Optimal Transmission Policies for Noisy Channels

IEEE Transactions on Wireless Communications, 2000

Wireless networks, as an indispensable part of the Internet, are expected to support diverse quality of service requirements and traffic characteristics. This paper presents stochastic performance analysis of a wireless network with finite-state Markov channel (FSMC). The analysis is based on stochastic network calculus. Specifically, the analytical principle behind stochastic network calculus is first presented. Then, based on this principle, delay and backlog upper bounds are derived. Both the single user case and the multi-user case are considered. For the multi-user case, two channel sharing methods among eligible users are studied, which are the even sharing method and the exclusive use method. In the former, the channel service rate is evenly divided among eligible users; in the latter, it is exclusively used by a user randomly selected from the eligible users. When the even sharing method is studied, the problem that the state space is exponentially increased with the user number is addressed through a novel approach. The essential idea of this approach is to construct a new Markov modulation process from the channel state process. In the new process, the multi-user effects are equivalently reflected by its transition and steady-state probabilities and the state space size is kept unchanged even with the increase of the user number, which significantly reduces the complexity in calculating the obtained backlog and delay bounds. Finally, the proposed analytical principle and methods are validated through comparison between analytical and simulation results.

This paper investigates the benefits of cooperation in large wireless networks with multiple sources and relays, where the nodes form an homogeneous Poisson point process. The source nodes may dispose of their nearest neighbor from the set of inactive nodes as their relay. Although cooperation can potentially lead to significant improvements on the asymptotic error probability of a communication pair, relaying causes additional interference in the network, increasing the average noise. We address the basic question: how should source nodes optimally balance cooperation vs. interference to guarantee reliability in all communication pairs. Based on the decode-and-forward (DF) scheme at the relays (which is near optimal when the relays are close to their corresponding sources), we derive closed-form approximations to the upper bounds on the error probability, averaging over all node positions. Surprisingly, in the small node-density regime, there is an almost binary behavior that dictates -depending on network parametersthe activation or not of all relay nodes.

Theory of Probability & Its Applications, 2006

The paper concerns both controlled diffusion processes, and processes in discrete time. We establish conditions under which the strategy minimizing the expected value of a cost functional has a much stronger property; namely, it minimizes the random cost functional itself for all realizations of the controlled process from a set, the probability of which is close to one for large time horizons. The main difference of the conditions mentioned from those obtained earlier is that the former do not deal with strategies optimal in the mean themselves but concern a possibility of transition of the controlled process from one state to another in a time with a finite expectation. It makes the verification of these conditions in a number of situations much easier.

2004

In this paper we consider the problem of joint optimal power and admission control for a single user queue. The user may be in a finite set of channel fading states, each of which corresponds to a certain power-rate function. The user may choose a particular transmission power level and incur a cost that increases with the power. Packets arrive at the queue as a Poisson process with a constant rate. The user may choose a dropping probability for the incoming packet, which incurs a cost that increases with the dropping probability. Packets remaining in the queue also incur a holding cost. The goal is for the user to choose optimally its transmission power/rate and its admission rate so as to minimize the sum of the above costs. These costs model the tradeoff between increasing transmission power, increasing packet delay, and dropping a packet. In this paper we investigate a number of monotonicity properties of the optimal solution to the above problem. Specifically we prove the following results under an optimal strategy: (1) The output or transmission rate of a queue does not decrease and the acceptance rate does not increase as the queue size increases; (2) The output rate does not decrease and the acceptance rate does not increase as the time horizon (or steps to go) increases; (3) For a fixed transmission rate, we show that the acceptance rate does not increase as the system enters a worse fading state; (4) Under certain conditions on the arrival and maximum transmission rates, we show that the output rate does not increase as the system enters a worse fading state. These results provide good insight on the structure of the problem.

2009

We consider finite number of users, with infinite buffer storage, sharing a single channel using the aloha medium access protocol. This is an interesting example of a non saturated collision channel. We investigate the uplink case of a cellular system where each user will select a desired throughput. The users then participate in a non cooperative game wherein they adjust their transmit rate to attain their desired throughput. We show that this game, in contrast to the saturated case, either has no Nash Equilibrium or has infinitely many Nash Equilibria. Further, we show that the region of NE coincides with an appropriate 'stability region'. We also discuss the efficiency of the equilibria in term of energy consumption and congestion rate. Next, we propose two learning algorithms using a stochastic iterative procedure that converges to the best Nash equilibrium. For instance, the first one needs partial information (transmit rates of other users during the last slot) whereas the second is an information less and fully distributed scheme. We approximate the control iterations by an equivalent ordinary differential equation in order to prove that the proposed stochastic learning algorithm converges to a Nash equilibrium even in the absence of any coordination or extra information. Extensive numerical examples and simulations are provided to validate our results.

2015 Twenty First National Conference on Communications (NCC), 2015

We consider a wireless channel shared by multiple transmitter-receiver pairs. Their transmissions interfere with each other. Each transmitter-receiver pair aims to maximize its long-term average transmission rate subject to an average power constraint. This scenario is modeled as a stochastic game. We provide sufficient conditions for existence and uniqueness of a Nash equilibrium (NE). We then formulate the problem of finding NE as a variational inequality (VI) problem and present an algorithm to solve the VI using regularization. We also provide distributed algorithms to compute Pareto optimal solutions for the proposed game.

2017

This paper dedicates to exploring and exploiting the hidden resource in wireless channel. We discover that the stochastic dependence in wireless channel capacity is a hidden resource, specifically, if the wireless channel capacity bears negative dependence, the wireless channel attains a better performance with a smaller capacity. We find that the dependence in wireless channel is determined by both uncontrollable and controllable parameters in the wireless system, by inducing negative dependence through the controllable parameters, we achieve dependence control. We model the wireless channel capacity as a Markov additive process, i.e., an additive process defined on a Markov process, and we use copula to represent the dependence structure of the underlying Markov process. Based on a priori information of the temporal dependence of the uncontrollable parameters and the spatial dependence between the uncontrollable and controllable parameters, we construct a sequence of temporal copu...

This project aims to deal with less reliability of nodes in a wireless network, and study behaviour of each nodes in a dynamic fashion by splitting into pre-defined number of packets and attaching an information with each packet to study the link quality once it reaches the destination, how the data is broadcasted in the network and uses a storage for packet information and once there is a node failure it studies why the failure occurs if due to a technical failure or incapacity of sever to process the request or the client to receive the data it is analysed and resend or if a deliberate rejection from client or some middle man acquiring packets or destination ip and the receivers ip don't match it drops the node and uses optimal grouping to decide the next best linking if a node is dropped to achieve the best throughput rather than a random selection of link and in turn making it very inefficient even for a small round-trip.

2005

We derive outage expressions and throughput bounds for wireless networks subject to different sources of nondeterminism. The degree of uncertainty is characterized by the location of the network in the uncertainty cube whose three axes represent the three main sources of uncertainty in interferencelimited networks: the node distribution, the channel gains, and the channel access. The range for the coordinates is [0,1], where 0 indicates complete determinism, and 1 a maximum degree of randomness (nodes distributed in a Poisson point process, fading with fading figure 1, and ALOHA channel access, respectively).

IEEE GLOBECOM 2007-2007 IEEE Global Telecommunications Conference, 2007

Page 1. Constrained Stochastic Games in Wireless Networks Eitan Altman ∗ ‡ , Konstantin Avratchenkov ∗ , Nicolas Bonneau ∗ † , Mérouane Debbah † , Rachid El-Azouzi ‡ , Daniel Sadoc Menasché § ∗ INRIA, Centre Sophia ...