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[Author] Youhua FU(2hit)

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  • Clustering for Interference Alignment with Cache-Enabled Base Stations under Limited Backhaul Links

    Junyao RAN  Youhua FU  Hairong WANG  Chen LIU  

     
    PAPER-Wireless Communication Technologies

      Pubricized:
    2019/12/25
      Vol:
    E103-B No:7
      Page(s):
    796-803

    We propose to use clustered interference alignment for the situation where the backhaul link capacity is limited and the base station is cache-enabled given MIMO interference channels, when the number of Tx-Rx pairs exceeds the feasibility constraint of interference alignment. We optimize clustering with the soft cluster size constraint algorithm by adding a cluster size balancing process. In addition, the CSI overhead is quantified as a system performance indicator along with the average throughput. Simulation results show that cluster size balancing algorithm generates clusters that are more balanced as well as attaining higher long-term throughput than the soft cluster size constraint algorithm. The long-term throughput is further improved under high SNR by reallocating the capacity of the backhaul links based on the clustering results.

  • Joint MMSE Design of Relay and Destination in Two-Hop MIMO Multi-Relay Networks

    Youhua FU  Wei-Ping ZHU  Chen LIU  Feng LU  Hua-An ZHAO  

     
    PAPER-Wireless Communication Technologies

      Vol:
    E96-B No:3
      Page(s):
    836-846

    This paper presents a joint linear processing scheme for two-hop and half-duplex distributed amplify-and-forward (AF) relaying networks with one source, one destination and multiple relays, each having multiple antennas. By using the minimum mean-square error (MMSE) criterion and the Wiener filter principle, the joint relay and destination design with perfect channel state information (CSI) is first formulated as an optimization problem with respect to the relay precoding matrix under the constraint of a total relay transmit power. The constrained optimization with an objective to design the relay block-diagonal matrix is then simplified to an equivalent problem with scalar optimization variables. Next, it is revealed that the scalar-version optimization is convex when the total relay power or the second-hop SNR (signal to noise ratio) is above a certain threshold. The underlying optimization problem, which is non-convex in general, is solved by complementary geometric programming (CGP). The proposed joint relay and destination design with perfect CSI is also extended for practical systems where only the channel mean and covariance matrix are available, leading to a robust processing scheme. Finally, Monte Carlo simulations are undertaken to demonstrate the superior MSE (mean-square error) and SER (symbol error rate) performances of the proposed scheme over the existing relaying method in the case of relatively large second-hop SNR.