- Exploiting Channel Memory for Wireless Scheduling with Limited Channel Probing: An Asymptotic Study
Paolo Giaccone (Politecnico di Torino, Italy); Emilio Leonardi (Politecnico di Torino, Italy)
We consider a wireless downlink communication system with N parallel channels under the following two assumptions: (1) the channels states can be explicitly sensed at a limited rate λ_s, (2) channels are modeled as i.i.d., ON/OFF Markov chains with stationary distribution [π_OFF , π_ON]. The goal of this paper is to characterize the fundamental trade-off between system throughput and channel sensing rate λ_s in the challenging scenario in which N → ∞ and jointly π_ON → 0. To this end, we propose a simple scheduling algorithm that effectively exploits channel memory to maximize the successful transmission probability. We obtain sufficient and necessary conditions to achieve maximum (in order sense) system throughput. Finally, we show the performance of our policy under a non-asymptotic scenario.
- XOR-based Coding for the 3-user Broadcast Erasure Channel with Feedback
Sophia A. Athanasiadou (Aristotle University of Thessaloniki, Greece); Marios Gatzianas (Center for Research and Technology Hellas, Telematics and Informatics Institute, Greece); Leonidas Georgiadis (Aristotle University of Thessaloniki, Greece); Leandros Tassiulas (University of Thessaly, Greece)
We study the case of the three-user broadcast erasure channel, with multiple unicast traffic, where feedback from the users is fed back to the transmitter in the form of ACK/NACK messages. We propose two coding algorithms, named XOR1 and XOR2, which operate on a specially constructed network of virtual queues. XOR2 is more sophisticated than XOR1 but achieves a known capacity outer bound in the following settings 1) spatially i.i.d. erasures for all values of erasure probability and 2) spatially independent erasures where the maximum erasure probability does not exceed 8/9. The algorithms rely only on simple XOR operations between packets, allow instantaneous decoding and require no knowledge of channel statistics.
- Energy Efficient Routing with Mutual Information Accumulation
Tolga Girici (TOBB Economics and Technology University, Turkey); Ahmet Kazez (TOBB Economics and Technology University, Turkey)
We consider minimum-energy routing in a wireless network. We assume the use of ideal rateless codes, so that a node can accumulate transmission rates from the transmission of previous nodes on the routing path. Mutual information accumulation has significant advantages when compared with classical0 cooperative schemes that use energy accumulation. However, the resource allocation problem becomes more complex, as it involves the determination of 1) Routing path, 2) Transmission duration of each node, and 3) Transmission power of each node. We formulated the problem as an optimization problem, where the objective function is the total energy expenditure and the constraints are minimum mutual information for each node and the maximum total transmission time. The joint power/time optimization problem has a biconvex nature, which admits coordinate-descent type of solutions. The optimal routing path is found using a branch-and-bound technique. The energy gains are measured by comparison with a simple routing and resource allocation scheme.
- Network Cooperation for Client-AP Association Optimization
Akash Baid (WINLAB, Rutgers University, USA); Michael Schapira (Hebrew University of Jerusalem, USA); Ivan Seskar (Rutgers University, USA); Jennifer Rexford (Princeton University, USA); Dipankar Raychaudhuri (Rutgers University, USA)
Optimization of client-AP association pattern has been shown to improve load balancing and user throughput in multi-AP enterprise/hot-spot WiFi deployments. In this paper, we propose and evaluate a cooperation scheme between two or more such overlapping hot-spot networks that incorporates inter-network interference in the client-AP association optimization problem. We model the effects of multiple overlapping WiFi deployments, determine the information that networks need to share and formulate a non-linear program that each network can solve for proportional fair optimal client-AP association. Assuming a sum of log rates utility function, we reuse a known 2 + ϵ approximation algorithm for solving the NP-hard problem in polynomial time. We evaluate the performance gain through large scale simulations with 2-4 overlapping networks, each consisting of 15-35 access points(APs) and 50-250 users in a 0.5x0.5 sq.km. urban setting. Results show an average of 150% improvement in the 10 percentile client throughputs with modest reductions in the mean throughputs