Multimedia Transmission Over Cognitive Radio Networks using Decode-and-Forward

Multi-Relays and Rateless Coding

Abdelaali Chaoub, Elhassane Ibn-ElhajNational Institute of Posts and Telecommunications, Rabat, Morocco2014 International Conference on Communications and Networking

Outline

• Introduction• System Description• Numerical Results• Conclusion

Introduction

• The cognitive radio technology (CR) [1] has emerged as new solution which aims to increase the spectral efficiency by leveraging the spectrum holes.

[1] J. Mitola III and G.Q Maguire, “Cognitive radio: making software radios more personal,” Personal Communications, IEEE , vol.6, no.4, pp.13-18, Aug 1999.

Introduction

• The Cognitive Radio for Virtual Unlicensed Spectrum (CORVUS) model is a cognitive radio based approach to create and use virtual unlicensed spectrum [2].– Allowing the cognitive device to use different non-

contiguous sub-channels (SCs) scattered over multiple primary frequency bands.

[2] R. W. Broderson, A. Wolisz, D. Cabric, S. M. Mishra, and D. Willkomm, “Corvus: A cognitive radio approach for usage of virtual unlicensed spectrum,” White Paper, Univ. California Berkeley, Tech. Rep., Jul. 2004.

Introduction

• Authors in [3] have exploited the CORVUS architecture to distribute a fountain encoded multimedia stream over CR networks with a Poisson primary traffic pattern.– channel correcting codes– avoid the problem of coordination between sub-

channels

[3] H. Kushwaha, Y. Xing, R. Chandramouli, and H. Heffes, “Reliable multimedia transmission over cognitive radio networks using fountain codes,” Proc. IEEE, vol. 96, no. 1, pp. 155-165, Jan. 2008.

Introduction

• The basic idea of cooperative communications is to create transmit diversity via spatial diversity by transmitting and forwarding the same signals through the relay nodes.

• Castura and Mao introduced a relaying protocol in which a relay collaborates with the source by forming a distributed space-time coding scheme based on rateless codes [5].

[5] J. Castura and Yongyi Mao, “Rateless Coding for Wireless Relay Channels,” Information Theory, 2005. ISIT 2005. Proceedings. International Symposium on, vol., no., pp. 810-814, 4-9 Sept. 2005.

Introduction

• In [6], results have shown that the use of fountain codes helps reducing the transmission time.

• In this paper we will consider a generalized case of multiple sub-channels selected among different PU frequencies (CORVUS).

[6] Weijia Lei, Xianzhong Xie and Guangjun Li, “Performance Analysis of Wireless Dynamic Cooperative Relay Networks Using Fountain Codes,” Journal of Communications, vol. 5, no. 4, pp. 307-316, April 2010.

Outline

• Introduction• System Description– System model– From source to relays– From relays to destination

• Numerical Results• Conclusion

System Description

• In this paper, we focus on multimedia transmissions through multi-relay dual-hop networks with information accumulation at the receiver side.

• Secondary data packets are encoded using fountain codes and secondary links are established according to CORVUS design.

System Description

System DescriptionSystem model

• Considering a CR network hosting a common cognitive source S and a set of L cognitive relays forwarding a given stream to a common cognitive destination D in a wireless environment.

• Assuming that the destination cannot receive from the source directly.

• Transmission paths are formed using the CORVUS concept.– The probability of PU appearance on any sub-

channel is given by – The error probability of fading and noise is

denoted by

System DescriptionSystem model

• It is a matter of fact that secondary users could be evicted from their sub-channels at any time whenever the corresponding primary user returns.

• To compensate for the eventual discarded packets, rateless codes are considered for use.

System DescriptionSystem model

• The initial stream is fragmented into a given number of messages, each divided into the same number of packets K.

• The LT decoder needs at least N packets to recover the original K packets with a high probability.

System DescriptionSystem model

System DescriptionSystem model

• Define the throughput

– and are the transmission times of the first hop and the second hop.

System DescriptionSystem model

• Let be the time taken by the message to reach the relay nodes.

• Let be the probability that the sub-channel has to be excluded from the SUL.– = +

• Define as the message success probability which is the probability that the message m reaches successfully the relay target.

System DescriptionFrom source to relays

• • Define (n) as the PDF of

System DescriptionFrom source to relays

• Finally, the average transmission time of the first hop is computed as the expectation of

System DescriptionFrom source to relays

System DescriptionFrom relays to destination

• Assume that each relay among the arbitrary L intermediate nodes that have first finished receiving the message sent by the source has the capability to relay information the moment it achieves correct decoding of the N packets.

System DescriptionFrom relays to destination

• Each node is connected to the destination D through one sub-channel and will convey different encoded packets from the same fountain– Ensuring that no duplicate packets will be received

at the receiving node.• Let (n) be the PDF of .

System DescriptionFrom relays to destination

Outline

• Introduction• System Description• Numerical Results• Conclusion

Numerical Results

• For these experiments, here used 512 x 512 gray Lenna image compressed using a bit rate of 0.44bit/pixel .

• Need a total of N = 80 packets (LT codes overhead included) for a packet size of 1500bits.

• The primary user appearance probability = 0.08.• The fading loss probability = 0.02.• The number of relaying nodes is L = 5.

Numerical Results

X = 9

Numerical Results

X = 9

Numerical Results

Numerical Results

N = 40 and X = 3.

Numerical Results

N = 40 and X = 3.

Outline

• Introduction• System Description• Numerical Results• Conclusion

Conclusion

• The properties of fountain codes have been exploited to mitigate the effects of packet loss and avoid the need for coordination among relaying nodes.

• Experiments have described the available tradeoffs between different system parameters. – Number of relaying nodes and the added

redundancy must be carefully adjusted.