17 research outputs found
Distributed Opportunistic Scheduling For Ad-Hoc Communications Under Noisy Channel Estimation
Distributed opportunistic scheduling is studied for wireless ad-hoc networks,
where many links contend for one channel using random access. In such networks,
distributed opportunistic scheduling (DOS) involves a process of joint channel
probing and distributed scheduling. It has been shown that under perfect
channel estimation, the optimal DOS for maximizing the network throughput is a
pure threshold policy. In this paper, this formalism is generalized to explore
DOS under noisy channel estimation, where the transmission rate needs to be
backed off from the estimated rate to reduce the outage. It is shown that the
optimal scheduling policy remains to be threshold-based, and that the rate
threshold turns out to be a function of the variance of the estimation error
and be a functional of the backoff rate function. Since the optimal backoff
rate is intractable, a suboptimal linear backoff scheme that backs off the
estimated signal-to-noise ratio (SNR) and hence the rate is proposed. The
corresponding optimal backoff ratio and rate threshold can be obtained via an
iterative algorithm. Finally, simulation results are provided to illustrate the
tradeoff caused by increasing training time to improve channel estimation at
the cost of probing efficiency.Comment: Proceedings of the 2008 IEEE International Conference on
Communications, Beijing, May 19-23, 200
Distributed Opportunistic Scheduling for MIMO Ad-Hoc Networks
Distributed opportunistic scheduling (DOS) protocols are proposed for
multiple-input multiple-output (MIMO) ad-hoc networks with contention-based
medium access. The proposed scheduling protocols distinguish themselves from
other existing works by their explicit design for system throughput improvement
through exploiting spatial multiplexing and diversity in a {\em distributed}
manner. As a result, multiple links can be scheduled to simultaneously transmit
over the spatial channels formed by transmit/receiver antennas. Taking into
account the tradeoff between feedback requirements and system throughput, we
propose and compare protocols with different levels of feedback information.
Furthermore, in contrast to the conventional random access protocols that
ignore the physical channel conditions of contending links, the proposed
protocols implement a pure threshold policy derived from optimal stopping
theory, i.e. only links with threshold-exceeding channel conditions are allowed
for data transmission. Simulation results confirm that the proposed protocols
can achieve impressive throughput performance by exploiting spatial
multiplexing and diversity.Comment: Proceedings of the 2008 IEEE International Conference on
Communications, Beijing, May 19-23, 200
Almost sure consensus for multi-agent systems with two level switching
In most literatures on the consensus of multi-agent systems (MASs), the agents considered are time-invariant. However in many cases, for example in airplane formation, the agents have switching dynamics and the connections between them are also changing. This is called two-level switching in this paper. We study almost sure (AS) consensus for a class of two-level switching systems. At the low level of agent dynamics, switching is determin- istic and controllable. The upper level topology switching is random and follows a Markov chain. The transition probability of the Markov chain is not fixed, but varies when low level dynamics changes. For this class of MASs, a sufficient condition for AS consensus is developed in this paper
Distributed opportunistic scheduling for ad-hoc communications: An optimal stopping approach
Abstract — We study distributed opportunistic scheduling (DOS) in an ad-hoc network, where many links contend for the same channel using random access. In such a network, DOS involves a process of joint channel probing and distributed scheduling. Due to channel fading, the link condition corresponding to a successful channel probing could be either good or poor. In the latter case, further channel probing, although at the cost of additional delay, may lead to better channel conditions and hence yield higher throughput. The desired tradeoff boils down to judiciously choosing the optimal stopping rule for channel probing and distributed scheduling. In this paper, we pursue a rigorous characterization of the optimal strategies from two perspectives, namely, a network-centric perspective and a usercentric perspective. We first consider DOS from a network-centric point o