LiNKS

Link-State Based Optimal Transmission for the Two-way Relay Channel

Link-State and Priority Based Transmission

Figure 1: Two-way relay channel model in an ad-hoc network with general Rayleigh fading links.
Figure 1: Two-way relay channel model with general Rayleigh fading links.

Project Overview:

Wireless links between nodes of the one-way and two-way relay channel depend upon the distance between the nodes, pathloss, and fading. In this project, a composite coding scheme for both the one-way and two-way relay channel is designed to be optimal for the links between the active users and relay. Further, because wireless links vary over time due to fading, our composite scheme adapts to the changing link state. When applied in the two-way relay channel, the composite scheme has the capability to prioritize one user of the other. When applied in a larger network setting, this project investigates how to prioritize users of the system.

Motivation:

One particular transmission scheme may be optimal for certain channel conditions, or link states, but not in others. This project seeks to find which decode-and-forward (DF) relaying strategy is optimal depending on the link state of the system. Further, in a wireless environment, links change frequently due to fading. As such, the optimal transmission scheme may change over time. Therefore, not only does this project identify the optimal coding scheme based on the link-state, but it also explores how to perform link adaptation in a fading environment.

Reducing relay transmit power allows the relay to operate longer and improves the overall network performance. Further, by transmitting below full power, the relay creates less interference to other nodes in the network, resulting in better network performance. Therefore, it is of interest to design a transmission scheme that achieves the maximum rate using the minimum relay transmit power.

Composite Decode-Forward Transmission Scheme:

In this scheme, the relay has the option of transmitting using three distinctive techniques: independent coding, a signal structure that enables block Markov coding at the sources, or a combination of these two approaches. Both sources may perform block Markov coding or independent coding depending on the signal structure at the relay. We investigate how link states affect which transmission strategy should be chosen in order to produce the largest rate region. For a given set of link states, our analysis reveals which coding strategy will produce the largest rate region.

Figure 2. Composite decode-forward scheme optimally combines independent coding and block Markov coding depending on the link states.
Figure 2. Composite decode-forward scheme optimally combines independent coding and block Markov coding depending on the link states.
Figure 3. In some link-state regimes, the composite decode-forward scheme achieves a larger rate region than either block Markov coding or independent coding or timesharing between them.
Figure 3. In some link-state regimes, the composite decode-forward scheme achieves a larger rate region than either block Markov coding or independent coding or timesharing between them.

 

 

Figure 4. Optimal transmission as a function of distance for FDD system
Figure 4. Optimal transmission as a function of distance for FDD system

Discussion and Results

Results demonstrate that when the user-to-relay link is just marginally stronger than the direct links, independent coding is employed to provide a network coding gain. With only independent coding, the source uses full power for the new message in each block and the relay uses just enough power to forward the old message. In this case, the relay does not need to use full power. As the user-to-relay link becomes stronger, block Markov coding is also used. This theme of transitioning from direct transmission to independent coding to block Markov coding as the link state improves is illustrated in a frequency-division duplex system (FDD) in Fig. 4. The distance between the two users is fixed at 20 meters while the relay location varies over the entire X-Y plane, typical inter-node distances for a small cell in 5G systems. Because this is a FDD system and user 1 is prioritized, the regions are not symmetric.

 

 

Figure 5. Percentage of power savings in a spatial simulation
Figure 5. Percentage of power savings in a spatial simulation

 

Relay Power

From the analysis, it was found that the relay can conserve power when performing only independent coding, a result that follows naturally from the formulation of the problem. When considering this composite scheme in Rayleigh fading, for any inter-node distance configuration, there will be some probability of link-state regimes that enable relay power savings. Hence, in Figure 5, we have the same simulation setup as in Figure 4 but now simulate the percentage of relay power savings. One significant result from this simulation is the vast proportion of space that the relay can save over power (up to 20% in this scenario).

 

 

Figure 6.
Figure 6. (One-way relay channel) Source and relay are assumed to have practical CSI (perfect receive CSI and long-term transmit CSI); a) Relay power savings; b) Rate gain over direct transmission

Rate versus Power Savings for Relay Placement

By comparing the relay power savings and rate gain over direct transmission assuming practical CSI in the one-way relay channel (Fig. 6), we demonstrate a trade-off between rate and power savings for relay placement when the relay is between the source and destination. It is evident that the most rate gain is obtained when the relay is closer to the source and the most power savings are realized when the relay is closer to the destination. Specifically if the relay is between the source and destination but closer to the source, employing the composite scheme with practical CSI results in up to 300% rate gain over direct transmission, a significant gain. However, when the relay is instead closer to the destination, rate gain is sacrificed for power savings at the relay, which is up to 90%.

 

Publications:

  1. “Link Regime and Power Savings of Decode-Forward Relaying in Fading Channels,”
    L. Pinals, A. A. Al Haija, and M. Vu, IEEE Trans. on Communications, vol. 64, no. 3, pp. 931-946, March 2016.
  2. “Link-State Optimized Decode-Forward Transmission for Two-Way Relaying,”
    L. Pinals and M. Vu, IEEE Trans. on Communications, vol. 64, no. 5, pp. 1844-1860, May 2016.
  3. “Maximum Entropy Quantization for Link-State Adaptation in Two-Way Relaying,”
    L. Pinals and M. Vu, MILCOM, 2015.
  4. “Relay Power Savings Through Independent Coding,”
    L. Pinals and M. Vu, Globecom, 2015.
  5. “Link State Based Decode-Forward Schemes for Two-way Relaying,”
    L. Pinals and M. Vu, International Workshop on Emerging Technologies for 5G Wireless Cellular Networks (Globecom), Dec 2014.
  6. “Adaptation of Decode-Forward Two-Way Relaying to Fading Links: a Rate and Power Analysis,”
    L. Pinals and M. Vu, International Conference on Communications (ICC), June 2015.