Fusion of decisions transmitted over Rayleigh fading channels in wireless sensor networks

In this paper, we revisit the problem of fusing decisions transmitted over fading channels in a wireless sensor network. Previous development relies on instantaneous channel state information (CSI). However, acquiring channel information may be too costly for resource constrained sensor networks. In this paper, we propose a new likelihood ratio (LR)-based fusion rule which requires only the knowledge of channel statistics instead of instantaneous CSI. Based on the assumption that all the sensors have the same detection performance and the same channel signal-to-noise ratio (SNR), we show that when the channel SNR is low, this fusion rule reduces to a statistic in the form of an equal gain combiner (EGC), which explains why EGC is a very good choice with low or medium SNR; at high-channel SNR, it is equivalent to the Chair-Varshney fusion rule. Performance evaluation shows that the new fusion rule exhibits only slight performance degradation compared with the optimal LR-based fusion rule using instantaneous CSI.     

Decision fusion for Wireless Sensor Networks under Nakagami fading channels

Decision fusion rules for Wireless Sensor Networks (WSNs) under Nakagami fading channels are investigated in this paper. Considering the application limitation of Likelihood Ratio Test fusion rule based on information of Channel Statistics using Series expansion (LRT-CSS), and the detection performance limitation of the Censoring based Mixed Fusion rule (CMF), a new LRT fusion rule based on information of channel statistics has been presented using Laplace approximation (LRT-CSL). Theoretical analysis and simulations show that the proposed fusion rule provides better detection performance than the Censoring based Mixed Fusion (CMF) and LRT-CSS fusion rules. Furthermore, compared with LRT-CSS fusion rule, the proposed fusion rule expands the application range of likelihood ratio test fusion rule.     

Cyclostationarity-based cooperative spectrum sensing over imperfect reporting channels

Reliable detection of weak primary user signals is a crucial problem for cognitive radio networks. To address the above issue, cooperative spectrum sensing (CSS) methods based on cyclostationary detection (CD) have been introduced in the literature. In this paper, a soft decision-based CSS method based on the second-order CD at secondary users (SUs) is proposed. The proposed scheme aims to maximize the deflection criterion at the fusion center (FC), while the reporting channels are characterized by Rayleigh fading. To this end, a fusion rule which does not require to know the noise variances of sensing channels is developed. Since the fusion rule assumes the perfect knowledge of channel state information (CSI) of reporting links, it has theoretical significance and provides an upper bound for the performance of cyclostationarity-based CSS. We have also proposed a more practical suboptimum fusion rule and studied its detection performance in the presence of uncertainties in noise variance and channel power gain estimations. Furthermore, in order to be able to evaluate the performance of the CSS, an analytic threshold estimation method has been proposed. Extensive simulation results have been illustrated the robustness of the proposed method compared to the existing cyclostationary detectors.     

The union bound for turbo-coded modulation systems over fadingchannels

We derive performance bounds for turbo-coded modulation systems over fading channels. We consider a Ricean fading channel model both with and without channel-state information (CSI). This model obviously includes Rayleigh fading channel as a special case. The bounds are extensions of similar bounds derived for additive white Gaussian noise channels. For the special case of a Rayleigh fading channel with CSI, we also derive a tighter version of the bound. We illustrate the use of the new bounds via some numerical examples     

Channel aware decision fusion in wireless sensor networks

Information fusion by utilizing multiple distributed sensors is studied in this work. Extending the classical parallel fusion structure by incorporating the fading channel layer that is omnipresent in wireless sensor networks, we derive the likelihood ratio based fusion rule given fixed local decision devices. This optimum fusion rule, however, requires perfect knowledge of the local decision performance indices as well as the fading channel. To address this issue, two alternative fusion schemes, namely, the maximum ratio combining statistic and a two-stage approach using the Chair-Varshney fusion rule, are proposed that alleviate these requirements and are shown to be the low and high signal-to-noise ratio (SNR) equivalents of the likelihood-based fusion rule. To further robustify the fusion rule and motivated by the maximum ratio combining statistics, we also propose a statistic analogous to an equal gain combiner that requires minimum a priori information. Performance evaluation is performed both analytically and through simulation.     

Secrecy Analysis of Cooperative Vehicular Relaying Networks over Double-Rayleigh Fading Channels

In this paper, we investigate physical-layer security performance of the cooperative vehicular relaying networks, wherein the communication from a source vehicle to the destination vehicle is assisted by an amplify-and-forward (AF) relay vehicle in the presence of a passive eavesdropper vehicle. We assume that the communication links between the vehicles experience double-Rayleigh fading. We also consider two AF relaying protocols: (1) fixed gain relaying which requires partial channel state information (CSI), and (2) variable gain relaying which requires full CSI. Specifically, we derive the novel intercept probability and ergodic secrecy capacity expressions for both fixed and variable gain relaying in the presence of double-Rayleigh fading channels. The numerical and simulation results verify our theoretical and analytical findings, and show the impacts of channel conditions and relay and eavesdropper locations on the system secrecy performance.

     

On the capacity of some channels with channel state information

We study the capacity of some channels whose conditional output probability distribution depends on a state process independent of the channel input and where channel state information (CSI) signals are available both at the transmitter (CSIT) and at the receiver (CSIR). When the channel state and the CSI signals are jointly independent and identically distributed (i.i.d.), the channel reduces to a case studied by Shannon (1958). In this case, we show that when the CSIT is a deterministic function of the CSIR, optimal coding is particularly simple. When the state process has memory, we provide a general capacity formula and we give some more restrictive conditions under which the capacity has still a simple single-letter characterization, allowing simple optimal coding. Finally, we turn to the additive white Gaussian noise (AWGN) channel with fading and we provide a generalization of some results about capacity with CSI for this channel. In particular, we show that variable-rate coding (or multiplexing of several codebooks) is not needed to achieve capacity and, even when the CSIT is not perfect, the capacity achieving power allocation is of the waferfilling type     

Performance analysis of HARQ protocols with link adaptation on fading channels

This work considers hybrid automatic repeat request (HARQ) protocols on a fading channel with Chase combining and deals with both Rayleigh and Nakagami-m fading. We derive the packet loss probability and the throughput for HARQ both for a slow-varying and a fast-varying channel. We then consider link adaptation with complete channel state information (CSI) for which the instantaneous signal-to-noise ratio (SNR) is known and with incomplete CSI for which only the average SNR is known. We derive analytical formulae of the long-term throughput. These formulae are simple enough to be used for higher level simulations. We show that the throughput is slightly higher on a slow-varying channel but at the expense of a higher loss probability.     

On the Secrecy Capacity of Fading Channels

We consider the secure transmission of information over an ergodic fading channel in the presence of an eavesdropper. Our eavesdropper can be viewed as the wireless counterpart of Wyner's wiretapper. The secrecy capacity of such a system is characterized under the assumption of asymptotically long coherence intervals. We first consider the full channel state information (CSI) case, where the transmitter has access to the channel gains of the legitimate receiver and the eavesdropper. The secrecy capacity under this full CSI assumption serves as an upper bound for the secrecy capacity when only the CSI of the legitimate receiver is known at the transmitter, which is characterized next. In each scenario, the perfect secrecy capacity is obtained along with the optimal power and rate allocation strategies. We then propose a low-complexity on/off power allocation strategy that achieves near-optimal performance with only the main channel CSI. More specifically, this scheme is shown to be asymptotically optimal as the average signal-to-noise ratio (SNR) goes to infinity, and interestingly, is shown to attain the secrecy capacity under the full CSI assumption. Overall, channel fading has a positive impact on the secrecy capacity and rate adaptation, based on the main channel CSI, is critical in facilitating secure communications over slow fading channels.      

The Effect of Fading, Channel Inversion, and Threshold Scheduling on Ad Hoc Networks

This paper addresses three issues in the field of ad hoc network capacity: the impact of (i) channel fading, (ii) channel inversion power control, and (iii) threshold-based scheduling on capacity. Channel inversion and threshold scheduling may be viewed as simple ways to exploit channel state information (CSI) without requiring cooperation across transmitters. We use the transmission capacity (TC) as our metric, defined as the maximum spatial intensity of successful simultaneous transmissions subject to a constraint on the outage probability (OP). By assuming the nodes are located on the infinite plane according to a Poisson process, we are able to employ tools from stochastic geometry to obtain asymptotically tight bounds on the distribution of the signal-to-interference (SIR) level, yielding in turn tight bounds on the OP (relative to a given SIR threshold) and the TC. We demonstrate that in the absence of CSI, fading can significantly reduce the TC and somewhat surprisingly, channel inversion only makes matters worse. We develop a threshold-based transmission rule where transmitters are active only if the channel to their receiver is acceptably strong, obtain expressions for the optimal threshold, and show that this simple, fully distributed scheme can significantly reduce the effect of fading.     

Capacity Improvement for TDD-MIMO Systems via AR Modeling Based Linear Prediction

The quality of channel state information (CSI) affects the performance of multiple input multiple output (MIMO) systems which employ multi-elements antenna arrays at both the transmitter and the receiver. In a time division duplex (TDD) systems, the CSI for downlink can be obtained from uplink channel using reciprocity principal. However, the performance of a MIMO system can be degraded due to channel impairments especially in fast fading scenarios when the CSI obtained from uplink is used for downlink transmission. In this paper, we study performance of autoregressive (AR) modeling based MIMO channel prediction under varying channel propagation conditions (mobile speed, multipath number and angle spread) and prediction filter order. Our simulation results show that using the predicted CSI for downlink provides capacity improvement compared to conventional method.     

Channel estimation based on distributed compressed sensing in amplify-and-forward relay networks

In orthogonal frequency-division multiplexing(OFDM)amplify-and-forward(AF)relay networks,in order to exploit diversity gains over frequency-selective fading channels,the receiver needs to acquire the knowledge of channel state information(CSI).In this article,based on the recent methodology of distributed compressed sensing(DCS),a novel channel estimation scheme is proposed.The joint sparsity model 2(JSM-2)in DCS theory and simultaneous orthogonal matching pursuit(SOMP)are both introduced to improve the estimation performance and increase the spectral efficiency.Simulation results show that compared with current compressed sensing(CS)methods,the estimation error of our scheme is reduced dramatically in high SNR region while the pilot number is still kept small.     

Analytical modelling of multiservice switching networks with multiservice sources and resource management mechanisms

In this paper, we presents an analytical link capacity and outage performance analysis of downlink multiuser diversity (MUD) in multiple-input multiple-output (MIMO) system employing maximal-ratio combining (MRC) with transmit antenna selection (TAS) in the presence of imperfect channel state information (CSI) due to feedback delay over Rayleigh fading channels. The unified achievable analysis is appropriate for MUD–MIMO with TAS/MRC systems in which effective output signal-to-noise ratio (SNR) is specified as highest order statistic of chi-square distribution. Based on this framework, the closed-form channel capacity and outage probability expressions are examined for the MUD–MIMO exploiting TAS/MRC with normalized SNR based scheduling in heterogeneous wireless networks. Further, we derive approximate upper bound capacity as well as capacity at high SNR and low SNR region under delayed feedback CSI. The upper and lower bound of outage probability under delayed feedback CSI is also evaluated. Thereafter the impact of feedback delay and antenna structures with significance on the consideration of MUD on the performance of the system has been analyzed.     

Pilot symbol-assisted detection of CPM schemes operating in fastfading channels

We present a coherent detection technique for continuous phase modulation (CPM) operating in the Rayleigh flat fading channel. The technique is based on the idea of inserting periodically data dependent pilot symbols that force the CPM signal to pass through known phase states. This transmission format enables the receiver to extract from the received signal the channel fading gains at regularly spaced instants. When coupled with proper channel estimation filters, very accurate channel state information (CSI) can be estimated at the receiver for fading compensation. Moreover, the accuracy of the CSI can be further refined by adopting a multiple-pass decoding approach. The paper discusses (a) the pilot symbol encoding technique required to force a M-level CPM scheme with a modulation index of p/M, p is an integer, to return periodically to a set of known phase states, (b) the optimal channel estimation filters, (c) a trellis-based precoding technique that can reduce the bit error rate in M-level CPM systems by close to 50%, and (d) a multiple-pass channel estimator/demodulator. Analytical and simulation results are presented for minimum shift keying (MSK), Gaussian MSK, and four-level continuous phase frequency shift keying with a modulation index of 1/4. It is observed that our pilot symbol-assisted CPM schemes exhibit no irreducible error floor even at a channel fade rate of three percent the symbol rate. The implicit phase coding in CPM and the accurate CSI provided by the pilot symbols lead to a diversity effect in the bit error rate curves of these modulation schemes     

Performance of Transmit and Receive Antenna Selection in the Presence of Channel Estimation Errors

This letter considers the effect of channel estimation errors on the performance of space-time coded (STC) systems with transmit and receive antenna selection over quasi-static flat fading channels. By performing pairwise error probability analysis and presenting numerical examples, we show that the diversity order achieved with perfect channel state information (CSI) is still achievable with imperfect CSI used both at the antenna selection and the space-time decoding processes. We note that our results apply to general STC systems with both transmit and/or receive antenna selection based on largest received powers which can be estimated by any channel estimator.     

Achievable Rates with Imperfect Transmitter Side Information Using a Broadcast Transmission Strategy

rdquoWe investigate the performance of the broadcast approach for various fading distributions, which correspond to different models of partial transmit channel state information (CSI). The first model considered is the quantized limited feedback. In this model, the receiver can send as feedback only a finite number of bits describing the fading gain. We derive the optimal power allocation for the broadcast approach for the quantized feedback model. For a Rayleigh fading channel, numerical results here show that if the feedback word can be longer than one bit, the broadcasting gain becomes negligible, due to diminished channel uncertainty. The second partial transmit CSI model is a stochastic Gaussian model with mean and variance information, which is commonly used for modeling the channel estimation error. In a single-input single-output (SISO) channel, this model also corresponds to the Ricean fading distribution, for which we derive maximal achievable broadcasting rates. We further consider a multiple-input single-output (MISO) channel, and derive the optimal power allocation strategy in a broadcast approach. Numerical results here show that uniform power allocation is preferable over beamforming power allocation in the region where broadcasting gain over single level coding is non-negligible.     

Limited Feedback Beamforming Over Temporally-Correlated Channels

Feedback of quantized channel state information (CSI), called limited feedback, enables transmit beamforming in multiple-input-multiple-output (MIMO) wireless systems with a small amount of overhead. Due to its efficiency, beamforming with limited feedback has been adopted in several wireless communication standards. Prior work on limited feedback commonly adopts the block fading channel model where temporal correlation in wireless channels is neglected. In this paper, we consider temporally correlated channels and design single-user transmit beamforming with limited feedback. Analytical results concerning CSI feedback are derived by modeling quantized CSI as a first-order finite-state Markov chain. These results include the information rate of the CSI quantizer output, the bit rate a CSI feedback channel is required to support, and the effect of feedback delay on throughput. In particular, based on the theory of Markov chain convergence rate, feedback delay is proved to reduce the throughput gain due to CSI feedback at least exponentially. Furthermore, an algorithm is proposed for CSI feedback compression in time. Combining the results in this work leads to a new method for designing limited feedback beamforming as demonstrated by a design example.     

Reliable adaptive modulation aided by observations of another fading channel

Adaptive transmission techniques, such as adaptive modulation and coding, adaptive power control, adaptive transmitter antenna diversity, etc., generally require precise channel estimation and feedback of channel state information (CSI). For fast vehicle speeds, reliable adaptive transmission also requires long-range prediction of future CSI, since the channel conditions are rapidly time variant. In this paper, we propose using past channel observations of one carrier to predict future CSI and perform adaptive modulation without feedback for another correlated carrier. We derive the minimum mean-square error (MMSE) long-range channel prediction that uses the time- and frequency-domain correlation function of the Rayleigh fading channel. An adaptive MMSE prediction method is also proposed. A statistical model of the prediction error that depends on the frequency and time correlation is developed and is used in the design of reliable adaptive modulation methods. We use a standard stationary fading channel model (Jakes model) and a novel physical channel model to test our algorithm. Significant gains relative to nonadaptive techniques are demonstrated for sufficiently correlated channels and realistic prediction range.     

Multiple-Antenna Signaling Over Fading Channels With Estimated Channel State Information: Capacity Analysis

Multiple-antenna concepts for wireless communication systems promise high spectral efficiencies and improved error rate performance by proper exploitation of the randomness in multipath propagation. In this paper, we investigate the impact of channel uncertainty caused by channel estimation errors on the capacity of Rayleigh and Ricean block-fading channels. We consider a training-based multiple-antenna system that reserves a portion of time to sound the channel. The training symbols are used to estimate the channel state information (CSI) at the receiver by means of an arbitrary linear estimation filter. No CSI is assumed at the transmitter. Our analysis is based on an equivalent system model for training-based multiple-antenna systems which specifies the channel by the estimated (and hence, known) channel coefficients and an uncorrelated, data-dependent, multiplicative noise. This model includes the special cases of perfect CSI and no CSI. We present new upper and lower bounds on the maximum instantaneous mutual information to compute ergodic and outage capacities, and extend previous results to arbitrary (and possibly mismatched) linear channel estimators and to correlated Ricean fading. Several numerical results for single- and multiple-antenna systems with estimated CSI are included as illustration.     

Fading Channel Prediction for Mobile Radio Adaptive Transmission Systems

Adaptive transmission methods can potentially aid the achievement of high data rates required for mobile radio multimedia services. To realize this potential, the transmitter needs accurate channel state information (CSI) for the upcoming transmission frame. In most mobile radio systems, the CSI is estimated at the receiver and fed back to the transmitter. However, unless the mobile speed is very low, the estimated CSI cannot be used directly to select the parameters of adaptive transmission systems, since it quickly becomes outdated due to the rapid channel variation caused by multipath fading. To enable adaptive transmission for mobile radio systems, prediction of future fading channel samples is required. Several fundamental issues arise in the design and testing of fading prediction algorithms for adaptive transmission systems. These include complexity, robustness, choice of an appropriate channel model for algorithm validation, channel estimation and noise reduction required for reliable prediction, and design and analysis of adaptive transmission methods aided by fading prediction algorithms. We use these criteria in the review of recent advances in the area of fading channel prediction. We also demonstrate that reliable fading prediction makes adaptive transmission feasible in diverse wireless communication systems.