324 research outputs found
Multiuser Scheduling in a Markov-modeled Downlink using Randomly Delayed ARQ Feedback
We focus on the downlink of a cellular system, which corresponds to the bulk
of the data transfer in such wireless systems. We address the problem of
opportunistic multiuser scheduling under imperfect channel state information,
by exploiting the memory inherent in the channel. In our setting, the channel
between the base station and each user is modeled by a two-state Markov chain
and the scheduled user sends back an ARQ feedback signal that arrives at the
scheduler with a random delay that is i.i.d across users and time. The
scheduler indirectly estimates the channel via accumulated delayed-ARQ feedback
and uses this information to make scheduling decisions. We formulate a
throughput maximization problem as a partially observable Markov decision
process (POMDP). For the case of two users in the system, we show that a greedy
policy is sum throughput optimal for any distribution on the ARQ feedback
delay. For the case of more than two users, we prove that the greedy policy is
suboptimal and demonstrate, via numerical studies, that it has near optimal
performance. We show that the greedy policy can be implemented by a simple
algorithm that does not require the statistics of the underlying Markov channel
or the ARQ feedback delay, thus making it robust against errors in system
parameter estimation. Establishing an equivalence between the two-user system
and a genie-aided system, we obtain a simple closed form expression for the sum
capacity of the Markov-modeled downlink. We further derive inner and outer
bounds on the capacity region of the Markov-modeled downlink and tighten these
bounds for special cases of the system parameters.Comment: Contains 22 pages, 6 figures and 8 tables; revised version including
additional analytical and numerical results; work submitted, Feb 2010, to
IEEE Transactions on Information Theory, revised April 2011; authors can be
reached at [email protected]/[email protected]/[email protected]
Scheduling of Multicast and Unicast Services under Limited Feedback by using Rateless Codes
Many opportunistic scheduling techniques are impractical because they require
accurate channel state information (CSI) at the transmitter. In this paper, we
investigate the scheduling of unicast and multicast services in a downlink
network with a very limited amount of feedback information. Specifically,
unicast users send imperfect (or no) CSI and infrequent acknowledgements (ACKs)
to a base station, and multicast users only report infrequent ACKs to avoid
feedback implosion. We consider the use of physical-layer rateless codes, which
not only combats channel uncertainty, but also reduces the overhead of ACK
feedback. A joint scheduling and power allocation scheme is developed to
realize multiuser diversity gain for unicast service and multicast gain for
multicast service. We prove that our scheme achieves a near-optimal throughput
region. Our simulation results show that our scheme significantly improves the
network throughput over schemes employing fixed-rate codes or using only
unicast communications
Resource management in QoS-aware wireless cellular networks
2011 Summer.Includes bibliographical references.Emerging broadband wireless networks that support high speed packet data with heterogeneous quality of service (QoS) requirements demand more flexible and efficient use of the scarce spectral resource. Opportunistic scheduling exploits the time-varying, location-dependent channel conditions to achieve multiuser diversity. In this work, we study two types of resource allocation problems in QoS-aware wireless cellular networks. First, we develop a rigorous framework to study opportunistic scheduling in multiuser OFDM systems. We derive optimal opportunistic scheduling policies under three common QoS/fairness constraints for multiuser OFDM systems--temporal fairness, utilitarian fairness, and minimum-performance guarantees. To implement these optimal policies efficiently, we provide a modified Hungarian algorithm and a simple suboptimal algorithm. We then propose a generalized opportunistic scheduling framework that incorporates multiple mixed QoS/fairness constraints, including providing both lower and upper bound constraints. Next, taking input queues and channel memory into consideration, we reformulate the transmission scheduling problem as a new class of Markov decision processes (MDPs) with fairness constraints. We investigate the throughput maximization and the delay minimization problems in this context. We study two categories of fairness constraints, namely temporal fairness and utilitarian fairness. We consider two criteria: infinite horizon expected total discounted reward and expected average reward. We derive and prove explicit dynamic programming equations for the above constrained MDPs, and characterize optimal scheduling policies based on those equations. An attractive feature of our proposed schemes is that they can easily be extended to fit different objective functions and other fairness measures. Although we only focus on uplink scheduling, the scheme is equally applicable to the downlink case. Furthermore, we develop an efficient approximation method--temporal fair rollout--to reduce the computational cost
A Framework for Uplink Intercell Interference Modeling with Channel-Based Scheduling
This paper presents a novel framework for modeling the uplink intercell
interference (ICI) in a multiuser cellular network. The proposed framework
assists in quantifying the impact of various fading channel models and
state-of-the-art scheduling schemes on the uplink ICI. Firstly, we derive a
semianalytical expression for the distribution of the location of the scheduled
user in a given cell considering a wide range of scheduling schemes. Based on
this, we derive the distribution and moment generating function (MGF) of the
uplink ICI considering a single interfering cell. Consequently, we determine
the MGF of the cumulative ICI observed from all interfering cells and derive
explicit MGF expressions for three typical fading models. Finally, we utilize
the obtained expressions to evaluate important network performance metrics such
as the outage probability, ergodic capacity, and average fairness numerically.
Monte-Carlo simulation results are provided to demonstrate the efficacy of the
derived analytical expressions.Comment: IEEE Transactions on Wireless Communications, 2013. arXiv admin note:
substantial text overlap with arXiv:1206.229
Per-user service model for opportunistic scheduling scheme over fading channels
In this paper, we propose a ¯nite-state Markov model for per-user service of an oppor- tunistic scheduling scheme over Rayleigh fading channels, where a single base station serves an arbitrary number of users. By approximating the power gain of Rayleigh fading chan- nels as ¯nite-state Markov processes, we develop an algorithm to obtain dynamic stochastic model of the transmission service, received by an individual user for a saturated scenario, where user data queues are highly loaded. The proposed analytical model is a ¯nite-state Markov process. We provide a comprehensive comparison between the predicted results by the proposed analytical model and the simulation results, which demonstrate a high degree of match between the two sets
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