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@PHDTHESIS{Xu:480454,
      author       = {Xu, Xiang},
      othercontributors = {Mathar, Rudolf and Ascheid, Gerd},
      title        = {{S}trategies for wireless network control with applications
                      to {LTE}},
      school       = {Aachen, Techn. Hochsch.},
      type         = {Dissertation},
      address      = {Aachen},
      publisher    = {Publikationsserver der RWTH Aachen University},
      reportid     = {RWTH-2015-03682},
      pages        = {VI, 128 S. : Ill., graph. Darst., Kt.},
      year         = {2015},
      note         = {Aachen, Techn. Hochsch., Diss., 2015},
      abstract     = {The 4th generation (4G) mobile cellular network aims at
                      providing high data rate, low latency wireless links and
                      ubiquitous connectivity. To meet these demands,
                      sophisticated network control methods are required. Since
                      the 4G mobile cellular system is constituted of many
                      advanced techniques, the Long-Term Evolution (LTE) standards
                      are established to provide unified technical specifications
                      and thus ensure compatibility. Following the LTE standards,
                      various strategies for wireless network control on both link
                      level and network level are presented and discussed in this
                      dissertation.First, to engage systematic analysis of
                      wireless networks, different channel models are reviewed.
                      Based on two existing modeling methodologies, namely,
                      geometry based stochastic model and deterministic
                      ray-launching, a semi-stochastic channel model is derived.
                      The semi-stochastic channel model first uses a geometric
                      description of the propagation environment to calculate
                      propagation paths for radio waves, and then employs
                      stochastic procedures to calculate the channel impulse
                      response for multiple-input multiple-output (MIMO) channels.
                      Hence, the semi-stochastic model can improve modeling
                      accuracy by knowledge of the propagation environment, while
                      keeping randomness for Monte-Carlo simulations. When
                      comparing with measurement data, the semi-stochastic channel
                      model shows better modeling accuracy than the WINNER
                      model.Second, the feedback information from mobile stations
                      (MS) and its influence on LTE systems are studied. Since
                      base stations (BS) need channel state information to
                      facilitate adaptive modulation and coding schemes and manage
                      radio resources, the MSs have to measure the
                      signal-to-interference-plus-noise-ratio (SINR) and send the
                      compressed channel quality indicator (CQI) to the BSs. To
                      compensate for temporal variation, prediction schemes of the
                      SINR are investigated. The statistics of SINR in a
                      multi-cell network are derived analytically for slowly
                      moving MSs. Furthermore, a simple approximation of the
                      autocovariance function of the SINR is given. Since
                      different prediction schemes show different behavior for the
                      MSs moving with different speed, that optimal prediction
                      schemes are chosen to adapt to the speed. In addition, by
                      assuming the prediction noise follows a Gaussian
                      distribution, bandwidth efficiency of LTE systems with
                      imperfect CQI feedback is obtained considering both cases
                      with and without hybrid automatic repeat request (HARQ).
                      Further investigations show that a biased estimator may
                      provide higher throughput than an unbiased one. Finally,
                      transmit power control for heterogeneous LTE networks based
                      on CQI is addressed. To provide pervasive coverage to indoor
                      users, femtocells are introduced as a part of the
                      heterogeneous network structure. Due to the shared frequency
                      spectrum among femtocells and macrocells, co-channel
                      interference is inevitable. Conventional interference
                      suppression methods usually require full knowledge of the
                      network structure or depend on the accuracy of the pathloss
                      model. The presented power control scheme takes only the
                      feedback CQIs as input. By differentiating service types of
                      users and applying different quality of service (QoS)
                      constraints, the transmit power of femtocells can be managed
                      in a self-organizing fashion. The self-organizing power
                      control does not need prior information about the network
                      structure and thus is easy to implement. It shows superior
                      performance compared to conventional methods with respect to
                      both capacity and coverage.},
      cin          = {613410 / 611810},
      ddc          = {621.3},
      cid          = {$I:(DE-82)613410_20140620$ / $I:(DE-82)611810_20140620$},
      typ          = {PUB:(DE-HGF)11},
      urn          = {urn:nbn:de:hbz:82-rwth-2015-036823},
      url          = {https://publications.rwth-aachen.de/record/480454},
}