Opportunistic file transfer over a fading channel under energy and delay constraints

We consider transmission control (rate and power) strategies for transferring a fixed-size file (finite number of bits) over fading channels under constraints on both transmit energy and transmission delay. The goal is to maximize the probability of successfully transferring the entire file over a time-varying wireless channel modeled as a finite-state Markov process. We study two implementations regarding the delay constraints: an average delay constraint and a strict delay constraint. We also investigate the performance degradation caused by the imperfect (delayed or erroneous) channel knowledge. The resulting optimal policies are shown to be a function of the channel-state information (CSI), the residual battery energy, and the number of residual information bits in the transmit buffer. It is observed that the probability of successful file transfer increases significantly when the CSI is exploited opportunistically. When the perfect instantaneous CSI is available at the transmitter, the faster channel variations increase the success probability under delay constraints. In addition, when considering the power expenditure in the pilot for channel estimation, the optimal policy shows that the transmitter should use the pilot only if there is sufficient energy left for packet transfer; otherwise, a channel-independent policy should be used.     

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.     

Performance of Alamouti transmit diversity over time-varying Rayleigh-fading channels

We analyze the impact of a time-varying Rayleigh-fading channel on the performance of an Alamouti transmit-diversity scheme. We propose several optimal and suboptimal detection strategies for mitigating the effects of a time-varying channel, and derive expressions for their bit-error probability as a function of the channel correlation coefficient /spl rho/. We find that the maximum-likelihood detector that optimally compensates for the time-varying channel is very tolerant to time-varying fading, attaining full diversity order even for the extreme case of /spl rho/=0. In contrast, although lower in complexity, the suboptimal schemes suffer a diversity penalty and are thus suitable only for slowly fading channels.     

Outage analysis of the hybrid free-space optical and radio-frequency channel

We study the hybrid free-space optical (FSO) and radio-frequency (RF) channel from an information theoretic perspective. Since both links operate at vastly different carrier frequencies, we model the hybrid channel as a pair of parallel channels. Moreover, since the FSO channel signals at a higher rate than the RF channel, we incorporate this key feature in the parallel channel model. Both channels experience fading due to scintillation, which is slow compared to typical signalling rates. Under this framework, we study the fundamental limits of the hybrid channel. In particular, we analyse the outage probability in the large signal-to-noise ratio (SNR) regime, and obtain the outage diversity or SNR exponent of the hybrid system. First we consider the case when only the receiver has perfect channel state information (CSIR case), and obtain the exponents for general scintillation distributions. These exponents relate key system design parameters to the asymptotic outage performance and illustrate the benefits of using hybrid systems with respect to independent FSO or RF links. We next consider the case when perfect CSI is known at both the receiver and transmitter, and derive the optimal power allocation strategy that minimises the outage probability subject to peak and average power constraints. The optimal solution involves non-convex optimisation, which is intractable in practical systems. We therefore propose a suboptimal algorithm that achieves significant power savings (on the order of tens of dBs) over uniform power allocation. We show that the suboptimal algorithm has the same diversity as the optimal power allocation strategy.     

Performance of coded DS-CDMA with pilot-assisted channel estimationand linear interference suppression

We consider a direct sequence (DS-) code division multiple access (CDMA) system with orthogonally multiplexed pilot signals and minimum mean squared error (MMSE) data and channel estimation. Both flat and frequency-selective fading channels are considered. Large system analysis is used to optimize the pilot-to-data power ratio (PDR) and the code rate for a fixed bandwidth expansion. Specifically, the PDR is selected to minimize the probability of error subject to a constraint on transmitted power. When the MMSE filter estimates the channel of the desired user, but averages over the channels of the interferers (corresponding to an adaptive filter in moderate to fast fading), the optimal PDR is less than that for the matched filter (MF). That is, the MMSE filter benefits from allocating more power to the data. When the MMSE filter directly incorporates estimates of all users' channel coefficients, the optimal PDR is greater than that for the MF. System performance as a function of code rate is characterized through both probability of error and cutoff rate. The optimal code rate for the MMSE receiver is generally higher than that for the MF, and increases with load and E_b/N₀. In the presence of fading, and with channel estimation, the optimal code rate approaches zero for both MMSE and MF receivers, but the MMSE filter is more robust with respect to a suboptimal choice of code rate     

Spectrum Efficiency Evaluation with Diversity Combining for Fading and Branch Correlation Impairments

In this paper, closed-form expressions for capacities per unit bandwidth for fading channels with impairments due to Branch Correlation are derived for optimal power and rate adaptation, constant transmit power, channel inversion with fixed rate, and truncated channel inversion policies for maximal ratio combining diversity reception case. Closed-form expressions for system spectrum efficiency when employing different adaptation policies are derived. Analytical results show accurately that optimal power and rate adaptation policy provides the highest capacity over other adaptation policies. In the case of errors due to branch correlation, optimal power and rate adaptation policy provides the best results. All adaptation policies suffer no improvement in channel capacity as the branch correlation is increased. This fact is verified using various plots for different policies. With increase in branch correlation, capacity gains are significantly larger for optimal power and rate adaptation policy as compared to the other policies. The outage probability for branch correlation is also derived and analyzed using plots for the same.     

Capacity, mutual information, and coding for finite-state Markovchannels

The finite-state Markov channel (FSMC) is a discrete time-varying channel whose variation is determined by a finite-state Markov process. These channels have memory due to the Markov channel variation. We obtain the FSMC capacity as a function of the conditional channel state probability. We also show that for i.i.d. channel inputs, this conditional probability converges weakly, and the channel's mutual information is then a closed-form continuous function of the input distribution. We next consider coding for FSMCs. In general, the complexity of maximum-likelihood decoding grows exponentially with the channel memory length. Therefore, in practice, interleaving and memoryless channel codes are used. This technique results in some performance loss relative to the inherent capacity of channels with memory. We propose a maximum-likelihood decision-feedback decoder with complexity that is independent of the channel memory. We calculate the capacity and cutoff rate of our technique, and show that it preserves the capacity of certain FSMCs. We also compare the performance of the decision-feedback decoder with that of interleaving and memoryless channel coding on a fading channel with 4PSK modulation     

Optimal resource allocation for wireless video over CDMA networks

We present a multiple-channel video transmission scheme in wireless CDMA networks over multipath fading channels. We map an embedded video bitstream, which is encoded into multiple independently decodable layers by 3D-ESCOT video coding technique, to multiple CDMA channels. One video source layer is transmitted over one CDMA channel. Each video source layer is protected by a product channel code structure. A product channel code is obtained by the combination of a row code based on rate compatible punctured convolutional code (RCPC) with cyclic redundancy check (CRC) error detection and a source-channel column code, i.e., systematic rate-compatible Reed-Solomon (RS) style erasure code. For a given budget on the available bandwidth and total transmit power, the transmitter determines the optimal power allocations and the optimal transmission rates among multiple CDMA channels, as well as the optimal product channel code rate allocation, i.e., the optimal unequal Reed-Solomon code source/parity rate allocations and the optimal RCPC rate protection for each channel. In formulating such an optimization problem, we make use of results on the large-system CDMA performance for various multiuser receivers in multipath fading channels. The channel is modeled as the concatenation of wireless BER channel and a wireline packet erasure channel with a fixed packet loss probability. By solving the optimization problem, we obtain the optimal power level allocation and the optimal transmission rate allocation over multiple CDMA channels. For each CDMA channel, we also employ a fast joint source-channel coding algorithm to obtain the optimal product channel code structure. Simulation results show that the proposed framework allows the video quality to degrade gracefully as the fading worsens or the bandwidth decreases, and it offers improved video quality at the receiver.     

Cross-layer Adaptive Transmission: Optimal Strategies in Fading Channels

We consider cross-layer adaptive transmission for a single-user system with stochastic data traffic and a time- varying wireless channel. The objective is to vary the transmit power and rate according to the buffer and channel conditions so that the system throughput, defined as the long-term average rate of successful data transmission, is maximized, subject to an average transmit power constraint. When adaptation is subject to a fixed bit error rate (BER) requirement, maximizing the system throughput is equivalent to minimizing packet loss due to buffer overflow. When the BER requirement is relaxed, maximizing the system throughput is equivalent to minimizing total packet loss due to buffer overflow and transmission errors. In both cases, we obtain optimal transmission policies through dynamic programming. We identify an interesting structural property of these optimal policies, i.e., for certain correlated fading channel models, the optimal transmit power and rate can increase when the channel gain decreases toward outage. This is in sharp contrast to the water-filling structure of policies that maximize the rate of transmission over fading channels. Numerical results are provided to support the theoretical development.     

Novel Closed-Form Expressions for Ergodic Capacity of MIMO-OSFBC-OFDM Systems Over Channel Adaptation Policies

In this work, closed-form expressions for capacities per unit bandwidth for MIMO-OFDM systems employing Orthogonal Space-Frequency Block Coding over multipath frequency-selective fading channels are derived for adaptation policies like optimal power and rate adaptation, optimal rate adaptation with constant transmit power, channel inversion with fixed rate, and truncated channel inversion polices. A Signal-to-Noise Ratio based user selection scheme is considered. Optimal power and rate adaptation policy provides the highest capacity over other adaptation policies. Capacity penalty is the highest for optimal rate adaptation with constant transmit power policy, while the performance of channel inversion with fixed rate policy and truncated channel inversion policy lie between that of OPRA and ORA policies.     

On power adaptation in adaptive signaling systems

The Shannon capacity of a fading channel under an average-power constraint with channel side information at the transmitter and receiver is only negligibly larger than the capacity of the same channel when constant-power transmission is employed. However, power adaptation has been shown to be quite useful in practical systems, where it has been conjectured that it allows for compensation of the effect of rate quantization. Here, an average bit-error probability constraint is employed instead of the conventional instantaneous bit-error probability constraint. When the set of rates available to the transmitter is unrestricted in practical systems, necessary conditions for jointly optimal power and rate allocation are derived and used to demonstrate that power adaptation is of limited utility. However, when the rates available to the transmitter are restricted to the nonnegative integers for the example of uncoded quadrature amplitude modulation over frequency-nonselective Rayleigh fading channels, a 0.5-0.75 dB loss in power efficiency is incurred when employing only a single power level for each constellation, and a 0.5-bits/symbol loss in rate is incurred when constant power transmission is employed.     

Asymptotically Optimal Power Control Policies for MMSE Multiuser Detector

Asymptotically optimal uplink transmission power control policies are derived for synchronous and asynchronous CDMA time varying fading channels with multiple user classes, random spreading sequences and MMSE multiuser detector. One optimal policy minimizes the outage probability subject to maximum average power budget and maximum transmission power constraints. Another minimizes the average power budget subject to maximum outage probability and maximum transmission power constraints. If the channel states are available, we show that both optimal policies are channel inversion threshold cut-off policies and express them explicitly. When channel states are estimated, we show how to transform the optimal policies into estimator-based policies while controlling the degradation of their performance measures . Finally, we compare between the performance of the optimal policies and other policies in an environment with Lognormal and Rayleigh fading.     

Finite-state Markov model for Rayleigh fading channels

We form a finite-state Markov channel model to represent Rayleigh fading channels. We develop and analyze a methodology to partition the received signal-to-noise ratio (SNR) into a finite number of states according to the time duration of each state. Each state corresponds to a different channel quality indicated by the bit-error rate (BER). The number of states and SNR partitions are determined by the fading speed of the channel. Computer simulations are performed to verify the accuracy of the model     

Capacity and optimal resource allocation for fading broadcastchannels .I. Ergodic capacity

In multiuser wireless systems, dynamic resource allocation between users and over time significantly improves efficiency and performance. In this two-part paper, we study three types of capacity regions for fading broadcast channels and obtain their corresponding optimal resource allocation strategies: the ergodic (Shannon) capacity region, the zero-outage capacity region, and the outage capacity region with nonzero outage. We derive the ergodic capacity region of an M-user fading broadcast channel for code division (CD), time division (TD), and frequency division (FD), assuming that both the transmitter and the receivers have perfect channel side information (CSI). It is shown that by allowing dynamic resource allocation, TD, FD, and CD without successive decoding have the same ergodic capacity region, while optimal CD has a larger region. Optimal resource allocation policies are obtained for these different spectrum-sharing techniques. A simple suboptimal policy is also proposed for TD and CD without successive decoding that results in a rate region quite close to the ergodic capacity region. Numerical results are provided for different fading broadcast channels     

Power adaptation for BPSK signaling with average and peak power constraints in Rayleigh fading channels

We consider power adaptation strategies for binary phase-shift keying signals in Rayleigh fading channels under the assumption that channel state information is provided at both the transmitter and the receiver. We first derive a closed-form expression for the optimal power adaptation that minimizes average bit-error rate (BER) subject to average and peak transmission power constraints. Then, we analyze the average BER for channel inversion power adaptation with the same constraints. Our results show that the performance difference between the optimal power adaptation and the channel inversion becomes negligibly small as available average transmission power increases and/or peak-to-average power ratio decreases. We also find that an optimal peak-to-average power ratio exists that minimizes the average BER in the channel inversion scheme.     

Capacity and optimal resource allocation for fading broadcastchannels .II. Outage capacity

For pt.I see ibid., vol.47, no.3, p.1083-1102 (2002). We study three capacity regions for fading broadcast channels and obtain their corresponding optimal resource allocation strategies: the ergodic (Shannon) capacity region, the zero-outage capacity region, and the capacity region with outage. In this paper, we derive the outage capacity regions of fading broadcast channels, assuming that both the transmitter and the receivers have perfect channel side information. These capacity regions and the associate optimal resource allocation policies are obtained for code division (CD) with and without successive decoding, for time division (TD), and for frequency division (FD). We show that in an M-user broadcast system, the outage capacity region is implicitly obtained by deriving the outage probability region for a given rate vector. Given the required rate of each user, we find a strategy which bounds the outage probability region for different spectrum-sharing techniques. The corresponding optimal power allocation scheme is a multiuser generalization of the threshold-decision rule for a single-user fading channel. Also discussed is a simpler minimum common outage probability problem under the assumption that the broadcast channel is either not used at all when fading is severe or used simultaneously for all users. Numerical results for the different outage capacity regions are obtained for the Nakagami-m (1960) fading model     

Adaptive Modulation over Nakagami Fading Channels

We first study the capacity of Nakagami multipath fading (NMF) channels with an average power constraint for three power and rate adaptation policies. We obtain closed-form solutions for NMF channel capacity for each power and rate adaptation strategy. Results show that rate adaptation is the key to increasing link spectral efficiency. We then analyze the performance of practical constant-power variable-rate M-QAM schemes over NMF channels. We obtain closed-form expressions for the outage probability, spectral efficiency and average bit-error-rate (BER) assuming perfect channel estimation and negligible time delay between channel estimation and signal set adaptation. We also analyze the impact of time delay on the BER of adaptive M-QAM.     

Performance analysis of space-time MMSE multiuser detection for coded DS-CDMA systems in multipath fading channels

This paper investigates the use of convolutional coding in space-time minimum mean-square-error (MMSE) multiuser-based receivers over asynchronous multipath Rayleigh fading channels. We focus on the performance gain attained through error control coding when used with binary-phase-shift-keyed modulation (BPSK) and multiuser access based on direct sequence-code-division multiple access (DS-CDMA). In our analysis, we derive an approximation for the uncoded probability of bit-error in multipath fading channels. This bit-error rate (BER) approximation is shown to be very accurate when compared to the exact performance. For a convolutionally coded system, we obtain a closed form expression for the bit-error rate upper bound. This error bound is noted to be tight as the number of quantization levels increased beyond eight. Using our theoretical results, we obtain an estimate for the achieved user-capacity that accrues due to error control coding. It is found that using convolutional coding with 3-bit soft-decision decoding, a user-capacity gain as much as 300% can easily be achieved when complete fading state information plus ideal channel interleaving are assumed.     

Signal Detection in Cognitive Radio Networks over AWGN and Fading Channels

In this paper, we consider the problem of spectrum sensing based on energy detection method in cognitive radio over wireless communication channels when users experiences fading and nonfading effects. The closed-form analytical expressions for the detection probability are derived over nonfading additive white Gaussian noise channel, Rayleigh, Rician and Nakagami-m fading channels. The detection probability involving Marcum-Q function is replaced by closed-form expression. The probability distribution function of fading channels is used to obtain the expressions for detection probability. The new derived numerical results are simulated under various parameters.     

Effect of shadowing on the performance of space-time trellis-coded systems

We analyze the performance of space-time trellis codes over shadowed Rician fading channels. The shadowed Rician channel is a generalization of the Rician model, where the line-of-sight path is subjected to a lognormal transformation due to foliage attenuation, also referred to as shadowing. Using the moment generating function method, we derive an exact expression for the pairwise error probability (PEP) of space-time trellis coded systems operating over this channel. The asymptotic analysis of PEP shows that the design criteria of space-time trellis codes proposed for Rayleigh fading still hold when used over shadowed Rician channels. We also present simulation results for bit-error rate performance under various degrees of shadowing.