Mathematical modeling of rayleigh fading channels based on finite state markov chains

Park, Jae Man; Hwang, Gang Uk

doi:10.1109/lcomm.2009.090635

Cited by 38 publications

(33 citation statements)

References 3 publications

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“…The proposed model is aimed at fading channels that satisfy Markovian assumption. Commonly used channel fading models such as Rayleigh fading and the resultant exponential SNR distribution, can be represented as finite state Markov chains (FSMC) [48]- [50]. One method involved is to partition the fading coefficients value range such that, the duration spent in each state is the same, say τ.…”

Section: ) Markovian Representation Of Fading Channelsmentioning

confidence: 99%

Sequential Decision Making With Limited Observation Capability: Application to Wireless Networks

Kaza

Meshram

Mehta

et al. 2019

IEEE Trans. Cogn. Commun. Netw.

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This work studies a generalized class of restless multi-armed bandits with hidden states and allow cumulative feedback, as opposed to the conventional instantaneous feedback. We call them lazy restless bandits (LRB) as the events of decisionmaking are sparser than events of state transition. Hence, feedback after each decision event is the cumulative effect of the following state transition events. The states of arms are hidden from the decision-maker and rewards for actions are state dependent. The decision-maker needs to choose one arm in each decision interval, such that long term cumulative reward is maximized.As the states are hidden, the decision-maker maintains and updates its belief about them. It is shown that LRBs admit an optimal policy which has threshold structure in belief space. The Whittle-index policy for solving LRB problem is analyzed; indexability of LRBs is shown. Further, closed-form index expressions are provided for two sets of special cases; for more general cases, an algorithm for index computation is provided. An extensive simulation study is presented; Whittle-index, modified Whittleindex and myopic policies are compared. Lagrangian relaxation of the problem provides an upper bound on the optimal value function; it is used to assess the degree of sub-optimality various policies.

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Section: ) Markovian Representation Of Fading Channelsmentioning

confidence: 99%

Sequential Decision Making With Limited Observation Capability: Application to Wireless Networks

Kaza

Meshram

Mehta

et al. 2019

IEEE Trans. Cogn. Commun. Netw.

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“…By partitioning the range of the received signal-to-noise ratio (SNR) into a finite number of intervals, finite-state Markov channel models can be constructed for Rayleigh fading channels, for example, by using the methods from [24,25] or [26]. Thus, a radio channel can be represented by a Markov model with multiple states, which represent situations when the channel exhibits signal-to-noise ratios belonging to one of the chosen intervals.…”

Section: Radio Frequency Channelmentioning

confidence: 99%

“…We assume that the bit error rate in a state can be approximated to be the average bit error rate in that state as was done, for example, in [18,25]. Also, we assume that there are only transitions between two adjacent states, which represent adjacent ranges of the signal-to-noise ratio, as was done in [24][25][26] (see Figure 1). …”

Section: Radio Frequency Channelmentioning

confidence: 99%

“…The probability density function from (1) is the same as that of the SNR of Rayleigh fading channels representing RF channels [24][25][26], which is ( ) = (1/ ) exp(− / 0 ), for ≥ 0, where is the SNR and 0 is the average SNR. We therefore believe that, similar to the partitioning of the ranges of SNR for Rayleigh fading channels, it may be possible to meaningfully partition the range of possible irradiance values into separate ranges and to set up a Markov process corresponding to these ranges.…”

Section: Fso Channel Modelmentioning

confidence: 99%

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Availability of a Hybrid FSO/RF Link While Using the Link’s Diversity for Packet Scheduling

Grigoriu

2018

Wireless Communications and Mobile Computing

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Hybrid-free space optical and radio frequency wireless links are a way of providing reliable transport of real-time traffic in outdoor wireless environments. We consider a link layer protocol that assigns packets to each physical channel of such a hybrid link, which first attempts to send each packet over one of the links (the main link) and, if unsuccessful, sends the packet over the other link (the backup link). The hybrid link processes high-priority traffic by using the link layer protocol and additional (background) traffic at low priority over the backup link. In this setting, high-priority traffic can be transmitted at a rate as high as the maximum capacity of the main link, assuming that the backup link can compensate for main link capacity deterioration, with no need for reconfigurations aimed at adapting to changes in weather conditions, which is an advantage over other approaches. From the perspective of link availability for high-priority traffic, we compare our approach to using another protocol that does not require reconfigurations, which could be employed if the backup link is expected to have a constant transmission rate during the time interval of interest. For situations where both links can be represented by finite-state Markov models with states corresponding to channel bit error rates, as has been done in previous literature for radio frequency links and for free space optical links affected by strong atmospheric turbulence and Gaussian noise, we give a way to provide probabilistic quality of service guarantees for background traffic assuming that the high-priority traffic is insured to not exceed a given constant rate.

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“…In this section, the procedure for determining the transition probabilities for a Markov model of a Nakagami-m fading model is presented based on approached outlined in [11,12,13,14]. The transition probability of the Nakagami-m fading channel can be computed using the conditional probability, p(x|y) (eqn.…”

Section: State Transition Probabilitymentioning

confidence: 99%

Intermittent communications modeling and simulation for autonomous unmanned maritime vehicles using an integrated APM and FSMC framework

Coker¹,

Straatemeier²,

Rogers³

et al. 2014

SPIE Proceedings

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In this work a framework is presented for addressing the issue of intermittent communications faced by autonomous unmanned maritime vehicles operating at sea. In particular, this work considers the subject of predictive atmospheric signal transmission over multi-path fading channels in maritime environments. A Finite State Markov Channel is used to represent a Nakagami-m modeled physical fading radio channel. The range of the received signal-to-noise ratio is partitioned into a finite number of intervals which represent application-specific communications states. The Advanced Propagation Model (APM), developed at the Space and Naval Warfare Systems Center San Diego, provides a characterization of the transmission channel in terms of evaporation duct induced signal propagation loss. APM uses a hybrid ray-optic and parabolic equations model which allows for the computation of electromagnetic (EM) wave propagation over various sea and/or terrain paths. These models which have been integrated in the proposed framework provide a strategic and mission planning aid for the operation of maritime unmanned vehicles at sea.

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Mathematical modeling of rayleigh fading channels based on finite state markov chains

Cited by 38 publications

References 3 publications

Sequential Decision Making With Limited Observation Capability: Application to Wireless Networks

Sequential Decision Making With Limited Observation Capability: Application to Wireless Networks

Availability of a Hybrid FSO/RF Link While Using the Link’s Diversity for Packet Scheduling

Intermittent communications modeling and simulation for autonomous unmanned maritime vehicles using an integrated APM and FSMC framework

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