCOM 2003. Twenty-Second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37

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Abstract-We consider dynamic routing and power allocation for a wireless network with time varying channels. The network consists of power constrained nodes which transmit over wireless links with adaptive transmission rates. Packets randomly enter the system at each node and wait in output queues to be transmitted through the network to their destinations. We establish the capacity region of all rate matrices (λ ij ) that the system can stably support-where (λij) represents the rate of traffic originating at node i and destined for node j. A joint routing and power allocation policy is developed which stabilizes the system and provides bounded average delay guarantees whenever the input rates are within this capacity region. Such performance holds for general arrival and channel state processes, even if these processes are unknown to the network controller. We then apply this control algorithm to an ad-hoc wireless network where channel variations are due to user mobility, and compare its performance with the Grossglauser-Tse relay model developed in [13]. I. INTRODUCTIONWireless systems have emerged as a ubiquitous part of modern data communication networks. Demand for these systems continues to grow as applications involving both voice and data expand beyond their traditional wireline service requirements. In order to meet the increasing demand in data rates that are currently being supported by high speed wired networks composed of electrical cables and optical links, it is important to fully utilize the capacity available in wireless systems, as well as to develop robust strategies for integrating these systems into a large scale, heterogeneous data network. Emerging microprocessor technologies are enabling wireless units to be equipped with the processing power needed to implement adaptive coding techniques and to make intelligent decisions about packet routing and resource management. It is expedient to take full advantage of these capabilities by designing efficient network control algorithms.In this paper, we develop algorithms for dynamic routing and power allocation in a wireless network consisting of N power constrained nodes. Time is slotted, and every timeslot the channel conditions of each link randomly change (due to external effects such as fading, user mobility, and/or time varying weather conditions). Multiple data streams X ij (t) randomly enter the system, where X ij (t) represents an exogenous process of packets arriving to node i destined for node j. Packets are dynamically routed from node to node over multi-hop paths using wireless data links.Nodes can transmit data over multiple links simultaneously by assigning power to the link for each node pair (a, b) according to a power matrix P (t) = (P ab (t)), subject to a total power constraint at each node. Transmission rates over all link pairs are determined by the power allocation matrix P (t) and the current channel state S(t) according to a rate-power curve

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Section: µ(P S)mentioning

confidence: 99%

Section: µ(P S)mentioning

confidence: 99%

Section: B the Capacity Region λmentioning

confidence: 99%

See 1 more Smart Citation

Dynamic power allocation and routing for time varying wireless networks

Neely¹,

Modiano²,

Rohrs³

IEEE INFOCOM 2003. Twenty-Second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37

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483

1,000

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“…The objective is usually to minimize energy consumption given a fixed amount of data [5,6,8,9] or to maximize throughput under a given energy constraint [9]. It is known that with proper channel coding the energy required for transmitting any given amount of data is strictly convex and monotonically decreases with transmission time [5].…”

mentioning

confidence: 99%

“…Energy-efficient packet scheduling under a fading channel is more complicated. As the channel states change with time, the current and future channel states must be considered when allocating transmission power [9,10].…”

mentioning

confidence: 99%

Throughput and value maximization in wireless packet scheduling under energy and time constraints

Zhang

Chanson

Proceedings. 2003 International Symposium on System-on-Chip (IEEE Cat. No.03EX748)

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Energy-efficient data transmission is an important issue for mobile communication devices. In this paper, we study throughput and value-based packet scheduling over a wireless link under time and energy constraints. A mobile node is required to deliver multiple data streams to multiple receivers. These data streams may have different importance and incur different energy costs. In this research, point-to-point wireless data transmission is studied. The objective is to develop schemes that selectively transmit data streams at certain power levels so that the data throughput or the value of data delivery is maximized without violating the energy and time constraints. Exploiting the special properties of the throughput maximization problem, we propose an iterative algorithm that yields the optimal transmission schedule. The value maximization problem is formulated as a convex optimization problem and the optimal results can be obtained by solving the Kuhn-Tucker conditions. When time and transmission power are allocated at discrete slots and levels, respectively, a dynamic programming approach is proposed to find the optimal value.

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RED theory for quality of service provisioning in wireless communications

Dong

2012

Wirel. Commun. Mob. Comput.

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In this paper, we study the performance limit of a wireless communication system over a fading channel. The system under study consists of 1) a finite‐buffer discrete‐time queueing system on the link layer; and 2) a rate‐adaptive channel coding system on the physical layer. The objective of this paper is to analyze the relationship among data rate (R), packet error probability (E), and delay bound (D) under the interaction between the link layer and the physical layer. In our analysis, we consider three types of packet errors; that is, 1) packet drop due to full buffer; 2) packet drop due to delay bound violation; and 3) packet decoding error due to channel noise. We obtain an upper bound on the packet error probability. Furthermore, by minimizing the packet error probability over the transmission rate, we obtain an optimal rate control policy that guarantees the user‐specified data rate and delay bound. In the case of constant arrival, the optimal rate control policy results in a rate‐error‐delay triplet; then, by varying data rate and delay bound, we obtain rate‐error‐delay Pareto‐optimal surface, which serves as the performance limit of the system under study. Copyright © 2012 John Wiley & Sons, Ltd.

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Optimal energy allocation for delay-constrained data transmission over a time-varying channel

Cited by 118 publications

References 11 publications

Dynamic power allocation and routing for time varying wireless networks

Dynamic power allocation and routing for time varying wireless networks

Throughput and value maximization in wireless packet scheduling under energy and time constraints

RED theory for quality of service provisioning in wireless communications

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