Volume 18 Issue 1
May  2020
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Yung-Fa Huang, John Jenq, Cing-Chia Lai, Jyu-Wei Wang. Adaptive Path Selection Scheme with Combining for Multiple Relaying Cooperative Communications Networks[J]. Journal of Electronic Science and Technology, 2020, 18(1): 83-92. doi: 10.11989/JEST.1674-862X.71018108
Citation: Yung-Fa Huang, John Jenq, Cing-Chia Lai, Jyu-Wei Wang. Adaptive Path Selection Scheme with Combining for Multiple Relaying Cooperative Communications Networks[J]. Journal of Electronic Science and Technology, 2020, 18(1): 83-92. doi: 10.11989/JEST.1674-862X.71018108

Adaptive Path Selection Scheme with Combining for Multiple Relaying Cooperative Communications Networks

doi: 10.11989/JEST.1674-862X.71018108
Funds:  This work was supported by MOST under Grant No. 105-2221-E-324-019
More Information
  • Author Bio:

    Yung-Fa Huang received the B.Eng. degree from National Taipei University of Technology, Taipei in 1982, the M.Eng. degree from National Tsing Hua University, Hsinchu in 1987, and the Ph.D. degree from National Chung Cheng University, Chiayi in 2002, all in electrical engineering. During 1987 to 2002, he was an instructor with Chung Chou Institute of Technology, Yuanlin. From February 2002 to July 2004, he worked with the Department of Electrical Engineering, Chung Chou Institute of Technology, as an associate professor. From August 2004 to July 2007, he was an associate professor with the Graduate Institute of Networking and Communication Engineering, Chaoyang University of Technology, Taichung. From August 2007 to July 2008, he was the Head of the Department of Computer and Communication Engineering and the Institute Chair of the Graduate Institute of Networking and Communication Engineering, Chaoyang University of Technology. From August 2008 to July 2010, he was the Head of the Department of Information and Communication Engineering, Chaoyang University of Technology. Since September 2012, he has been a professor with the Department of Information and Communication Engineering, Chaoyang University of Technology. His current research interests include multiuser detection in orthogonal frequency division multiplexing-code division multiple-access (OFDM-CDMA) cellular mobile communications systems, communications signal processing, fuzzy systems, and wireless sensor networks. He is also the Member of IEEE and serves as a Co-Chair of IEEE System Man and Cybernetics Society Technical Committee on Intelligent Internet Systems

    John Jenq received his B.S. degree of science education in physics from National Changhua University of Education, Changhua in 1977. He received his M.S. and Ph.D. degrees from University of Minnesota, Minneapolis in 1986 and 1991, respectively, both in computer and information science with minor in electrical engineering. Before he joined in the Computer Science Faculty, Tennessee State University, Nashville in 1992, he was a research associate to develop expert systems for the College of Agriculture, University of Minnesota. From 1998, he has been with the Department of Computer Science, Montclair State University, Montclair. His research interests include parallel processing, algorithms, intelligent web based systems, and computational finance

    Cing-Chia Lai received the B.Eng. degree in computer engineering from Hsiuping University of Science and Technology, Taichung in 2008. He received his M.Eng. degree in computer science engineering from Chaoyang University of Technology, Taichung in 2010. From October 2011 to February 2013, he was a Linux software engineer with D-Link Corporation, Taipei. Since February 2013, he has been a senior software engineer with Zyxel Communications, Hsinchu. His current research interests include cooperation networks in cellular mobile communications systems, embedded Linux systems, and open sources in GNU/Linux and 802.11ac wireless networks

    Jyu-Wei Wang received the Ph.D. degree in electrical engineering from National Chung Cheng University in 1999. He spent most of his past career time with Chunghwa Telecom Co., Ltd., Taipei. Now he is working with the Department of Photonics and Communication Engineering, Asia University, Taichung, where he is an associate professor. His current research interests include wireless communications, wireless sensor networks, and computer communications networks

  • Corresponding author: Y.-F. Huang is with the Department of Information and Communication Engineering, Chaoyang University of Technology, Taichung 41368 (e-mail: yfahuang@cyut.edu.tw).; J.-W. Wang is with the Department of Photonics and Communication Engineering, Asia University, Taichung 41354 (e-mail: jwwang@asia.edu.tw).
  • Received Date: 2017-01-11
  • Rev Recd Date: 2017-04-18
  • Available Online: 2020-05-06
  • Publish Date: 2020-03-01

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Adaptive Path Selection Scheme with Combining for Multiple Relaying Cooperative Communications Networks

doi: 10.11989/JEST.1674-862X.71018108
Funds:  This work was supported by MOST under Grant No. 105-2221-E-324-019
  • Author Bio:

  • Corresponding author: Y.-F. Huang is with the Department of Information and Communication Engineering, Chaoyang University of Technology, Taichung 41368 (e-mail: yfahuang@cyut.edu.tw).;  J.-W. Wang is with the Department of Photonics and Communication Engineering, Asia University, Taichung 41354 (e-mail: jwwang@asia.edu.tw).

Abstract: In future communications, cooperative communications with relay networks will be one of the most effective schemes to enlarge the coverage area and to boost the data rate. In the recent research results, the path selection, power allocation, and relay protocols on relay networks are the most important factors to improve the system performance. However, the channel quality of the direct transmission path and the relaying path has an influential effect on the performance of relay networks. Therefore, in this paper, we propose a best relaying path selection (BRPS) scheme to obtain the path diversity to improve the system capacity and data rate for cooperative networks (CNs). Simulation results show that the more the relay nodes are selected, the lower the bit error rate (BER) is. The proposed BRPS scheme obtains a high concession between both BER and system capacity for CNs.

Yung-Fa Huang, John Jenq, Cing-Chia Lai, Jyu-Wei Wang. Adaptive Path Selection Scheme with Combining for Multiple Relaying Cooperative Communications Networks[J]. Journal of Electronic Science and Technology, 2020, 18(1): 83-92. doi: 10.11989/JEST.1674-862X.71018108
Citation: Yung-Fa Huang, John Jenq, Cing-Chia Lai, Jyu-Wei Wang. Adaptive Path Selection Scheme with Combining for Multiple Relaying Cooperative Communications Networks[J]. Journal of Electronic Science and Technology, 2020, 18(1): 83-92. doi: 10.11989/JEST.1674-862X.71018108
    • In the age of seamless wireless communications, the crammed full communications systems exhibit the interactivities in nowadays[1]. The interactivities between the communications terminals become more important. Therefore, the design of the cooperative communications is the involution scheme of the next generation communications networks[2],[3]. The multiple input and multiple output (MIMO) communications systems can effectively lower the bit error rate (BER) and improve the system capacity with multiple antennas[4]-[8]. The multi-radio and multi-channel (MRMC) technique with cooperative communications is exploited to combat co-channel interference and improve the performance of multi-hop wireless networks[9]. Cooperative communications or distributed MIMO systems are an emerging paradigm for increasing the spectral efficiency, coverage extension, and small cell deployment[10]. The effect of polarization on the downlink achievable sum-rate of multi-user cooperative multi-point systems was studied using synchronous multi-link channel measurement with two different antenna arrangements[11]. MIMO with a zero-forcing based linear receiver in the source-to-relay link was employed to enhance the radio frequency (RF) link data rate[12]. The amplify-and-forward (AAF) based cooperation in a MIMO relay network with two antennas at each node over the independent but not necessarily identically distributed Nakagami-m fading channels system has been studied in [13]. However, the multiple antennas for effective MIMO are not suitable to equip in the small handset. In cooperative networks (CNs), the path diversity increases the coverage of wireless communications systems[14]. Moreover, the spatial diversity increases the capacity of the wireless channels[15]. Thus, the relay nodes can relay data from the source node to the destination node to increase the path diversity.

    • In the cooperative communications, data are modulated by binary phase shift keying (BPSK) as shown in Fig. 1[16]. Moreover, the networking model for CNs consists of three parts: One source node S, one destination node D, and several relay nodes Ri, as shown in Fig. 2. As for the channels, there are three kinds of channels: Source to relay, $h_{{s,r}_i} $, source to destination, hs,d, and relay to destination, $h_{{r_i},d} $.

      Figure 1.  System model for the wireless communications systems.

      Figure 2.  Network model for the cooperative communications.

      In the wireless communications networks, the transmitted electromagnetic signal suffers the path loss and fading induced by the multiple reflections, refractions, and scattering through the obstacles. Thus the received nth symbol signal at the receiver of destination is obtained by

      where xs={+1, –1} is the transmitted data, as,d is Rayleigh fading, and ds,d is the path loss from source S to destination D. Thus, hs,d=ds,das,d. The term zs,d is the added white Gaussian noise (AWGN) with zero mean and variance σ2 for the link of the source node to the destination node.

    • In the basic cooperative communications, there are three nodes and three wireless channels. When the source node transmits data to the destination node, there are three types to perform the transmission. The first one is that the source node transmits data directly to the destination node through the direct path, hs,d. Then the received signal is obtained by

      The second one is that the source node transmits data to the relay node. Thus, the received signal at the rith relay node can be obtained by

      where the term ${z_{s,r}} $ is AWGN with zero mean and variance σ2 for all links of the source node to relay nodes. And then the relay nodes relay data to the destination node. Thus, the received signal at the destination node is obtained by

      The third is called as the cooperative mode which combines the two signals received from the source directly and from the relay nodes by relaying[16]. The term ${z_{r\!,d}} $ is AWGN with zero mean and variance σ2 for all links of the relay nodes to the destination node.

    • Moreover, to obtain the effective cooperation, two types of cooperative protocols have been developed[16],[17]. AAF[16] can be used to simply amplify the relaying signal while the computation power of the relay nodes is limited. However, there exists a weakness of the noise enhancement. Thus, to compromise the signal amplification and noise enhancement, the amplified gain can be optimized by

      where $ {h_{s,r}}$ is the estimated channels gain[16], ξ=E[|x|2] is signal power (E[·] represents the expectation operation), and $ {{{\sigma} _{s,r}}^2}$ is the variance of noise in the channel from the source node to the relay nodes. The other scheme is the decode-and-forward (DAF)[3], which relays the signal after decoding the received signal correctly.

    • In the wireless CNs, the received signal at the destination node would probably be obtained from more than two paths. Then many combining methods can be selected to optimize the received signal to noise ratio (SNR).

      The selection combining (SC) is the simplest method to select the most adequate channel to transmit the signal. The receiver needs to continually measure the channels situation to provide a good choice. The received signal by SC is obtained by

      where the symbol ∠hs,d in the superscript represents the phase part of the link $ {h_{s,d}}$. SNRs,r,d represents SNR of the link of source-relay-destination. To maximize SNR, the maximum ratio combining (MRC)[16] is performed by weighting the signal power of each path. When MRC is applied to the three nodes model, the received signal is obtained by

      where $ {g_1}$ and $ {g_2}$ are the weights applied to the direct path and the relaying path, respectively, by

      for the DAF scheme. If the relaying path is with the AAF scheme, ${g_1} $ and ${g_2} $ are obtained by

      where [·]* is the conjugate operation.

    • To perform the adaptive cooperative communications, the channel side information should be estimated and link quality should be evaluated[16]. When BPSK is used, BER for the single link quality based on channel side information (CSI) can be obtained by

      where h is the channel gain, γ is the instantaneous SNR of the channel, and Q(x) is the complementary error function given by [18]:

      Similarly, when QPSK is used, the instantaneous BER for the single link quality based on CSI can be obtained:

      However, in the cooperative communications, the link quality should be estimated based on the cooperative communications link. That is, with the exception of the direct link, the links of the relaying paths should also be included for the link estimation. Therefore, after BERs for CNs (S, R, and D) are gathered, with the BPSK scheme, the instantaneous SNR of the cooperative link can be estimated by

      where $ {\rm{BE}}{{\rm{R}}_{s,r\!,d}}$ is BER of the cooperative link in CNs (S, R, and D). Similarly, with QPSK, the instantaneous SNR of the channel can be estimated by

    • The channel capacity depends on the channels impulse response and SNR. Thus the channel capacity in a direct transmission path can be obtained by

      where ${{{E_b}} / {{N_o}}}$ is SNR in the channel. Moreover, the channel capacity in a DAF scheme can be obtained by[17]

      where the fraction 1/2 means that two time slots are used in the path. Therefore, it is easy to know that the relaying path decreases the system capacity in the cooperative communications. Besides, to perform effective relaying for the DAF scheme, the error coding should be included in the transmission of the source node to the relay nodes to ensure the decoding decision. In this paper, we add cyclic redundancy codes (CRCs) to perform the data error checking before the data relaying at the relay node.

    • In the cooperative communications, CSI is assumed to be perfectly estimated, such that the combining schemes can be used to perform the diversity gain. Moreover, the cooperative schemes of SC and MRC can be selected to obtain the required capacity. The optimization for CNs is obtained with SC and MRC via DAF protocols[3] in which the best relay selection method is shown as Fig. 3.

      Figure 3.  System model of relaying networks for the proposed best relay selection scheme with the number of relay nodes I=2.

      However, in this paper, the optimal cooperative path is obtained with SC by

      where ${\rm{SNR}}_{s,r\!,d}^i$ is defined at the instantaneous SNR for the relay network (S, R, and D). Therefore, to compromise the system capacity and link quality, an adaptive path selection (APS) scheme is proposed in this paper. There are seven adapted paths for CN with the number of relay nodes I=2 as shown in Table 1. Then, by MRC the received signal at the destination node can be obtained by

      No.Transmission pathInstantaneous SNR, γ
      1S to DSNRs,d
      2S to R1 to DSNR${{\rm{}}_{s,{r_1},d}}$
      3S to R2 to DSNR${{\rm{}}_{s,{r_2},d}}$
      4S to D + S to R1 to DSNR${{\rm{}}_{{r_1}\_{\rm{coop}}}}$
      5S to D + S to R2 to DSNR${\rm{}}{{\rm{}}_{{r_2}{\text{\_}}{\rm{coop}}}}$
      6S to R1 to D + S to R2 to DSNR${\rm{}}{{\rm{}}_{s,{r_i},d{\text{\_}}{\rm{coop}}}}$
      7S to D + S to R1 to D + S to R2 to DSNR${\rm{}}{{\rm{}}_{{\rm{coop}}}}$

      Table 1.  Instantaneous SNR for the proposed APS schemes

      where

      Moreover, with the perfect channel estimation, an adaptive threshold of the instantaneous channel gain is proposed to select the highest quality path.

    • In order to verify the performance of CNs, we performed the computer simulation using MATLAB programming for the system models in Fig. 3. The system models and simulation parameters are shown in Table 2.

      AbbreviationsDescriptions or parameters
      BPSKBinary phase shift keying
      QPSKQuadrature phase shift keying
      MRCMaximum ratio combining
      DAFDecode-and-forward
      BRPSBest relaying path selection
      Relay number Nr2
      Number of bits216
      AWGNGaussian distributed, independent, and zero mean with variance 2σ2
      Fading channelRayleigh fading channel

      Table 2.  Simulation structure and system parameters

      At first we investigated the performance of the MRC receiver for CNs as shown in Fig. 4. It is observed that MRC can improve the BER performance. The non-selection scheme provides more diversities of the cooperative links for CNs.

      Figure 4.  Comparisons of the selection on the best path for I =1 and I =2 with the MRC scheme for CNs.

      Moreover, the channel capacity in CNs is compared with the number of relay nodes I=1 and I=2, as shown in Fig. 5. It is observed that when the number of relay nodes I increases, the system capacity declines. That is because with TDMA, the channel capacity will be decreased by 1/(I+1). Moreover, the performance with CRC in the dash line slightly increases the system capacity for the lower SNR environment.

      Figure 5.  Capacity of CNs for I =1 and I =2 with CRC.

      Moreover, we investigated the performance of the MRC receiver for CNs as shown in Fig. 6. From Fig. 6, it is observed that MRC improves the BER performance. The multiple-input single-output (MISO) systems with two transmitter antennas and one receiver antenna denoted by 2×1 can obtain the maximal two-path diversity gain. The non-selection scheme with I=2 MRC provides more diversities of the cooperative links for CNs. However, the proposed BRPS scheme approaches the best performance comparing with the other cooperative communications schemes.

      Figure 6.  Comparisons of the selection on the best path for I=1 and I=2 with the MRC scheme in CNs.

      The channel capacity in CNs was compared with the number of relay nodes I=1 and I=2, as shown in Fig. 7. From Fig. 7, it is observed that as the number of relay nodes I increases, the system capacity declines. That is because with TDMA, the channel capacity will be decreased by 1/(I+1).

      Figure 7.  Capacity of CNs for I=1 and I=2.

      Furthermore, to investigate the need of the number of relay nodes, the average number of relay nodes is calculated for the comparisons as shown in Figs. 8 and 9. From Figs. 8 and 9, the proposed BRPS scheme needs less relay nodes than the conventional DAF schemes.

      Figure 8.  Comparison of the number of relay nodes for I=1 with MRC.

      Figure 9.  Comparison of the number of relay nodes for I=2 with MRC.

      Therefore, it can be derived that both BER and capacity performance are exclusive with each other. The path diversity gain with the relay nodes improves the BER performance but lowers the system capacity as shown in Fig. 10.

      Figure 10.  Compromise on both BER and system capacity for CNs.

    • In this paper, we investigated the relay diversity gain for CNs. Moreover, we proposed a BRPS scheme to improve the system capacity and data rate for CNs. Simulation results showed that the more the relay nodes were selected, the lower BER. The proposed BRPS could obtain the compromise between BER and system capacity for CNs.

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