You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: Finite-state Markov modeling of fading channels - a survey of principles and applications 
Chapter Title:  FIRST-ORDER FSMC MODELS FOR THE TV-FFC 
1. Abstract of Cited Paper (BIB001):  The throughput performance of a wireless media access protocol taking into account the effect of correlated channel fading, capture, and propagation delay is analyzed. For efficient access on the uplink (mobile-to-base-station link), the protocol makes use of the uplink channel status information which is conveyed to the mobiles through a busy/idle flag broadcast on the downlink (base-station-to-mobile link). A first-order Markov model is used to describe the correlation in the packet success/failure process on a Rayleigh-fading channel. The analytical results obtained through the first-order Markov approximation of the channel are compared to those obtained from an independent and identically distributed (i.i.d.) channel model. The Markovian-fading channel model is shown to provide better performance results than the i.i.d. channel model. Simulations show that a first-order Markov approximation of the Rayleigh-fading process is quite accurate. An enhanced version of the access protocol to take advantage of the memory in the fading channel behavior is proposed and analyzed. The effect of retransmission of erroneous data packets and propagation delay on the throughput is also analyzed. It is shown that the access protocol with an error detect (ED) feature is efficient in slow fading (e.g., pedestrian user speeds), whereas a retransmission protocol is more efficient in fast fading (e.g., vehicular user speeds). 
2. Abstract of Cited Paper (BIB002):  A useful model for general time-varying channels is a finite state Markov chain. In this paper, maximum likelihood sequence estimation (MLSE) for signals over finite state Markov channels (FSMCs) is studied. Also studied is the maximum a posteriori (MAP) channel state estimation. When coded signals with interleaving are transmitted, the channel estimates can be used to make soft-decision decoding. The error performance of the proposed sequence and channel state estimation schemes are evaluated through computer simulations. The effect of channel modeling error is also discussed. 
3. Abstract of Cited Paper (BIB003):  The performance studies of wireless systems often require a wireless channel model. A common one, for Rayleigh fading environments, is founded upon variations of the finite state Markov channel model (FSMC). This model partitions the received signal to noise ratio (SNR) into a finite number of intervals and represents each interval as a state of a Markov process. Previous studies have elaborated on the accuracy and appropriateness of the model under several assumptions. A key aspect that remains to be studied is the effect of the partitioning scheme. We study the effects of several proposed schemes and investigate the performance of a new scheme that takes into account the average fade duration at various SNR levels. 
4. Abstract of Cited Paper (BIB004):  We propose a decision-feedback decoder for coded signals transmitted over finite-state Markov channels. The decoder achieves maximum-likelihood sequence detection (in the absence of feedback errors) with very low complexity by exploiting previous bit decisions and the Markov structure of the channel. We also propose a similar decoder, the output-feedback decoder, that does not use previous bit decisions and therefore does not suffer from error propagation. The decoder performance is determined using a new sliding window analysis technique as well as by simulation. Both decoders exhibit excellent bit error rate performance with a relatively low complexity that is independent of the channel decorrelation time. 
5. Abstract of Cited Paper (BIB005):  This paper introduces a novel and efficient method based on information theoretic metrics to evaluate the accuracy of the first-order Markov approximation for block errors in transmissions over fading channels. Numerical results show that our approach provides significant improvements in both accuracy and simplicity over previously proposed methods. 
6. Abstract of Cited Paper (BIB006):  We designed a multi-channel Nakagami fading simulator by modeling the received combined signal-to-noise ratio as a finite-state Markov chain, following a previously proposed approach. Our model generates directly the error process at the output of a diversity receiver and can emulate selection, maximal-ratio, and equal-gain combining. As the order of diversity increases, the savings in computational complexity improve linearly with respect to a traditional waveform simulator. The level crossing rates of the simulated envelope are shown to be very close to their theoretical values. The simulator's performance is also evaluated in terms of the accuracy of the obtained bit error rates, for both uncoded and coded systems. The simulator speeds up the performance evaluation of high-rate communication links where a high number of samples is needed. 
7. Abstract of Cited Paper (BIB007):  We study the effect of training method on the receiver bit error rate (BER) performance in constant envelope phase modulation schemes that are transmitted through flat fading channels. Here we propose a novel method for receiver training by sending information bits with unbalanced probabilities. We call this method implicit training and compare it with traditional (explicit) training scheme in which known periodic training sequences are sent to the receiver. The simulation results show superior performance of implicit training where the gain is 2 dB at information rate of 0.15 bits/channel use. 
8. Abstract of Cited Paper (BIB008):  In this paper, time-varying flat-fading channels are modeled as first-order finite-state Markov channels (FSMC). The effect of this modeling on the channel information capacity is addressed. The approximation accuracy of the first-order memory assumption in the Markov model is validated by comparing the FSMC capacity with the channel capacity assuming perfect state information at the receiver side. The results indicate that the first-order Markovian assumption is accurate for normalized Doppler frequencies f/sub d/T /spl lsim/ 0.01, in amplitude-only quantization of the channel gain for noncoherent binary signaling. In phase-only and joint phase and amplitude quantization of the channel gain for coherent binary signaling, the first-order Markovian assumption is accurate for f/sub d/T /spl lsim/ 0.001. Furthermore, the effect of channel quantization thresholds on the FSMC capacity is studied. In high signal-to-noise ratio (SNR) conditions, nonuniform two-level amplitude quantization scheme outperforms equiprobable quantization method by 0.8-1.5 dB. 
9. Abstract of Cited Paper (BIB009):  This paper addresses the problem of dynamic control for power and rate allocation in V-BLAST wireless systems over Markovian fading channels. The problem is posed as a controlled Markov decision process problem with the goal of minimizing the average transmission power with the constraint on the average delay that can be interpreted as the Quality of Service (QoS) requirement of a given application. Several structural results on the nature of the optimal randomized policies and costs are derived. In particular, it is shown that number of actions to be considered can be reduced by dividing the rate allocation problem into bit-loading problem across individual antennas and the total rate allocation based on the current buffer and channel state. Further, optimal rate allocation policies are shown to be a mixture of two pure policies that are non-decreasing in the buffer state. These results can be utilized to devise an efficient online learning algorithm for optimal rate allocation policies1. 
10. Abstract of Cited Paper (BIB010):  This paper proposes a novel successive decoding paradigm for fading channels. K independent codewords of different rates and lengths are interleaved at the transmitter according to a pattern, and successively decoded at the receiver. This enables progressively better channel estimates for the receiver, at a minimal cost of pilot symbols. At each decoding stage, channel estimation and decoding are performed separately, or iteratively if the residual channel correlation within a codeword can be exploited. The flexible interleaver pattern, after some level of optimization, achieves near-capacity system performance with only a small number of codewords K, as demonstrated numerically by a finite state Markov modelled flat fading channel.

Literature Review:
In the literature, first-order FSMC modeling of the TV-FFC is most commonly used. In this section, we discuss how first-order FSMC models can be obtained for fading channels and postpone the discussion on the applicability and accuracy of the firstorder assumption to later in the article. There are three possibilities for modeling a TV-FFC with a first-order FSMC.  FSMC modeling of the TV-FFC amplitude a or the received SNR γ has been predominantly studied in the literature from 1995 onwards BIB001 - BIB002 , BIB007 - BIB004 , BIB005 , BIB010 - BIB006 . In amplitude-only FSMC modeling, the effects of unknown channel phase on the received signal are not considered. This modeling is more suitable for applications, where the channel phase can be estimated and compensated prior to decoding or where differential or noncoherent detection is used. More recently, FSMC modeling of the TV-FFC phase θ (or both in-phase h i and quadrature h q components, which together contain phase and amplitude information) has been considered by various researchers including BIB011 , BIB003 - BIB008 , and BIB009 . By including the fading phase in the FSMC model, various joint channel estimation and coherent data decoding techniques for phase-sensitive modulations in the presence of (fast) time-varying channel amplitude and phase distortions have become possible. These techniques will be addressed in the applications of FSMC models for fading channels later in the article.