Cross-Layer Rate and Power Adaptation Strategies for IR-HARQ Systems over Fading Channels with Memory: A SMDP-Based Approach

Incremental-redundancy hybrid automatic repeatrequest (IR-HARQ) schemes are proposed in several wireless standards for increased throughput-efficiency and greater reliability. We investigate transmit power and modulation order adaptation strategies for the IR-HARQ schemes over correlated Rayleigh fading channels using semi-Markov decision processbased model. In order to jointly analyze physical layer and link layer, transmitter model incorporates a finite-size buffer that receives randomly varying traffic from a higher layer application. It is assumed that channel variations can be modeled with a firstorder Markov chain. We show that the optimal transmission power and rate adaptation laws under buffering delay and packet overflow constraints can be obtained using the framework of semi-Markov decision process. We discuss three different adaptation models for the IR-HARQ schemes and compare their performances with the non-adaptive scheme. It is shown that unique optimal policy exists for each case and it can be computed using linear programming approach. This optimal policy is then applied for realistic channel fading and incoming traffic samples to evaluate its performance for both hard-decision and softdecision decoding. Simulation results in general point out that substantial power savings can be achieved using adaptation and also if the transmission-delay requirements are relaxed.     

Multifaceted potentials of tire-derived three dimensional geosynthetics in geotechnical applications and their evaluation

Scrapped tire-derived materials, such as tire chips and tire shreds, can be categorized as three dimensional geosynthetics. This paper introduces recent Japanese experience in geotechnical related applications of geosynthetics that focus mainly on tire chips and tire shreds. Three specific applications of tire chips and tire shreds are introduced here. They are: (1) tire shreds to improve drainage; (2) sand-mixed tire chips to mitigate earthquake damage; and (3) tire chips mixed with cement-treated clay to improve toughness and ductility. The developed techniques related to these applications, verification through model testing, as well as element testing and the field applications are presented. It was observed that tire shreds can maintain high permeability even under a high compressive load. When tire chips and/or sand-mixed tire chips are used as a compressible cushion, not only the dynamic load against a structure but also the dynamically induced permanent structural displacement could also be significantly reduced. On the other hand, mixing tire chips with cement-treated clay gives toughness to the geomaterial, and thus provides resistance against the development of cracks during deformation. In addition, an X-ray CT investigation of deformation behavior of such materials demonstrated the success of using cement-treated clay with tire chips as a sealing material to protect leakage of contaminated materials at a waste disposal site in Tokyo bay area.     

POMDP-Based Coding Rate Adaptation for Type-I Hybrid ARQ Systems over Fading Channels with Memory

We address the issue of optimal coding rate scheduling for adaptive type-I hybrid automatic repeat request wireless systems. In this scheme, the coding rate is varied depending on channel, buffer and incoming traffic conditions. In general, we consider the hidden Markov model for both time-varying flat fading channel and bursty correlated incoming traffic. It is shown that the appropriate framework for computing the optimal coding rate allocation policies is partially observable Markov decision process (POMDP). In this framework, the optimal coding rate allocation policy maximizes the reward function, which is a weighted sum of throughput and buffer occupancy with appropriate sign. Since polynomial amount of space is needed to calculate the optimal policy even for a simple POMDP problem, we investigate maximum-likelihood, voting and Q-MDP policy heuristic approaches for the purpose of efficient and real-time solution. Our results show that three heuristics perform close to completely observable system state case if the fading and/or traffic state mixing rate is slow. On the other hand, when the channel fading is fast, Q-MDP heuristic is the most throughput-efficient among considered heuristics. Also, its performance is close to the optimal coding rate allocation policy of fully observable system state case. We also explore the performances of the proposed heuristics in the bursty correlated traffic case and show that maximum-likelihood and voting heuristics consistently outperform the non-adaptive case     

Optimal and suboptimal packet scheduling over correlated time varying flat fading channels

We address the issue of optimal packet scheduling over correlated fading channels which trades off between minimization of three goals: average transmission power, average delay and average packet dropping probability. We show that the problem forms a weakly communicating Markov decision process and formulate the problem as both unconstrained and constrained problem. Relative value iteration (RVI) algorithm is used to find optimal deterministic policy for unconstrained problem, while optimal randomized policy for constrained problem is obtained using linear programming (LP) technique. Whereas with RVI only a finite number of scheduling policies can be obtained over the feasible delay region, LP can produce policies for all feasible delays with a fixed dropping probability and is computationally faster than the RVI. We show the structure of optimal deterministic policy in terms of the channel and buffer state and form a simple log functional suboptimal scheduler that approximately follows the optimal structure. Performance results are given for both constant and bursty Poisson arrivals, and the proposed suboptimal scheduler is compared with the optimal and channel threshold scheduler. Our suboptimal scheduler performs close to the optimal scheduler for every feasible delay and is robust to different channel parameters, number of actions and incoming traffic distributions.