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]

The temporal value of information to network protocols: an analytical framework

Network protocol performance is closely related to the available information about the network state. However, acquiring such information expends network bandwidth resource. Thus a trade-off exists between the amount of information collected about the network state, and the improved protocol performance due to this information. A framework has been developed to study the optimal trade-off between the amount of collected information and network performance. However, the effect of information delay is not considered. In this paper, we extend the framework to study the impact of information delay on the value of network state information to network protocols, based on which optimal periodic information update policies could be obtained. The framework is illustrated by an example of multiuser scheduling, and observations about the impact of information delay on network protocols are obtained. © 2015 IEEE.postprin

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

Exploiting channel memory for joint estimation and scheduling in downlink networks

We address the problem of opportunistic multiuser scheduling in downlink networks with Markov-modeled outage channels. We consider the scenario in which the scheduler does not have full knowledge of the channel state information, but instead estimates the channel state information by exploiting the memory inherent in the Markov channels along with ARQ-styled feedback from the scheduled users. Opportunistic scheduling is optimized in two stages: (1) Channel estimation and rate adaptation to maximize the expected immediate rate of the scheduled user; (2) User scheduling, based on the optimized immediate rate, to maximize the overall long term sum-throughput of the downlink. The scheduling problem is a partially observable Markov decision process with the classic ‘exploitation vs exploration ’ trade-off that is difficult to quantify. We therefore study the problem in the framework of restless multi-armed bandit processes and perform a Whit-tle’s indexability analysis. Whittle’s indexability is traditionally known to be hard to establish and the index policy derived based on Whittle’s indexability is known to have optimality properties in various settings. We show that the problem of downlink scheduling under imperfect channel state information is Whittle indexable and derive the Whittle’s index policy in closed form. Via extensive numerical experiments, we show that the index policy has near-optimal performance. Our work reveals that, under incomplete channel state infor-mation, exploiting channel memory for opportunistic scheduling can result in significant performance gains and that almost all of these gains can be realized using an easy-to-implement index policy

Fairness-Adaptive Goodput-Based Resource Allocation in OFDMA Downlink with ARQ

We present a cross-layer resource-allocation (RA) scheme for the downlink in orthogonal frequency-division multiple-access (OFDMA) systems with fairness control among the users, where the resources to be allocated are power, bits per symbol, and subchannels. The use of subchannels, which are defined as group of subcarriers, leads to reducing the complexity of the bandwidth allocation compared with the commonly adopted subcarrier allocation. A goodput-based optimization function, which is derived by combining automatic repeat request (ARQ) and physical (PHY)-layer parameters, is used to perform RA for applications that demand error-free transmissions. Two transmission strategies are considered, with and without concatenation of subchannels, for which two different RA methods are developed, respectively. We also propose an algorithm that improves the complexity associated to both concatenation and nonconcatenation schemes, without appreciable performance loss.The work was supported by the GRE3N Project under Grant TEC2011-29006-C03-03.Publicad

Energy Efficient Reduced Complexity Multi-Service, Multi-Channel Scheduling Techniques

The need for energy efficient communications is essential in current and next-generation wireless communications systems. A large component of energy expenditure in mobile devices is in the mobile radio interface. Proper scheduling and resource allocation techniques that exploit instantaneous and long-term average knowledge of the channel, queue state and quality of service parameters can be used to improve the energy efficiency of communication. This thesis focuses on exploiting queue and channel state information as well as quality of service parameters in order to design energy efficient scheduling techniques. The proposed designs are for multi-stream, multi-channel systems and in general have high computational complexity. The large contributions of this thesis are in both the design of optimal/near-optimal scheduling/resource allocation schemes for these systems as well as proposing complexity reduction methods in their design. Methods are proposed for both a MIMO downlink system as well as an LTE uplink system. The effect of power efficiency on quality of service parameters is well studied as well as complexity/efficiency comparisons between optimal/near optimal allocation

Cross-layer design and optimization of medium access control protocols for wlans

This thesis provides a contribution to the field of Medium Access Control (MAC) layer protocol design for wireless networks by proposing and evaluating mechanisms that enhance different aspects of the network performance. These enhancements are achieved through the exchange of information between different layers of the traditional protocol stack, a concept known as Cross-Layer (CL) design. The main thesis contributions are divided into two parts. The first part of the thesis introduces a novel MAC layer protocol named Distributed Queuing Collision Avoidance (DQCA). DQCA behaves as a reservation scheme that ensures collision-free data transmissions at the majority of the time and switches automatically to an Aloha-like random access mechanism when the traffic load is low. DQCA can be enriched by more advanced scheduling algorithms based on a CL dialogue between the MAC and other protocol layers, to provide higher throughput and Quality of Service (QoS) guarantees. The second part of the thesis explores a different challenge in MAC layer design, related to the ability of multiple antenna systems to offer point-to-multipoint communications. Some modifications to the recently approved IEEE 802.11n standard are proposed in order to handle simultaneous multiuser downlink transmissions. A number of multiuser MAC schemes that handle channel access and scheduling issues and provide mechanisms for feedback acquisition have been presented and evaluated. The obtained performance enhancements have been demonstrated with the help of both theoretical analysis and simulation obtained results