7,395 research outputs found
Throughput Optimal Scheduling with Dynamic Channel Feedback
It is well known that opportunistic scheduling algorithms are throughput
optimal under full knowledge of channel and network conditions. However, these
algorithms achieve a hypothetical achievable rate region which does not take
into account the overhead associated with channel probing and feedback required
to obtain the full channel state information at every slot. We adopt a channel
probing model where fraction of time slot is consumed for acquiring the
channel state information (CSI) of a single channel. In this work, we design a
joint scheduling and channel probing algorithm named SDF by considering the
overhead of obtaining the channel state information. We first analytically
prove SDF algorithm can support fraction of of the full rate
region achieved when all users are probed where depends on the
expected number of users which are not probed. Then, for homogenous channel, we
show that when the number of users in the network is greater than 3, , i.e., we guarantee to expand the rate region. In addition, for
heterogenous channels, we prove the conditions under which SDF guarantees to
increase the rate region. We also demonstrate numerically in a realistic
simulation setting that this rate region can be achieved by probing only less
than 50% of all channels in a CDMA based cellular network utilizing high data
rate protocol under normal channel conditions.Comment: submitte
Energy-Efficient Resource Allocation Optimization for Multimedia Heterogeneous Cloud Radio Access Networks
The heterogeneous cloud radio access network (H-CRAN) is a promising paradigm
which incorporates the cloud computing into heterogeneous networks (HetNets),
thereby taking full advantage of cloud radio access networks (C-RANs) and
HetNets. Characterizing the cooperative beamforming with fronthaul capacity and
queue stability constraints is critical for multimedia applications to
improving energy efficiency (EE) in H-CRANs. An energy-efficient optimization
objective function with individual fronthaul capacity and inter-tier
interference constraints is presented in this paper for queue-aware multimedia
H-CRANs. To solve this non-convex objective function, a stochastic optimization
problem is reformulated by introducing the general Lyapunov optimization
framework. Under the Lyapunov framework, this optimization problem is
equivalent to an optimal network-wide cooperative beamformer design algorithm
with instantaneous power, average power and inter-tier interference
constraints, which can be regarded as the weighted sum EE maximization problem
and solved by a generalized weighted minimum mean square error approach. The
mathematical analysis and simulation results demonstrate that a tradeoff
between EE and queuing delay can be achieved, and this tradeoff strictly
depends on the fronthaul constraint
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