Non-identical Channels Research Articles

Investigation on Multi-user Scheduling Algorithms Over Non-identical Channel Distribution and LTE Networks

In this paper, we investigate the performance of various multi-user scheduling algorithms over independent and non-identically distributed generalized fading channel and 3GPP long term evolution (LTE) networks. Multi-user scheduling is an important task to be performed in wireless communication networks to share the bandwidth resource effectively between large number of users. In this paper, novel expressions for average BER, average channel capacity and fairness among users are derived for various scenarios such as (1) independent identical fading parameter, independent non identical average SNR channel conditions and (2) both fading parameter and average SNR are independent and non-identically distributed under absolute SNR (AS) scheduling and threshold SNR scheduling. More over the performance of threshold SNR scheduling is compared with AS scheduling and other existing scheduling techniques to identify a suitable scheduling algorithm for LTE networks. Analytical expressions are simulated and validated through MATLAB, and insightful discussions are provided from the numerical results.

Analysis of phase bias between GNSS signal components caused by nonideal group delay

Binary offset carrier (BOC) modulations are widely used in the modernized satellite navigation systems. But we find an interesting phenomenon that the signal composed of different BOC modulations suffers larger phase bias than the case that all the components have the same modulation due to the nonideal group delay of the channel. This issue is more obvious in navigation satellites for the use of a narrowband filter to suppress the out-of-band part. The general form of analytic expression that reveals the impact of the nonideal channel on phase bias is presented and validated with simulations. Further, by simplifying the spectrums for the signals like B1 of BeiDou and E1 of Galileo navigation systems, we obtain the concise expression of phase bias and find that the bias is mainly derived from the phase difference between the subcarrier frequencies caused by the odd order terms of group delay.

Performance Analysis of Scheduled Access Mode of the IEEE 802.15.6 MAC Protocol under Non-Ideal Channel Conditions

In this paper, we present an analytical model for the scheduled access mechanism of IEEE 802.15.6 based Wireless Body Area Network (WBAN) taking into account the impact of non-ideal transmission channel. We provide a thorough analysis and closed form expressions for the frame delay, reliability of data transfer, throughput, energy consumption, and Energy Efficiency (EE) of the sensor nodes with medium to high data rate applications. We validate our theoretical derivations through simulation results. The results show the variation in the performance indicators with respect to different system parameters, such as beacon period, data transmission rate, traffic loads, channel Signal-to-Noise Ratio (SNR), Allocation Intervals (AIs), and Payload Sizes (PSs). Our results indicate the tradeoff between average frame delay and EE with respect to selection of AIs and PSs. Thus, through this analysis we show how a network designer can prepare a look-up table for sensor nodes enabling them to select the optimum and minimum AIs and their associated PSs based on the channel SNR to achieve the maximum EE for a particular average frame delay and reliability constraint.

Performance analysis of the IEEE 802.15.4e TSCH-CA algorithm under a non-ideal channel

The TSCH Collision Avoidance (TSCH-CA) algorithm has been implemented by the IEEE 802.15.4e amendment to decrease the probability of repeated collisions in the packet retransmission in the Industrial Wireless Sensor Networks (IWSNs). This paper proposes a two-dimensional Markov chain model to evaluate the performances of the TSCH-CA algorithm when only shared links are used under non-ideal channel conditions. The accuracy of this model has been verified through Monte Carlo simulations. Based on the proposed model, the expressions of different performance metrics that include retransmission probability, data packet loss rate, reliability, energy consumption, normalised throughput and average access delay have been obtained. Furthermore, a comparative study between TSCH-CA and the unslotted CSMA-CA of IEEE 802.15.4 under a non-ideal channel has been provided. Numerical results reveal that the TSCH-CA performances are clearly affected by channel errors when using only shared links under a noisy environment.

Performance analysis of the IEEE 802.15.4e TSCH-CA algorithm under a non-ideal channel

Performance analysis of the IEEE 802.15.4e TSCH-CA algorithm under a non-ideal channel

Outage probability of direct and relay signal selection over non-identical channel estimation error

This paper investigates the outage probability of the direct and relay signal selection in the transmit antenna selection (TAS)-maximal ratio combining (MRC) relay system with user terminal selection at the destination node over non-identical channel estimation error. This paper derives the exact closed-form outage probability expression of the proposed scheme over non-identical channel estimation error, which is the first contribution. Using the approximate cumulative distribution function (CDF), the diversity order of the proposed scheme for the outage probability under non-identical channel estimation error is quantified to MSK+min[MS,KMR] where MS, MR and K denote the number of multiple antennas at the base station and relay node and the number of user terminals at destination node, which is the second contribution. From numerical results, we show that the outage probability of the proposed scheme is superior to that of the conventional schemes by direct signal and relay signal selection. Further, the receive diversity by MRC is removed by non-identical channel estimation error compared to the perfect channel estimation.

Automatic Wireless Signal Classification: A Neural-Induced Support Vector Machine-Based Approach

Automatic Classification of Wireless Signals (ACWS), which is an intermediate step between signal detection and demodulation, is investigated in this paper. ACWS plays a crucial role in several military and non-military applications, by identifying interference sources and adversary attacks, to achieve efficient radio spectrum management. The performance of traditional feature-based (FB) classification approaches is limited due to their specific input feature set, which in turn results in poor generalization under unknown conditions. Therefore, in this paper, a novel feature-based classifier Neural-Induced Support Vector Machine (NSVM) is proposed, in which the features are learned automatically from raw input signals using Convolutional Neural Networks (CNN). The output of NSVM is given by a Gaussian Support Vector Machine (SVM), which takes the features learned by CNN as its input. The proposed scheme NSVM is trained as a single architecture, and in this way, it learns to minimize a margin-based loss instead of cross-entropy loss. The proposed scheme NSVM outperforms the traditional softmax-based CNN modulation classifier by managing faster convergence of accuracy and loss curves during training. Furthermore, the robustness of the NSVM classifier is verified by extensive simulation experiments under the presence of several non-ideal real-world channel impairments over a range of signal-to-noise ratio (SNR) values. The performance of NSVM is remarkable in classifying wireless signals, such as at low signal-to-noise ratio (SNR), the overall averaged classification accuracy is > 97% at SNR = −2 dB and at higher SNR it achieves overall classification accuracy at > 99%, when SNR = 10 dB. In addition to that, the analytical comparison with other studies shows the performance of NSVM is superior over a range of settings.

Performance Analysis of Automatic Modulation Classification using Time Frequency Transforms under Non-Ideal Channel Conditions

Classification of different analog and digital modulation classes using Time-Frequency Transforms (TFTs) through MST and MFSWT under ideal channel conditions is presented in this paper. It also deals with performance analysis of proposed Modified S- Transform (MST) and Modified Frequency Slice Wavelet Transform (MFSWT) based Automatic Modulation Classification (AMC) methods under different channel conditions such as Gaussian and fading channels. The performance of the proposed TFT based AMC methods under AWGN (with SNR values varied from -10 dB to 20 dB) and fading channels is examined through simulation. Moreover, the performance of the proposed TFT based AMC is compared with that of the existing techniques in terms of performance metric namely classification accuracy which is also discussed in this paper.

UWB RSS-Based Localization for Capsule Endoscopy Using a Multilayer Phantom and In Vivo Measurements

In recent years, the localization for capsule endoscopy applications using ultrawideband (UWB) technology has become an attractive field of investigation due to its potential benefits for patients. The literature concerning performance analysis of radio frequency-based localization techniques for in-body applications at UWB frequencies is very limited. Available studies mainly rely on finite-difference time-domain simulations, using digital human models and on experimental measurements by means of homogeneous phantoms. Nevertheless, no realistic analysis based on multilayer phantom measurements or through in vivo experiment has been reported yet. This paper investigates the performance of the received signal strength-based approach for 2-D and 3-D localizations in the UWB frequency band. For 2-D localization, experimental laboratory measurements using a two-layer phantom-based setup have been conducted. For 3-D localization, data from a recently conducted in vivo experiment have been used. Localization accuracy using path loss models, under ideal and non-ideal channel estimation assumptions, is compared. Results show that, under nonideal channel assumption, the relative localization error slightly increases for the 2-D case but not for the in vivo 3-D case. Impact of receivers selection on the localization accuracy has also been investigated for both 2-D and 3-D cases.

Performance analysis of opportunistic beamforming system under non‐identical imperfect channel environment

In this study, the authors study the effect of non-identical channel estimation error and feedback delay on the performance of an opportunistic beamforming system. This study derives the exact system performance (i.e. outage probability, symbol-error rate (SER), and ergodic capacity) of the proposed system using moment generating function in an imperfect channel environment. This study also uses an asymptotic analysis to quantify the diversity order of SER and outage probability to analyse which system variables affect system performance. From the results of an asymptotic analysis, it is shown that by channel estimation error and feedback delay, spatial diversity is eliminated, but the benefits of multiuser diversity still exist. Therefore, the diversity order of the SER and the outage probability of the proposed system are proportional to the number of user terminals, but the conventional system is limited to 1 by channel estimation error and feedback delay.

Training for massive MIMO systems with non-identically aging user channels

In this paper, we consider the problem of channel state information (CSI) acquisition in massive MIMO systems with the users exhibiting non-identical channel aging profiles. For this purpose, we derive the per user achievable rates, and the corresponding CSI outage times for different users. We then use these derived results to argue that scheduling the training of all the users, with respect to the outage time of the fastest moving user is suboptimal, and results in unnecessary training overhead. Therefore, we present and evaluate the performance of two simple schemes for scheduling the training of users with different mobilities. Via numerical results, we show that training a subset of users based on the ages of their channel estimates can significantly increase the spectral efficiency of a massive MIMO system.

Theoretical evaluation of group delay on pseudorange bias

The phenomenon of pseudorange bias, which is also called S-Curve bias, becomes more obvious with the combined use of multiple satellite systems or navigation satellites with different phases. The different characteristics of the transmitting channel of a navigation satellite result in different distortions of the pseudorange bias in navigation signals; in particular, this issue worsens when the RF channel is not optimized to decrease the pseudorange bias. Therefore, it is interesting to reveal the essential relationship between pseudorange bias and the non-ideal channel and to present an analytic model of the effect of a non-ideal channel on pseudorange bias. Instead of using the numerical method of finding the bias of the zero-crossing point of the discriminator, we provide a theoretical evaluation of the S-Curve bias for the given parameters of channel and signals. Based on the model and presented analyses, we find that second-order group delay plays an important role in the distortion of S-Curve bias and should be avoided in the design of the RF channel for navigation satellites and receivers.

Performance analysis of transmit antenna selection–maximal ratio combining relay systems over non‐identical channel estimation error

This study investigates the performance analysis of a transmit antenna selection–maximal ratio combining relay system over non-identical channel estimation error. The proposed system selects both relay and user terminal with a maximum signal-to-noise ratio (SNR) using feedback information. The exact closed-form expression of the proposed system for the outage probability and symbol error rate (SER) is derived in the presence of non-identical channel estimation error. Using the approximated probability density function, the authors quantify the diversity order for the SER and outage probability. From the above results, the diversity order of the proposed system is proportional to the number of relay nodes and user terminals. Thus, the diversity order of the proposed system is superior to that of the previous selection systems. The diversity order of the proposed system is independent of the number of receive antennas at the relay and user terminal and the channel correlation coefficient. Furthermore, the SNR gain of the proposed system is in proportion to the sum of the channel correlation coefficients and the number of receive antennas at the relay and user terminal.

Low Complexity Adaptive Demapper for 2-D Non-Uniform Constellations

In this paper, a novel demapper for 2-D non-uniform constellations (2D-NUCs) is proposed, exploiting the characteristics of these constellations. It represents the combination of two underlying demapping techniques targeting the ATSC 3.0 compliant OFDM transceiver. On the one hand, for low code rates, we define a metric to perform condensed demapping. On the other hand, for high code rates, adaptive sub-region demapping is proposed. In this paper, a combination of both demapping methods is designed showing comparable performance to the classical ML demapper. The gap does not exceed 0.1 dB for all code rates of the ATSC 3.0 standard. Higher complexity reduction, from 79.2% to 95.4%, than state of art 2D-NUC demappers is obtained for 2D-256NUCs. These results are validated for ideal and non-ideal channel state information over additive white noise Gaussian and Rayleigh independently and identically distributed channels. Results are extended to 2D-1kNUCs and 2D-4kNUCs showing demapping complexity reduction from 96% to 99.7% with a negligible impact on performance.

Reconstruction of Sequences Over Non-Identical Channels

Motivated by the error behavior in the DNA storage channel, in this paper, we extend the previously studied sequence reconstruction problem by Levenshtein. The reconstruction problem studies the model in which the information is read through multiple noisy channels, and the decoder, which receives all channel estimations, is required to decode the information. For the combinatorial setup, the assumption is that all the channels cause at most some $t$ errors. Levenshtein considered the case in which all the channels have the same behavior, and we generalize this model and assume that the channels are not identical. Thus, different channels may cause different maximum numbers of errors. For example, we assume that there are $N$ channels, which cause at most $t_{1}$ or $t_{2}$ errors, where $t_{1} , and the number of channels with at most $t_{1}$ errors is at least $\lceil pN\rceil $ , for some fixed $0 . If the information codeword belongs to a code with minimum distance $d$ , the problem is then to find the minimum number of channels that guarantees successful decoding in the worst case. A different problem we study in this paper is where the number of channels is fixed, and the question is finding the minimum distance $d$ that provides exact reconstruction. We study these problems and show how to apply them for the cases of substitutions and transpositions.

A Soft⁻Hard Combination Decision Fusion Scheme for a Clustered Distributed Detection System with Multiple Sensors.

In the distributed detection system with multiple sensors, there are two ways for local sensors to deliver their local decisions to the fusion center (FC): a one-bit hard decision and a multiple-bit soft decision. Compared with the soft decision, the hard decision has worse detection performance due to the loss of sensing information but has the main advantage of smaller communication costs. To get a tradeoff between communication costs and detection performance, we propose a soft–hard combination decision fusion scheme for the clustered distributed detection system with multiple sensors and non-ideal communication channels. A clustered distributed detection system is configured by a fuzzy logic system and a fuzzy c-means clustering algorithm. In clusters, each local sensor transmits its local multiple-bit soft decision to its corresponding cluster head (CH) under the non-ideal channel, in which a simple and efficient soft decision fusion method is used. Between clusters, the fusion center combines all cluster heads’ one-bit hard decisions into a final global decision by using an optimal fusion rule. We show that the clustered distributed system with the proposed scheme has a good performance that is close to that of the centralized system, but it consumes much less energy than the centralized system at the same time. In addition, the system with the proposed scheme significantly outperforms the conventional distributed detection system that only uses a hard decision fusion. Using simulation results, we also show that the detection performance increases when more bits are delivered in the soft decision in the distributed detection system.

M/M/1 Retrial Queue with Collisions and Transmission Errors

In this paper, an M/M/1 retrial queue with collisions and transmission errors is considered. The collision may occur when a primary arriving customer finds the server busy while the transmission errors usually occur due to an erroneous packet or due to a non-ideal channel condition. We apply the generating function method to derive the joint distribution of the server state and the orbit length in steady state and we obtain important system characteristics. Finally, we present numerical examples to show the applicability of the model.

Improved Transmitter Jitter Modeling for Accurate Bit Error Rate (BER) Eye Contours Using Transient Simulation of Short Bit Patterns

Increase in the signaling speeds has led to decrease in jitter budget available for the channel to pass the product specifications. The current serial link specifications are based on a bit-error-rate (BER) metric and hence there is a need to account for jitter statistically. Accurately capturing jitter through the channel is very important to have confidence in the product specifications. Current statistical eye approaches are based on either single pulse/step response or multiple edge responses, which do not account for transmitter (Tx) driver jitter accurately since jitter interaction between the edges is ignored. There is an inherent assumption in pulse/step response methods that there is zero correlation between independent responses created from 2n combinations for n cursor pulse response where n is number where the tail settles, hence one zero crossing does not impact an adjacent zero crossing. Transient simulation accurately accounts for Tx jitter but is time consuming and requires large memory when simulating very large bit sequences. A new methodology is proposed to generate BER contours that capture the Tx driver jitter and inter symbol interference (ISI) through the channel accurately using unique waveforms created from truth table bit combinations. It utilizes 2N short N bit patterns as waveforms with jitter correlation from current bit patterns into adjacent bit patterns to get equivalent transient simulation of a desired pseudo random bit sequence. The method accounts for the edge interactions from any current bit pattern to next successive bit pattern to account for ISI accurately. The statistical eye diagram generated with the above approach includes nonideal channel characteristics, including ISI, XTK from nearby aggressor channels, and jitter through the channel.

Resource Allocation in SWIPT Networks Under a Nonlinear Energy Harvesting Model: Power Efficiency, User Fairness, and Channel Nonreciprocity

This paper considers a multiuser simultaneous wireless information and power transfer system with a nonlinear energy harvesting model, in which a multiantenna base station estimates the downlink channel state information (CSI) via uplink pilots. Each single-antenna user is equipped with a power splitter. Three crucial issues on resource management for this system include: 1) power-efficient improvement, 2) user-fairness guarantee, and 3) nonideal channel reciprocity effect mitigation. Potentially, a resource allocation scheme to address jointly such issues can be devised by using the framework of multiobjective optimization. However, the resulting problem might be complex to solve since the three issues hold different characteristics. Therefore, we propose a novel method to design the resource allocation scheme. In particular, the principle of our method relies on structuralizing mathematically the issues into a cross-layer multilevel optimization problem. On this basis, we then devise solving algorithms and closed-form solutions. Moreover, to instantly adapt the CSI changes in practice while reducing computational burdens, we propose a closed-form suboptimal solution to tackle the problem. Finally, we provide numerical results to show the achievable performance gains using the optimal and suboptimal solutions, and then validate the proposed resource allocation scheme.

Adaptive and Economically-Robust Group Selling of Spectrum Slots for Cognitive Radio-Based Networks.

Auction theory has found vital application in cognitive radio to relieve spectrum scarcity by redistributing idle channels to those who value them most. However, countries have been slow to introduce spectrum auctions in the secondary market. This could be in part because a number of substantial conflicts could emerge for leasing the spectrum at the micro level. These representative conflicts include the lack of legislation, interference management, setting a reasonable price, etc. In addition, the heterogeneous nature of the spectrum precludes the true evaluation of non-identical channels. The information abstracted from the initial activity in terms of price paid for specific channels may not be a useful indicator for the valuation of another channel. Therefore, auction mechanisms to efficiently redistribute idle channels in the secondary market are of vital interest. In this paper, we first investigate such leading conflicts and then propose a novel Adaptive and Economically-Robust spectrum slot Group-selling scheme (AERG), for cognitive radio-based networks such as IoT, 5G and LTE-Advanced. This scheme enables group-selling behavior among the primary users to collectively sell their uplink slots that are individually not attractive to the buyers due to the auction overhead. AERG is based on two single-round sealed-bid reverse-auction mechanisms accomplished in three phases. In the first phase, participants adapt asks and bids to fairly evaluate uplink slots considering the dynamics of spectrum trading such as space and time. In the second phase, an inner-auction in each primary network is conducted to collect asks on group slots, and then, an outer-auction is held between primary and secondary networks. In the third phase, the winning primary network declares the winners of the inner-auction that can evenly share the revenue of the slots. Simulation results and logical proofs verify that AERG satisfies economic properties such as budget balance, truthfulness and individual rationality and improves the utilities of the participants.