Keywords: Wireless Relay Networks, Transmission Rate, Relay Selection, Power Control.

Transcription

1 6 International Conference on Service Science Technology and Engineering (SSTE 6) ISB: Relay Selection and Power Allocation Strategy in Micro-power Wireless etworks Xin-Gang WAG a Lu Wang b a Li c Yi-Chen XU d Shen-Long LI e ai-bin LIU f Xiniang Electric Power Company Research Institute Xiniang China China GRIDCOM Co. Ltd Shenzhen Guangdong China a wangxingang@dky.x.sgcc.com.cn b wanglu@dky.x.sgcc.com.cn c lina@dky.x.sgcc.com.cn d xuyichen@dky.x.sgcc.com.cn e lishenlong@sgitg.sgcc.com.cn f liuhaibin@sgitg.sgcc.com.cn Keywords: Wireless Relay etworks Transmission Rate Relay Selection Power Control. Abstract: This paper investigates the problem of relay selection and optimal power allocation in micro-power wireless network under the total power constrain. We first propose the relay selection strategy by using the greedy algorithm in which the power is allocated equally. Then we transform the problem into a convex optimization one by using the high SR approximation and its equivalent form under the optimal condition. A closed-form result can be obtained with the Lagrange method. Using the Lagrange s approach we obtain a closed-form result of the relay selection and power allocation. The simulations results demonstrate the advantage of the proposed strategy. Introduction Smart grid will become the next generation electrical power grid integrating modern information communication and electronic technologies. And the micro-power wireless network plays an important role in smart grid due to its low-cost easy-deployment characteristics. owever since the energy resource of a micro-power wireless network is limited the maximum of energy efficiency must be achieved by using advanced techniques. Cooperative communication technique based on cooperative diversity has been adopted to improve smart grid s performance by taking advantage of the broadcast nature of wireless channels. Various issues (e.g. scheduling [] power allocation [] and routing [3]) have been addressed of cooperative transmission in the literature. In [4] subcarrier and power allocation schemes were proposed and analyzed for different scenarios for a two-hop amplify-and-forward OFDM relay network. And a fully distributed algorithm where the oint routing relay selection and power allocation problem has been proposed in [5] to minimize power consumption. owever none of them considers the wireless environment for smart grid which has different transmission requirements. In this paper two-hop cooperative transmission is considered. Specifically the relay station of a community adopts the amplify-and-forward (AF) relaying scheme. Then the relay selection method and power allocation strategy are introduced to acquire the maximum power efficiency. And the simulation shows that the scheme proposed in this paper can lead to performance gain. The rest of this paper is organized as follows. Our system model is described in Section II. Then we design a relay selection and power allocation strategy in 56

2 Section III. After evaluating our proposed schemes in Section IV we conclude our paper in Section V. System Model As shown in fig. we consider a micro-power wireless communication system where the source is communicating with destinations through a relay for each. The number of relays in the system is M (m>=). Figure. System Model. The signals transmitted from the source to a certain destination can be overheard by relays in this system. And one of the relay nodes will repeat the transmission which makes it possible for the destination to receive multiple independent copies of the transmitted information from the source and the relay. According to [6-7] the maximum SR at the destination can be expressed as SR Ps hs d Ps Pr hs r hr d max = + Ps hs r + Pr hr d + () Where P s and Pr are transmit powers of the source and the relay; h s r hs d and h r d represent the channels fading. is the average power of Gaussian noise. To maximize the total system throughput under the total power constrain the optimization problem can be formulated as M Ps h s Ps hs r Pr h r max ρr log + + r= = s s r r r P h P h + + () Subect to: 57

3 M P + ρ P = P (3) s r r total = r= = M ρr = (4) r= { } ρ r = (5) P P (6) s r where P s Pr represent the average power using to transmit signal for destination on source and relay. ρ r is the relay-destination pair parameter. Relay Selection and Power Allocation The problem above cannot be solved efficiently if we oint power allocation and relay selection together. ence we separately discuss relay selection algorithm and power allocation scheme. Start : P = P = P / ρ = ; r s r total Relay set : S = {... M} r For = to Find k in S satisfying Rk R ρ r = r k ; ρ k n = ( ) S = S { k} end r a. relay selection algorithm The main aim of throughput-oriented relay selection algorithm is to maximize the total date rate without considering power allocation. It is sometime referred to as greedy algorithm. The summary of the greedy relay selection algorithm is as follows: b. power allocation for a single destination According to [89] we obtain Ps hs r Pr h r Ps hs r Pr hr + + Ps hs r Pr h r Ps hs r Pr hr + Denoting h. (7) s = (8) 58

4 3 hs r = (9) h r = () P / P = m () r s P + P = P () r s the rate for destination can be expressed as R = log + P + m 3 r + m + m + m 3 And it can be proved that Rr can be optimized when m satisfies. (3) m 3 = ( + ) 3 ( + ) 3 3 < 3. (4) c. power allocation among destinations Denoting m = + + m + m + m 3 3. (5) the optimization problem can be transformed into max log + P = ( ) s t + m P = P = P total after the relay-destination pairs have been determined. The optimum results of acquired with the help of Lagrange s interpolation. P = =... λ ( + m ) (6) P can be (7) where λ can be obtained by ( ) = + m P = P total. IV Simulation Result 59

5 3 system capacity(bit/sec/z) cooperative non-cooperative with power allocation proposed algorithm P/(dB) Figure. System Capacity. In this section we confirm our simulation results through comparison with other strategies. We assumed that all relay nodes all relay nodes are located units away from the source. And all destination nodes are located d units away from the relay nodes. The numbers of relays and destination nods are M = = 5. We choose TGn. A model to simulate the channel fading. In figure we compared total system capacity of proposed algorithm with non-cooperative with power allocation scheme and cooperative without power allocation scheme. And it is observed that the proposed cooperative and power allocation strategy provides better performance than others. In figure 3 we plot the transmission rates of different destination nodes when P/=5dB. And it is observed that the rate of certain destination may be decreased for cooperative with power allocation scheme as the power allocation between nodes can cause fairness problems. 8 7 proposed algorithm cooperative without power allocation non-cooperative with power allocation 6 5 rate(bit/sec/z) node number Figure 3. Transmission Rates between Destinations. 6

6 Conclusion We have analyzed the performance of power allocation scheme in two hop AF relay micro-power networks in home environments. We first adopted greedy algorithm to determine the relay-destination pairs. Then we obtained the optimum power allocation scheme with the help of Lagrange s interpolation. Our results indicate that the relay selection and power allocation strategy between different users can get a performance gain in terms of system capacity and energy efficiency. Acknowledgement Thankful to fund from research proects of various kinds of data acquisition methods and related technologies for its support in this paper. Reference [] S. Senthuran A. Anpalagan and O. Das Cooperative Subcarrier and Power Allocation for A Two-op Decode-and-Forward OFCMD Based Relay etwork IEEE Trans. Wireless Commun. vol. 8 no. 9 Sept. 9 pp [] L. Le and E. ossain Cross-Layer Optimization Frameworks For Multihop Wireless etworks Using Cooperative Diversity IEEE Trans. Wireless Commun. vol. 7 no. 7 July 8 pp [3] Y. Yang et al. Relay Technologies for WiMax and LTE Advanced Mobile Systems IEEE Commun. Mag. vol.47 no. Oct. 9 pp. 5. [4] Lande S.B.; Shende S.P.; Pathak S.S. "Strategic Subcarrier Allocation for Cooperative OFDMA Relaying etwork" in Electronic Systems Signal Processing and Computing Technologies (ICESC) 4 International Conference on vol. no. pp Jan. 4. [5] S. S. Ikki O. Amin and M. Uysal Performance Analysis of Adaptive L-QAM for Opportunistic Decode-and-Forward Relaying Proc. VTC-Spring May. [6] Zhao Yi Adve Ravira Lim Tengoon. Improving Amplify-and-Forward Relay etworks: Optimal Power Allocation versus Selection. IEEE Transactions on Wireless Communications 7 6(8): [7] Shen Yanyan Feng Gang Yang Bo Guan Xinping. Resource Allocation with Proportional Rate Fairness in Orthogonal Frequency Division Multiple Access Relay etworks. Wireless Communications and Mobile Computing 4 4(): [8] Junsu Kim Diomidis S. Michalopoulos Robert Schober. Diversity Analysis of Multi-User Multi-Relay etworks. IEEE Transactions on Wireless Communications (7): [9] ammerstrom Ingmar Wittneben Armin. Power Allocation Schemes for Amplify-and-Forward MIMO-OFDM Relay Links. IEEE Transactions on Wireless Communications 7 6(8):