393 research outputs found
Wireless Information Transfer with Opportunistic Energy Harvesting
Energy harvesting is a promising solution to prolong the operation of
energy-constrained wireless networks. In particular, scavenging energy from
ambient radio signals, namely wireless energy harvesting (WEH), has recently
drawn significant attention. In this paper, we consider a point-to-point
wireless link over the narrowband flat-fading channel subject to time-varying
co-channel interference. It is assumed that the receiver has no fixed power
supplies and thus needs to replenish energy opportunistically via WEH from the
unintended interference and/or the intended signal sent by the transmitter. We
further assume a single-antenna receiver that can only decode information or
harvest energy at any time due to the practical circuit limitation. Therefore,
it is important to investigate when the receiver should switch between the two
modes of information decoding (ID) and energy harvesting (EH), based on the
instantaneous channel and interference condition. In this paper, we derive the
optimal mode switching rule at the receiver to achieve various trade-offs
between wireless information transfer and energy harvesting. Specifically, we
determine the minimum transmission outage probability for delay-limited
information transfer and the maximum ergodic capacity for no-delay-limited
information transfer versus the maximum average energy harvested at the
receiver, which are characterized by the boundary of so-called "outage-energy"
region and "rate-energy" region, respectively. Moreover, for the case when the
channel state information (CSI) is known at the transmitter, we investigate the
joint optimization of transmit power control, information and energy transfer
scheduling, and the receiver's mode switching. Our results provide useful
guidelines for the efficient design of emerging wireless communication systems
powered by opportunistic WEH.Comment: to appear in IEEE Transactions on Wireless Communicatio
Queueing analysis of opportunistic scheduling with spatially correlated channels
International audienc
Delay Considerations for Opportunistic Scheduling in Broadcast Fading Channels
We consider a single-antenna broadcast block fading
channel with n users where the transmission is packetbased.
We define the (packet) delay as the minimum number of channel uses that guarantees all n users successfully receive m packets. This is a more stringent notion of delay than average delay and is the worst case (access) delay among the users. A delay optimal scheduling scheme, such as round-robin, achieves the delay of mn. For the opportunistic scheduling (which is throughput optimal) where the transmitter sends the packet to the user with the best channel conditions at each channel use, we derive the mean and variance of the delay for any m and n. For large n and in a homogeneous network, it is proved that the expected delay in receiving one packet by all the receivers scales as n log n, as opposed to n for the round-robin scheduling. We also show that when m grows faster than (log n)^r, for some r > 1, then the delay scales as mn. This roughly determines the timescale required for the system to behave fairly in a homogeneous network. We then propose a scheme to significantly reduce the delay at the expense of a small throughput hit. We further look into the advantage of multiple transmit antennas on the delay. For a system with M antennas in the transmitter where at each channel use packets are sent to M different users, we obtain the expected delay in receiving one packet by all the users
Selective Fair Scheduling over Fading Channels
Imposing fairness in resource allocation incurs a loss of system throughput,
known as the Price of Fairness (). In wireless scheduling, increases
when serving users with very poor channel quality because the scheduler wastes
resources trying to be fair. This paper proposes a novel resource allocation
framework to rigorously address this issue. We introduce selective fairness:
being fair only to selected users, and improving by momentarily blocking
the rest. We study the associated admission control problem of finding the user
selection that minimizes subject to selective fairness, and show that
this combinatorial problem can be solved efficiently if the feasibility set
satisfies a condition; in our model it suffices that the wireless channels are
stochastically dominated. Exploiting selective fairness, we design a stochastic
framework where we minimize subject to an SLA, which ensures that an
ergodic subscriber is served frequently enough. In this context, we propose an
online policy that combines the drift-plus-penalty technique with
Gradient-Based Scheduling experts, and we prove it achieves the optimal .
Simulations show that our intelligent blocking outperforms by 40 in
throughput previous approaches which satisfy the SLA by blocking low-SNR users
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