# Energy-Efficient Decentralized Cooperative Routing in Wireless Networks

Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding

### Standard

**Energy-Efficient Decentralized Cooperative Routing in Wireless Networks.** / Madan, Ritesh; Mehta, Neelesh B.; Molisch, Andreas; Zhang, Jin.

Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding

### Harvard

*Ieee Transactions On Automatic Control.*vol. 54, IEEE - Institute of Electrical and Electronics Engineers Inc., pp. 512-527, 45th Annual Allerton Conference on Communication, Control and Computing, 0001/01/02. https://doi.org/10.1109/TAC.2009.2012979

### APA

*Ieee Transactions On Automatic Control*(Vol. 54, pp. 512-527). IEEE - Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TAC.2009.2012979

### CBE

### MLA

*Ieee Transactions On Automatic Control.*IEEE - Institute of Electrical and Electronics Engineers Inc. 2009, 512-527. https://doi.org/10.1109/TAC.2009.2012979

### Vancouver

### Author

### RIS

TY - GEN

T1 - Energy-Efficient Decentralized Cooperative Routing in Wireless Networks

AU - Madan, Ritesh

AU - Mehta, Neelesh B.

AU - Molisch, Andreas

AU - Zhang, Jin

PY - 2009

Y1 - 2009

N2 - Wireless adhoc networks transmit information from a source to a destination via multiple hops in order to save energy and, thus, increase the lifetime of battery-operated nodes. The energy savings can be especially significant in cooperative transmission schemes, where several nodes cooperate during one hop to forward the information to the next node along a route to the destination. Finding the best multi-hop transmission policy in such a network which determines nodes that are involved in each hop, is a very important problem, but also a very difficult one especially when the physical wireless channel behavior is to be accounted for and exploited. We model the above optimization problem for randomly fading channels as a decentralized control problem - the channel observations available at each node define the information structure, while the control policy is defined by the power and phase of the signal transmitted by each node. In particular, we consider the problem of computing an energy-optimal cooperative transmission scheme in a wireless network for two different channel fading models: (i) slow fading channels, where the channel gains of the links remain the same for a large number of transmissions, and (ii) fast fading channels, where the channel gains of the links change quickly from one transmission to another. For slow fading, we consider a factored class of policies (corresponding to local cooperation between nodes), and show that the computation of an optimal policy in this class is equivalent to a shortest path computation on an induced graph, whose edge costs can be computed in a decentralized manner using only locally available channel state information (CSI). For fast fading, both CSI acquisition and data transmission consume energy. Hence, we need to jointly optimize over both these; we cast this optimization problem as a large stochastic optimization problem. We then jointly optimize over a set of CSI functions of the local channel states, and a corresponding factored class of control policies corresponding to local cooperation between nodes with a local outage constraint. The resulting optimal scheme in this class can again be computed efficiently in a decentralized manner. We demonstrate significant energy savings for both slow and fast fading channels through numerical simulations of randomly distributed networks.

AB - Wireless adhoc networks transmit information from a source to a destination via multiple hops in order to save energy and, thus, increase the lifetime of battery-operated nodes. The energy savings can be especially significant in cooperative transmission schemes, where several nodes cooperate during one hop to forward the information to the next node along a route to the destination. Finding the best multi-hop transmission policy in such a network which determines nodes that are involved in each hop, is a very important problem, but also a very difficult one especially when the physical wireless channel behavior is to be accounted for and exploited. We model the above optimization problem for randomly fading channels as a decentralized control problem - the channel observations available at each node define the information structure, while the control policy is defined by the power and phase of the signal transmitted by each node. In particular, we consider the problem of computing an energy-optimal cooperative transmission scheme in a wireless network for two different channel fading models: (i) slow fading channels, where the channel gains of the links remain the same for a large number of transmissions, and (ii) fast fading channels, where the channel gains of the links change quickly from one transmission to another. For slow fading, we consider a factored class of policies (corresponding to local cooperation between nodes), and show that the computation of an optimal policy in this class is equivalent to a shortest path computation on an induced graph, whose edge costs can be computed in a decentralized manner using only locally available channel state information (CSI). For fast fading, both CSI acquisition and data transmission consume energy. Hence, we need to jointly optimize over both these; we cast this optimization problem as a large stochastic optimization problem. We then jointly optimize over a set of CSI functions of the local channel states, and a corresponding factored class of control policies corresponding to local cooperation between nodes with a local outage constraint. The resulting optimal scheme in this class can again be computed efficiently in a decentralized manner. We demonstrate significant energy savings for both slow and fast fading channels through numerical simulations of randomly distributed networks.

KW - multiple output (MIMO) systems

KW - multiple input

KW - Ad hoc networks

KW - channel state information (CSI)

U2 - 10.1109/TAC.2009.2012979

DO - 10.1109/TAC.2009.2012979

M3 - Paper in conference proceeding

VL - 54

SP - 512

EP - 527

BT - Ieee Transactions On Automatic Control

PB - IEEE - Institute of Electrical and Electronics Engineers Inc.

ER -