ISSN ONLINE(2319-8753)PRINT(2347-6710)

Power Allocation for Two Source Destination Pair Cooperative Communication System under The Outage Probability Constraint

P.Mangayarkarasi1, A.Kalpana2, Dr.S.Jayashri3
  1. Assistant Professor, Department of ECE, Adhiparasakthi Engineering College, Melmaruvathur, Tamil Nadu, India
  2. PG Student, Department of ECE, Adhiparasakthi Engineering College, Melmaruvathur, Tamil Nadu, India
  3. Professor, Department of ECE, Adhiparasakthi Engineering College, Melmaruvathur, Tamil Nadu, India
Related article at Pubmed, Scholar Google

Visit for more related articles at International Journal of Innovative Research in Science, Engineering and Technology

Abstract

To achieve the multiuser diversity and cooperative diversity, a two source destination pair is considered for cooperative communication system. Hybrid Decode Amplify Forward (HDAF) Relaying Protocol improves the system performance by combining the merits of both Amplify Forward (AF) and Decode Forward (DF) protocols is used. The fast and efficient Parallel Shift Water Filling (SPWF) algorithm can minimize the total power, based on the outage probability constraint. In the conventional algorithms, the solution is obtained by an iterative binary searching and Lagrange Multiplier searching process. In contrast, PSWF Algorithm removes the iterative searching process. It executes the PSWF only once, and then directly calculates the final solution with the parallel shift property as an enabling mechanism. Numerical analysis is used to compare the various relaying protocols based on outage probability and Bit Error Rate.

Keywords

Cooperative communication system, HDAF Relaying Protocol, Outage Probability, PSWF Power Allocation.

INTRODUCTION

In mobile terminals, it is difficult to support multiple antennas due its limitations in size, cost, complexity, etc. The alternative approach to achieve spatial and cooperative diversity without multiple antennas is the cooperative communication system [1]. Spatial diversity is that several antenna elements separated in space. Cooperative diversity is that several cooperative multiple antenna elements separated in space. Advantages of Cooperative communication system are ease of implementation, good scalability, increased connectivity, better coverage, reduced operating power level etc. Cooperative communication system consists of three nodes, a) Source, which transmits the signal, b) Relay, which forwards its signal to destination by some relaying protocols, c) Destination, receives the signal from relay and source. Amplify and forward relay will amplify its signal and forward it to the destination. But the demerit here is the amplification of noise [2]. Decode and Forward relay will regenerate the original signal and passes the clean set of signals to destination. It provides clean data extraction. But the demerit of this is if the relay wrongly decodes the signal, the performance of the system is degraded [3]. These observations motivate a new signal forwarding scheme that combines the benefits from AF and DF, this scheme is called Hybrid Decode Amplify Forward (HDAF) relaying. The intuition behind this protocol is that, if the relay cannot decode the signal correctly or the link between the relay and source is not good enough, then the relay will amplify the signal and forward the amplified signal to destination.

II. RELATED WORK

The relay will forward the reliable information to the destination by performing soft decoding and forward the reliable information to destination [4]. The Symbol Error Probability (SEP) of HDAF cooperative system has been analyzed [5]. HDAF protocol is the best relaying protocol when the quality of relay destination link is better than source relay [6]. The expressions for outage probability and Bit Error Rate (BER) have been derived [7]. In [8] and [9], the scheme requires many relay nodes to forward the received signal to destination and it degrades the spectral efficiency.
In recent years, there is an increasing interest in investigating the relaying in MIMO networks, which improves the achievable rate in shared spectrum multiple access wireless networks [10]. MIMO achieves the cooperative diversity, with the support of multiple relays [11]. The result of using multiple relay schemes is very low spectral efficiency and high complexity. To reduce the spectral efficiency loss and high complexity, decrease the number of relays. Hence, the two source destination pair relay network is modelled [12]. Therefore, each source destination pair can achieve the cooperative diversity, where another source will act as the relay.Beyond these considerations, to improve the performance of cooperative communication system due to limited transmission power, the most important design consideration is the power allocation. Various power allocation schemes are proposed to maximize the minimum SNR, to minimize the maximum transmit power and to maximize the network throughput [13]. The Water Filling power allocation algorithm using iterative binary searching process has been proposed to optimize the total power [14]. Each iterations are computationally efficient and guarantees to a local optimum. But this computational process makes it as a complex algorithm. Hence, a new power allocation algorithm called Parallel Shift Water Filling power allocation algorithm has been proposed to remove the iterative binary searching process [15]. It executes the Parallel Shift Water Filling only once, and then directly calculates the final solution with the parallelshift property as an enabling mechanism. Outage probability and power allocation for AF relaying with channel estimation errors has been investigated and it shows that significant power saving can be obtained [16].
The main objective is the power allocation for a HDAF relaying using PSWF algorithm under the outage probability constraint. The design considerations are summarized as follows. 1. The simple two source destination pair cooperative network is modeled, which can achieve high cooperative diversity in high SNR region and also reduce the spectral efficiency loss and high complexity over multiple relays in MIMO system. It achieves both cooperative diversity and multiuser diversity and reduces the total power. 2. The HDAF relaying protocol can improve system performance especially at higher SNR regions. By comparing the threshold SNR and SNR of source relay link, either AF or DF protocol will be chosen and then the signal will be forwarded to the destination. 3. The fast and efficient Parallel Shift Water Filling algorithm can minimize the total power, based on the outage probability constraint.
image
Consider the two source destination pair cooperative communication wireless network in Fig. 1, in which source nodes S1 and S2 transmit the data to destination nodes D1 and D2, respectively. A higher level network protocol has allocated bandwidth to two terminals for transmission to their intended destinations or next hops, such as, in a cellular network, S1 and S2 are respectively handsets and D1 = D2 correspond to the base station. As another consideration, in wireless local area network, D1 and D2 correspond to ad hoc configuration. Here, we assume all the channels as quasi static Rayleigh distribution. The Additive White Gaussian Noise (AWGN) with complex Gaussian components with zero mean and variance ��0 is represented at each receiver.
image
In Fig. 2, case 1 is illustrated. In that, S1 acts as a “source” and S2 acts as a “relay”. It consists of two phases. In first phase, S1 transmits the information to destinations D1 and D2 and also to relay S2. The relay will amplify or decode the information according to the SNR condition in source relay link. At lower SNR the relay will amplify the received information and at higher SNR the relay will decode the received information. Then in second phase, S2 will forward the amplified or decoded symbols to both of the destinations D1 and D2. Then at both destinations Maximum Ratio Combining (MRC) technique will be applied to combine the direct signal and the relayed signal.
image
In Fig. 3, case 2 is illustrated. In that, S2 acts as a “source” and S1 acts as a “relay”. It also consists of two phases. In first phase, S2 transmits the information to destinations D1 and D2 and to the relay S1. The relay will amplify or decode the information according totheSNRconditioninsourcerelay link. At lower SNR the relay will amplify the received information and at higher SNR the relay will decode the received information. Then in second phase, S1 will forward the amplified or decoded symbols to both of the destinations D1 and D2. Then at both destinations MRC technique will be applied to combine the direct signal and the relayed signal.
image
Some level of synchronization between the terminals is required for cooperative diversity to be effective. Consider the scenario in Fig. 4,in which the terminals are block, carrier and symbol synchronous. Given some form of network block synchronization, carrier and symbol synchronization for the network can build upon the same between the individual transmitters and receivers. It focuses on half duplex communication that lends itself more easily to practical implementation. Thus, for half duplex operation, each channel is divided into orthogonal sub channels. A. Channel Models Under the above orthogonality constraints, the channel models are characterized using a frequency division notation. During the transmission sources ��1 and ��2 broadcast their messages to each other and to the destinations ��1 and ��2 respectively. A baseband equivalent discrete time channel model considers N consecutive uses of the channel, where N is larger.For Orthogonal Direct Transmission (ODT), the received signal to the destination directly from source is
image
image
image
image
image
image
Fig. 6 presents outage probability versus available rate in two cases: (OCT). The numerical simulation results of outage probability are 0.0152, 0.143, and 0.6942 at R = 0.5, 1, and 1.5 for Non cooperative communication system. The numerical simulation results of outage probability are 0.13e-3, 0.3183e-3, and 0.5737e-3 at R = 0.5, 1, and 1.5 for HDAF Cooperative communication system. Hence, it is observed that MUD gain and diversity gain can be obtained in the form of improved outage performance.

VIII. CONCLUSION AND FUTURE WORK

A two source destination pair cooperative communication system was developed and derived closed form expressions of outage probability associated with Amplify and forward, Decode and Forward and HDAF protocols are analyzed. Based on outage probability constraint, water filling power allocation minimizes the outage probability was discussed. Numerical results offer important analytical tools and fully exploit the potential of HDAF based multiple source destination pairs.

References

1. J. N. Laneman, D. N. Tse, and G. W. Wornell, “Cooperative diversity in wireless networks: Efficient protocols and outage behavior,” IEEETransactions on Information Theory, vol. 50, no. 12, pp. 3062–3080, Dec. 2004.

2. I. Krikidis, J. Thompson, S. McLaughlin, and N. Goertz, “Optimization issues for cooperative amplify-and-forward systems over block-fading channels,” IEEE Transactions on Vehicular Technology., vol. 57, no. 5, pp. 2868–2884, Sep. 2008.

3. S. Lee, W. Su, S. Batalama, and J. D. Matyjas, “Cooperative decode-and forward ARQ relaying: Performance analysis and power optimization,” IEEE Transactions on Wireless Communications., vol. 9, no. 8, pp. 2632–2642, Aug. 2010.

4. X. Bao and J. Li, “Efficient message relaying for wireless user cooperation: Decode–amplify–forward (DAF) and hybrid DAF and codedcooperation,” IEEE Transactions on Wireless Communications., vol. 6, no. 11, pp. 3975– 3984, Nov. 2007.

5. T. Q. Duong and H. J. Zepernick, “On the performance gain of hybrid decode–amplify–forward cooperative communications,” EURASIPJournal of Wireless Communications Networking., vol. 2009, Article ID 479463, 10 pp., 2009.

6. W. Su and X. Liu, “On optimum selection relaying protocols in cooperative wireless networks,” IEEE Transactions on WirelessCommunications., vol. 58, no. 1, pp. 52–57, Jan. 2010.

7. H. Chen, J. Liu, C. Zhai, and L. Zheng, “Performance analysis of SNR-based hybrid decode–amplify–forward cooperative diversity networks over Rayleigh fading channels,” in Proceedings of IEEE Wireless Communications and Networking Conference Workshops, Sydney, Australia, Apr. 2010, pp. 1–6.

8. T. Liu, L. Song, Y. Li, Q. Huo, and B. Jiao, “Performance analysis of hybrid relay selection in cooperative wireless systems,” IEEETransactions on Communications., vol. 60, no. 3, pp. 779–788, Mar. 2013.

9. M. Abouelseoud and A. Nosratinia, “Heterogeneous relay selection,” IEEE Transactions on Wireless Communications., vol. 12, no. 4, pp. 1735–1743, Apr. 2013.

10. F. Chen,W. Su, S. Batalama, and J. D.Matyjas, “Joint power optimization for multi-source multi-destination relay networks,” IEEETransactions on Signal Processing., vol. 59, no. 5, pp. 2370–2381, May 2011.

11. S. S. Ikki and M. H. Ahmed, “Performance analysis of cooperative diversity with incremental best relay technique over Rayleigh fading channels,” IEEE Transactions on Communications, vol. 59, no. 8, pp. 2152–2161, Aug. 2011.

12. Hailin Xiao and Shan Ouyang, “Power Allocation for a Hybrid Decode – Amplify – Forward Cooperative Communication System With Two Source – Destination Pairs Under Outage Probability Constraint,” IEEE Systems Journal, vol.5, no. 9, pp.1 – 8, March 2014.

13. K. T. Phan, T. Le-Ngoc, S. A. Vorobyov, and C. Tellambura, “Power allocation in wireless multi-user relay networks,” IEEE Transactions onWireless Communications., vol. 8, no. 5, pp. 2535–2545, May 2009.

14. Hui-Ming Wang, Feng Liu, and Xiang-Gen Xia, “Joint Source-Relay Precoding and Power Allocation for Secure Amplify-and-Forward MIMO Relay Networks,” IEEE Transactions on Information forensics and security.,vol. 9, no. 8, pp. 1240 – 1250, August 2014.

15. Xiang Ling, Bin Wu, Hong Wen, Lili Pan and FengvaLuo, “Fast and efficient parallel-shift water-filling algorithm for power allocation in orthogonal frequency division multiplexing-based underlay cognitive radios,” IEEE Journals and Magazines Communications,IET, vol. 7, no. 12, pp. 1269 - 1278, Aug. 2013.

16. F. S. Tabataba, P. Sadeghi, and M. R. Pakravan, “Outage probability andpower allocation of amplify and forward relaying with channel estimationerrors,” IEEE Transactions Wireless Communications., vol. 10, no. 41, pp. 124–134,Jan. 2011.