General expression of outage probability in cooperative networks

Renk, Tobias; Jaekel, Holger; Kloeck, C.; Jondral, Friedrich K.

doi:10.1002/ett.1331

Cited by 10 publications

(13 citation statements)

References 18 publications

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“…Observe that h .Z U / is independent of X T ; hence, maximising (21) becomes an entropy maximisation problem. U , fDestination; S c g, such that Y 1 D Y 2 D ¿, where ¿ denotes the empty set.…”

Section: An Outer Boundmentioning

confidence: 99%

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The value of cooperation between relays in the multiple‐access channel with multiple relays

Ghelber

Dabora

2012

Trans. Emerging Tel. Tech.

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We study the discrete memoryless multiple‐access channel with two independent sources, two relays and a single destination. We refer to this configuration as the multiple‐access channel with multiple relays (MACMRs), which is a generalisation of the multiple‐access relay channel model obtained by adding a relay node. We present inner and outer bounds on the capacity region of the MACMR. The inner bound is based on a hierarchical decode‐and‐forward scheme, in which each relay decodes the messages of the lower hierarchy. We extend the regular encoding, sliding‐window decoding and backward decoding techniques, previously applied to multiple‐access relay channels and multiple‐relay channels, to MACMRs. The outer bounds are obtained using the cut‐set bound. For Gaussian MACMRs, the bounds are evaluated and compared with those obtained for the multiple‐access channel with parallel relays. We conclude that a significantimprovement in performance can be obtained by letting the relays interact with each other. Copyright © 2012 John Wiley & Sons, Ltd.

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Section: An Outer Boundmentioning

confidence: 99%

“…However, the delay of sliding-window decoding is lower than that of backward decoding. Additional related work can be found in [20][21][22].…”

Section: The Multiple-relay Channelmentioning

confidence: 99%

The value of cooperation between relays in the multiple‐access channel with multiple relays

Ghelber

Dabora

2012

Trans. Emerging Tel. Tech.

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“…(5) From a finite set fk 2 f1; : : : ; Kgg, the relay selects the minimum k so that the relay can decode S 0 reliably. With k and m D 1, go to (6). (6) With m and k, when m D 1, the CSF index pair…”

Section: Multilevel Iteration Constructing Rule Of Relay-to-source Chmentioning

confidence: 99%

“…Cooperative relaying has been shown to be an effective technique to enhance the performance of wireless networks by allowing user terminals to share their antennas and transmit cooperatively [1][2][3][4][5][6][7]. Recently, with the higher demand on reliability and spectrum efficiency for wireless communications, research on cooperative relaying is attracting a great deal of attention.…”

Section: Introductionmentioning

confidence: 99%

Interaction of multiplexing gains and power exponents allocation of two‐level superposition coding relaying

Jia

Yang

2011

Trans Emerging Tel Tech

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A two-level rate superposition coding relaying (SC-relaying) scheme is discussed, in which only the relay-to-source channel state information feedback (CSF) is considered and, at source, a long power constraint is imposed on the basic signal S 0 and the additional signal S 1 whose multiplexing gains are r 0 and r 1 , respectively. The CSF index is constructed based on the correct decoding of the signal S 0 at relay. For the SC-relaying scheme, we propose a multilevel iteration constructing rule for the CSF index. With the proposed CSF constructing rule, the allocation method of the power signal-to-noise ratio exponents is first obtained by the investigation of the optimal outage exponent of the signal S 0 . Secondly, we obtain the value range of p 11 , p 11 2 OE1; 1=r 0 , by studying the outage exponent lower bound of the signal S 0 , where p 11 denotes the minimum of the power signal-to-noise ratio exponent of the signal S . Lastly, to observe the interaction between the multiplexing gains r 0 and r 1 , we discuss the closed-form solution of the lower bound of the optimal outage exponent for the signal S 1 , through which we find that the multiplexing gain constraint is r 1 Ä 1 r 0 p 11 , p 11 1. The substantial numerical analyses show that the results in this paper are reasonable.

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“…For that purpose, several mobile users pool their resources in order to create a virtual antenna array. Suitable cooperation strategies lead to great improvements with respect to maximal data rate, error probability, transmission range, and outage probability [1].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Resource Allocation in Wireless Relay Networks

Renk

Iankov

Jondral

2009

VTC Spring 2009 - IEEE 69th Vehicular Technology Conference

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We consider a wireless relay network in a Rayleigh fading scenario where transmission power as well as transmission time per user are optimized. The criterion of optimization is the capacity. We apply an optimization algorithm based on Brent's method. Hence, we employ parabolic interpolation for finding the optimum whenever possible in order to achieve a faster convergence. If parabolic interpolation is not suitable, we use golden section search which is a robust root-finding method. Optimization takes place in two steps. First, we optimize power allocation and consider time as parameter. Second, time is optimized. We demonstrate that, depending on the cooperation strategy, remarkable capacity gains over direct transmission can be achieved by multi-routing. However, for a high overall transmission power, direct transmission outperforms multi-hopping. Generally, capacity gains increase with decreasing overall system power, which demonstrates that relaying is beneficial for low overall transmission powers.

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General expression of outage probability in cooperative networks

Cited by 10 publications

References 18 publications

The value of cooperation between relays in the multiple‐access channel with multiple relays

The value of cooperation between relays in the multiple‐access channel with multiple relays

Interaction of multiplexing gains and power exponents allocation of two‐level superposition coding relaying

Adaptive Resource Allocation in Wireless Relay Networks

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