Convolutional Neural Networks (CNN) and Graph Neural Networks (GNN) are two widely used architectures in Hyperspectral Image (HSI) Classification. Most CNN models tend to heavily rely on neighboring pixels of the target pixel, leading to performance degradation when target pixels differ from their surrounding pixels. To address this limitation, this paper introduces a novel approach to Hyperspectral Image (HSI) classification using a combination of CNN and GNN networks to complement the drawbacks of CNN models. We propose a CNN-based 3D-Spectral Spatial Feature Network (3D-S2FN) to extract features in spectral, spatial, and spectral-spatial spaces, utilizing pyramid squeeze attention to prioritize their importance. Additionally, we introduce a Graph Attention Feature Processor (GAFP) module that evaluates the relevance of neighboring HSI pixels to the target pixel, generating a graph attention map (GRAM). This GRAM is applied to the CNN’s intermediate features to mitigate neighborhood bias. Unlike conventional GNNs, the proposed GAFP module directly processes the data within a local window, without requiring dimensionality reduction methods that would diminish pixel-level detail. By integrating features from the GAFP and the attention-enhanced 3D-S2FN, the proposed SSGRAM method achieves superior classification performance, as demonstrated through extensive experiments on four publicly available datasets.

Speech emotion recognition (SER) has gained utmost attention among researchers for its vital role in Human-Computer Interaction, enabling systems to understand and respond to the emotional states of the users. In this work, the concept of transfer learning has been extended to the novel domain of hybrid classical-quantum neural networks for enhancing SER performance. The classical part involves preprocessing raw speech signals to generate three-channel log mel-spectrograms and the pretrained VGG 19 network for extracting useful emotional features. The quantum part is built upon a dressed quantum neural network (QNN), comprising multiple parallel QNN blocks, for accurate emotion classification. Extensive experiments on the publicly accessible TESS dataset reveal that the proposed hybrid transfer learning approach achieves state of the art accuracy of 98.93 %. An ablation study demonstrates the significant performance improvement attributed to the incorporation of QNN blocks. The integration of classical and quantum neural networks provides a robust and efficient solution, leveraging the strengths of both computational paradigms to enhance SER based applications.

This work presents a novel approach for speech enhancement in scenarios where clean data is unavailable but noise type is known, using a modified Conditional Generative Adversarial Network (cGAN) with a Residual Attention UNet (RAUNet) as the generator. The proposed Noise-to-Noisy-to-Noise (N2N2N) algorithm works on known noise types to iteratively refine speech signals, achieving high performance even in low signal-to-noise ratio (SNR) conditions such as -15 dB. We demonstrate that our method surpasses existing solutions in terms of robustness, phase preservation, and computational efficiency. Experimental results validate the effectiveness of our approach, showcasing significant improvements in PESQ, STOI, CBAK, COVL and SSNR metrics across various noise environments.

The transition to Electric Vehicles (EVs) is crucial for sustainable transportation. However, the adoption of traditional plug-in charging systems remains limited due to their time-consuming nature and infrastructure demands. This study presents a Wireless Power Transfer (WPT) system leveraging inductive coupling to enhance EV charging efficiency, compatibility, and safety. The system converts AC to DC with power factor correction, then transforms it into high-frequency AC to energize the transmitter coil. The receiver coil generates alternating current (AC), which then converts to direct current (DC) for charging the battery. The proposed WPT model, developed using MATLAB Simulink Optimizer, demonstrates a charging efficiency ranging from 90 % to 93 %, resulting in energy losses as low as 10 % to 15 % and improved user convenience by reducing the need for manual plug-in operations. The developed model assumes a standard 60 kWh EV battery can be charged from 20 % to 80 % in approximately 3 hours using the proposed WPT system, compared to 5–6 hours with conventional plug-in chargers.

Quantum machine learning is one of the most exciting new avenues in the world of artificial intelligence, especially because of the enormous computational power of quantum computers and the promise of the development of near error-free quantum computers in the not-so-distant future. For quantum algorithms to be used in real-life applications, quantum computers must be able to work with classical data. One of the key steps in quantum algorithms dealing with classical data is the encoding of classical data points to quantum states, which can then be processed by quantum gates. It is known that the type of encoding technique that works best for a particular network is dependent on the dataset being used. In this paper, a new parallel structure is proposed utilizing two encoding techniques, namely amplitude encoding and angle encoding, for effective classical data classification via quantum neural network. The paper further proposes a maximally expressible and entangled ansatz used to design a simple Quantum Convolutional Neural Network (QCNN) with only 32 parameters, that is used in the latter stages of the network and is kept the same across all encoding instances so that a comparison between the different encoding methods is possible. Extensive experimentation is carried out on two publicly available image datasets, namely MNIST and Fashion MNIST. The results show that the proposed method achieves better results than any of the encoding techniques deployed alone for binary classification.

Brain-computer interface (BCI) systems rely on capturing characteristics of human brain activity from the electroencephalography (EEG) signals, especially for the reliable classification of motor imagery tasks. For multi-channel EEG signals, it is crucial to precisely capture the spatio-temporal variation along with the frequency characteristics. Hence, instead of directly operating on raw EEG data, in this paper, discrete wavelet transform (DWT) is first applied to the motor-imagery multi-channel EEG data and then a deep learning architecture is designed incorporating spatial-temporal operations, which operates on the DWT-transformed EEG signal. In the proposed architecture, temporal convolution followed by spatial convolution is performed on the DWT-operated MI-EEG signal, and this part is termed as SAT-net. Next, by considering all channels together convolutional operation is performed to reduce the number of channels and this part is termed as SOC-net. Finally, a fully connected layer is used to classify the MI-EEG data from the derived feature vector. Extensive experimentation is performed on multiple subjects taken from the MI-based EEG dataset BCI Competition IV 2a. It is found that the proposed model offers a classification accuracy of 84.65%, consistently providing better classification performance than that obtained by some state-of-the-art methods.

In-band full-duplex (IBFD) transmission enables simultaneous transmission and reception of signals over the same frequency, thereby doubling spectral efficiency. This technique has the potential to be the backbone of next-generation wireless networks. At the same time, a continuous up-scaling of wireless network carrier frequencies arising from ever-increasing data traffic is driving research on integrated sensing and communications (ISAC) systems. This paper considers hitherto unexamined ISAC system comprising IBFD multi-user (MU) multiple-input-multiple-output (MU-MIMO) communications and a distributed MIMO radar. In particular, we propose a transceiver co-design mechanism for a joint distributed MIMO radar and an IBFD MU-MIMO communications system in the presence of a moving radar target. We leverage the relationship between the achievable rate and the weighted minimum mean squared error for the co-designed transceiver. We solve the resulting non-convex optimization using the block coordinate descent algorithm to sequentially obtain the MIMO radar waveform matrix, the downlink, and uplink precoders of the IBFD MU-MIMO, and linear receive filters subject to the power and quality-of-service constraints. Numerical experiments show that our proposed WMMSE-based method for distributed ISAC design achieves monotonic convergence within finite steps with a much-improved signal-to-noise ratio for radar and communications functions.

We present a precoder design algorithm for an in-band full-duplex (IBFD) multi-user multiple-input-multiple-output (MU-MIMO) communications system concurrently operating within the same frequency band with a widely-distributed MIMO radar (WDMR). Prior works on joint radar communications (JRC) problems primarily focus on colocated MIMO radars and half-duplex/single-user MIMO communications. We maximize the weighted sum rate (WSR) of the joint radar-communications system subjected to UL/DL power budgets and quality of service. We solve the WSR maximization problem as a weighted minimum mean-squared-error (WMMSE) minimization problem by exploiting the relationship between achievable rate and MSE. A block coordinate descent (BCD) algorithm is resorted to finding the precoders for all UEs sequentially. Our numerical experiments demonstrate that the proposed precoder design scheme outperforms conventional precoding strategies in the presence of a WDMR.

Rapid and precise diagnosis of COVID-19 is one of the major challenges faced by the global community to control the spread of this overgrowing pandemic. In this article, a hybrid neural network is proposed, named CovTANet, to provide an end-to-end clinical diagnostic tool for early diagnosis, lesion segmentation, and severity prediction of COVID-19 utilizing chest computer tomography (CT) scans. A multiphase optimization strategy is introduced for solving the challenges of complicated diagnosis at a very early stage of infection, where an efficient lesion segmentation network is optimized initially, which is later integrated into a joint optimization framework for the diagnosis and severity prediction tasks providing feature enhancement of the infected regions. Moreover, for overcoming the challenges with diffused, blurred, and varying shaped edges of COVID lesions with novel and diverse characteristics, a novel segmentation network is introduced, namely tri-level attention-based segmentation network. This network has significantly reduced semantic gaps in subsequent encoding-decoding stages, with immense parallelization of multiscale features for faster convergence providing considerable performance improvement over traditional networks. Furthermore, a novel tri-level attention mechanism has been introduced, which is repeatedly utilized over the network, combining channel, spatial, and pixel attention schemes for faster and efficient generalization of contextual information embedded in the feature map through feature recalibration and enhancement operations. Outstanding performances have been achieved in all three tasks through extensive experimentation on a large publicly available dataset containing 1110 chest CT-volumes, which signifies the effectiveness of the proposed scheme at the current stage of the pandemic.

This correspondence proposes the use of a real-only equalizer (ROE), which acts on real signals derived from the received offset quadrature amplitude modulation (OQAM) symbols. For the same fading channel, we prove that both ROE and the widely linear equalizer (WLE) yield equivalent outputs. Hence, these exhibit the same performance. Our complexity analysis finds that depending on the frame length, ROE can be computationally less complex, and save significant signal processing time over WLE. In the adaptive normalized least mean square implementation, ROE performs better with lower complexity than its counterpart, for a given number of pilot bits.

In wireless communication environments, shadow fading represents signal fluctuations around the average path loss of a transmitted signal due to the orientation of large obstructions in the way of the propagating electromagnetic waves. This paper aims at generating shadow fading maps that can be used in simulations of realistic mobile radio network scenarios. The focus is on achieving two-dimensional spatial correlation of the shadow fading values with low numerical burden. Instead of the standard filtering procedure that requires a numerically exhaustive two-dimensional convolution, we propose an iterative multi-stage algorithm that achieves close to ideal correlation properties among the shadow-faded random variables at a substantially higher computational speed.

In a cognitive wireless network, the sudden arrival of a primary user (PU) can force one or more secondary users (SU) to terminate their ongoing communication. Buffers can be utilized to prevent them from dropping, but their effectiveness depends on the tolerance of the SUs to the buffer waiting time. In this paper, we propose to dynamically assign service rates to the SUs to complement the gain offered by the network buffers in reducing the dropping probability of the SUs. Our analysis is based on a two-dimensional Markov chain with four state variables. Performance metrics for the SUs such as dropping, blocking and completion probabilities, and the average time spent in buffer are derived. Our analytical results demonstrate that depending on the network condition, the proposed dynamic spectrum assignment scheme is alone capable of reducing the dropping probability substantially. Since the sum of call completion, blocking and dropping probabilities is 1, the reduction of dropping probability of the SUs is achieved by increasing the sum of call blocking and completion probabilities, which not necessarily implies higher blocking or reduced completion probabilities.

For real-time applications running over hand-held mobile terminals in heterogeneous environments, efficient vertical handover (VH) algorithms are required in maintaining a seamless connectivity and an acceptable level of quality. While received signal strength-based methods have dominated this class of algorithms, we propose a thorough system analysis framework and perform rigorous analysis for packet-loss based algorithms for an interworking environment comprising the cellular network and the Wireless Local Area Network (WLAN). The basic VH algorithm analyzed here is based on the moving average of the packet loss rate and we employed both a simple packet loss and Gilbert packet loss pattern. Modifications to the analytical framework have been made by employing block-wise packet loss patterns in order to keep the computational burden within practical limits. Performance trends of call drop probabilities and WLAN usage efficiency are shown with varying system and handover thresholds, and analytical results are compared to that obtained from Monte Carlo simulations.

The development of handheld mobile terminals (MT) capable of operating over both Wireless Local Area Networks (WLAN) and the cellular media is an important step toward the evolution of next-generation integrated networks. For real-time applications like voice, efficient vertical handover (VH) algorithms are required in maintaining a seamless connectivity and an acceptable level of quality for mobile users in heterogeneous environments. This paper proposes an analytical method for evaluating the performance of a VH algorithm that relies on the Received Signal Strength Indicator (RSSI) samples. The system model is portrayed upon addressing relevant factors that affect the quality and continuity of a voice call, and a set of performance metrics is proposed. A rigorous signal strength time series is utilized in characterizing the instantaneous decision metrics, and a novel intermediary system model, namely the N-model, is proposed to capture the large-scale shadowing effects. The performance of a generic algorithm that relies on the RSSI, which itself is susceptible to estimation error, is evaluated for an MT roaming in and out of the WLAN coverage area. Results obtained using the analytical expressions are validated by comparing them to that obtained through Monte Carlo simulation.

With the proliferation of a multitude of diverse yet coexistent array of networks in the recent past, the heterogeneous environment is foreseen to serve mobile terminals (MT) in a complementary fashion at large. Multimodal MTs can now switch interfaces between Wireless Local Area Networks (WLAN) and the cellular network. In order to exploit the heterogeneity of the wireless environment, MTs require smart medium selection methods. In this paper, we derive a practical yet tractable method of evaluating vertical handover (VH) algorithms for mobile voice users over heterogeneous environments. The random direction and the Gauss-Markov mobility models are analyzed as an extension to the previously studied random waypoint model. The performance of a VH algorithm is evaluated for an MT roaming in and out of the WLAN coverage area under these mobility models. The analytical procedure is utilized in deriving the required signal strength thresholds upon which an MT bases its handover decisions for a given outage probability.

Dynamic spectrum allocation is the most efficient way of allocating spectrum and reliable spectrum sensing is the core functionality of that idea. While most of the energy detection techniques deal with the additive white Gaussian noise (AWGN) channel, few algorithms have been implemented to recognize vacant spectrum over frequency selective fading channels where the primary and secondary users are not mutually synchronized at the bit level. For that environment, we devise a novel technique that can efficiently detect the presence of a primary user with the help of its known symbols. Sliding window technique is used to combat the effect of interference in a low signal-to-noise ratio (SNR) environment over the fading channels with different number of channel taps. Simulation results are performed to support the analysis.

The widespread deployment of Wireless Local Area Networks (WLAN) over the last decade, and advances in wireless access technologies, have endowed handheld mobile terminals (MT) with multimodal connectivity features. Multimodal MTs can now switch interfaces between the WLAN and the cellular network, and select their network of choice in real-time. In order to exploit the heterogeneity of the wireless environment, MTs require efficient vertical handover (VH) algorithms. In this paper, we present an analytical method of evaluating VH algorithm performance for mobile voice users over heterogeneous environments. An algorithm that computes the expected WLAN-lifetime of an MT, and uses it along with the Received Signal Strength Indicator (RSSI) in determining the appropriate handover instance, is analyzed. The average number of handovers per crossover of the WLAN border region, and the average bandwidth available to the MT, are analytically derived and compared to simulation results.

In this paper, random binary phase offsets are induced into the transmitting symbols to mitigate the spatial correlation effects in a cyclic delay diversity (CDD) based MIMO-OFDM system. Our analysis reveals that depending on the channel spatial correlation, some of the sub-carriers have substantially lower average capacity than others and may, therefore, deteriorate the system performance. In such cases, the proposed scheme enables those sub-carriers to recover from correlation effects and reinstates all the sub-carriers with the same upper bound of the average capacity as offered by the uncorrelated channel. Our analysis of pairwise error probability (PEP) demonstrates the effects of spatial correlation on the squared Euclidean distance between any two codewords and shows how the proposed scheme mitigates those effects without the knowledge of the channel spatial correlation. We observe in simulation that depending on the channel spatial correlation, our proposed scheme can yield a dramatic performance improvement.

With the proliferation of a diverse array of networks in the recent past, the heterogeneous environment is foreseen to serve mobile terminals (MT) in a complementary fashion at large. Multimodal MTs can now switch interfaces between Wireless Local Area Networks (WLAN) and the cellular media. In order to exploit the heterogeneity of the wireless environment, MTs require not only to have efficient medium access schemes but also smart medium selection methods. This paper aims at evaluating the performance of such schemes analytically. A practical yet tractable method of evaluating vertical handover (VH) algorithms was developed in the authors' prior work yet a simplistic system scenario was addressed. In this paper, that framework is extended further to facilitate analyzing more realistic scenarios. Specifically, several random user mobility models are addressed here, and the prior assumptions of cellular ubiquity and stationarity of WLAN characteristics are relaxed. The performance of a Received Signal Strength Indicator (RSSI) based VH algorithm is evaluated in computing the WLAN usage efficiency and deriving the required signal strength thresholds for handover decisions that meet given target outage probabilities. An additional WLAN lifetime-based algorithm is also evaluated. Analytical results are validated by comparing them to simulation results.

In cyclic delay diversity (CDD) based multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) systems, correlation can evolve among parallel channels due to closeness of antennas or lack of scatterers in the environment. In this work, pseudo random binary phase offsets are induced into the transmitting symbols to mitigate the correlation effect. Average capacity per sub-carrier and pairwise error probability (PEP) are used as metrics to analyze the system performance for an arbitrary number of transmitting and receiving antennas. Our analysis reveals that depending on the channel spatial correlation, some of the sub-carriers have substantially lower average capacity than others and may, therefore, deteriorate the system performance. In such cases, the proposed scheme enables those sub-carriers to recover from correlation effects and reinstates all the sub-carriers with the same upper bound of the average capacity as offered by the uncorrelated channel. Our analysis of PEP demonstrates the effects of spatial correlation on the squared Euclidean distance between any two codewords and shows how the proposed scheme mitigates those effects without knowledge of the channel spatial correlation. We observe in simulation that depending on the channel spatial correlation, our proposed scheme can yield a dramatic performance improvement.

This paper presents the fixed and floating point implementations for field-programmable gate arrays (FPGA) of third-order hand tremor predictors using recursive-least square (RLS) and a proposed Kalman adaptation algorithms. The proposed algorithm outperforms RLS in convergence speed and mean square error (MSE). It also shows better numerical convergence than the RLS as the number of bits in fixed-point precision is reduced. Both fixed and floating point realizations are implemented and the hardware tradeoffs are discussed. A modified binary floating point format is proposed that takes advantage of the 18-bit hard macro multiplier within the Xilinx Virtex 5 Architecture in order to gain precision while preserving speed. The increased precision overcomes the prior known issues of explosive divergence and the stalling effect associated with the fixed point implementation of such adaptive algorithms, proving the feasibility of an FPGA based physiological hand tremor predictor.

The development of handheld mobile terminals (MT) capable of operating over both cellular networks and Wireless Local Area Networks (WLAN) is an important step towards the evolution of next-generation integrated networks. For real-time applications, maintaining a seamless connectivity and an acceptable level of quality is essential, and efficient vertical handover (VH) algorithms are required. This paper proposes an analytical framework of evaluating the performance of VH algorithms for the voice application over a WLAN/cellular inter-working environment. The performance of a generic algorithm that uses the Received Signal Strength Indicator samples to estimate the WLAN usability is evaluated for an MT roaming in and out of the WLAN coverage area under the random waypoint model. The analytical procedure is utilized in deriving the required signal strength thresholds upon which an MT bases its handover decisions, and validated through Monte Carlo simulation.

In a cognitive wireless network, sudden arrival of a primary user could force one or more secondary users to terminate their ongoing communication. This situation leads us to propose a cognitive wireless network which dynamically assigns service rates to the secondary users depending on the available network spectral resource. Our analysis is based on a two-dimensional Markov chain with three state variables. Performance metrics for the secondary users such as dropping probability, blocking probability and completion probability are derived. Our numerical result demonstrates that, depending on the network condition, the proposed dynamic spectrum assignment scheme is capable of reducing the dropping probability substantially and yielding higher throughput via increasing the maximum allowable service rate. Analysis of blocking probability implies that higher value of the maximum allowable service rate may or may not make the network more selective in terms of admitting new secondary users.

Game theory has emerged as a new mathematical tool in the analysis and design of wireless communication systems, being particularly useful in studying the interactions among adaptive transmitters that attempt to achieve specific objectives without cooperation. In this paper, we present a game-theoretic approach to the problem of joint transmitter adaptation and power control in wireless systems, where users' transmissions are subject to quality-of-service requirements specified in terms of target signal-to-interference-plus-noise ratios (SINRs) and nonideal vector channels between transmitters and receivers are explicitly considered. Our approach is based on application of separable games, which are a specific class of noncooperative games where the players' cost is a separable function of their strategic choices. We formally state a joint codeword and power adaptation game, which is separable, and we study its properties in terms of its subgames, namely, the codeword adaptation subgame and the power adaptation subgame. We investigate the necessary conditions for an optimal Nash equilibrium and show that this corresponds to an ensemble of user codewords and powers, which maximizes the sum capacity of the corresponding multiaccess vector channel model, and for which the specified target SINRs are achieved with minimum transmitted power.

Temporal fading is an inherent characteristic of wireless channels. Furthermore, in a multiuser spread spectrum network, the instantaneous value of the multiple access interference varies with time. As a consequence, the instantaneous signal-to-interference-plus-noise ratio varies from one frame to another. This variation can even occur within a given frame. In this work, we present a new set of analytical and numerical results on Incremental Spreading (IS) protocols that adaptively increase the duration of a frame, or the spreading gain, based on the past instantaneous channel and interference conditions. The control operation is carried out mainly at the receiver end, resulting in a distributed system, unlike other spreading gain control algorithms which are centralized. These protocols are ready to be implemented in single- and multi-carrier code division multiple access (CDMA) type technologies and can enhance the throughput and capacity of wireless networks.

The wide deployment of Wireless Local Area Networks (WLAN) and the advent of Third Generation (3G) networks have provided users with the flexibility of switching between dissimilar networks while running different applications. A Mobile Terminal (MT) can be equipped with multimodal functionalities, and can select the wireless interface that best suits its needs. This paper specifically focuses on the web-browsing application, and models the user-perceived performance for an MT operating over a WLAN/3G environment. A system model is proposed that facilitates performance evaluation of web-browsing sessions in terms of different network metrics. The effect of user mobility and that of variations in network characteristics are incorporated. A simulation framework has been developed and the results generated are presented to demonstrate the utility of the data-session modeling and handover algorithms proposed in this paper.

In this paper, we study the problem of optimizing the pilot-to-data power ratio (PDR) for uplink code-division multiple access (CDMA) systems with partial RAKE (PRAKE) receivers. Both code-division multiplex (CDM) and time-division multiplex (TDM) reference-assisted schemes are considered. We assume Nakagami-m fading channel with two types of power delay profile (PDP): uniform and exponential PDPs. The optimum PDR is derived via minimizing the upper bound of the probability of bit error. A closed-form expression for the optimum PDR is obtained for both CDM and TDM schemes with uniform PDP. For exponential PDP, we derive the condition satisfied by the optimum PDR and obtain it numerically. It is observed that the optimum PDR is noticeably affected by the decay factor, but not by the m-parameter. For exponential PDP, unlike for uniform PDP, the optimum PDR depends on the number of combined paths. We also show that the optimum PDR derived from the block-fading channel model performs favorably in the Jakes' model.

The development of handheld user equipments (UE) capable of operating over both cellular networks and wireless local area networks (WLAN) is an important step towards the evolution of next-generation integrated networks. For real-time applications, maintaining a seamless connectivity and an acceptable level of quality is quite important. Efficient vertical handoff algorithms are required to ensure the best exploitation of the available resources under certain quality constraints. This paper proposes a realistic performance analysis framework upon addressing relevant factors that affect the performance of a voice application within a heterogeneous network environment. While the existing works in this field relies on received signal strength (RSS) samples to estimate the WLAN usability, this paper also proposes an algorithm that takes into account the real-time packet error pattern along with RSS.

Convolutional codes provide a robust means of forward error control, especially in a harsh communication medium like a wireless channel. The use of rate compatible punctured convolutional (RCPC) codes, derived by code puncturing at the transmitter, is an established method to improve the throughput of wireless networks. In this paper, we propose to exploit the idea of code puncturing at the receiver end to improve the performance of wireless systems. It is shown that utilizing the proposed protocol yields a significant reduction in the frame error rate at the expense of a slight increase in computational complexity.

There are two code division multiple access (CDMA) systems which are capable of adapting to the time-varying nature of radio channels efficiently. In one of these systems, information symbols are transmitted simultaneously and in the other system, information symbols are chip-interleaved before transmission. Both systems exploit temporal variations in the channels so efficiently that depending on the signal-to-noise ratio values, using the estimated channel coefficients they are capable of outperforming the conventional system with perfect channel state information (CSI). In this correspondence, we analyze the relative performance behavior of these two promising fade-resistant CDMA systems. We show that both fade-resistant transmission systems exhibit identical performance when the system load is high. However, when the system load is light, the chip-interleaved system slightly outperforms the system that transmits information symbols simultaneously due to higher self-interference in the latter.

Temporal fading is an inherent characteristic of wireless channels. Also, in a multiuser spread spectrum network, the instantaneous value of the multiple access interference varies with time. As a consequence, the instantaneous signal-to-interference-plus-noise ratio varies from one frame to another. This variation can also occur within a given frame. In this work, we propose protocols, namely, soft-length frame (SOLF) protocols, that adaptively control the duration of the frame, or the spreading gain, according to the channel and interference conditions. In these protocols, the control operation is carried out mainly at the receiver end, resulting in a distributed system, unlike other variable spreading gain algorithms which are centralized. We implement these protocols in single- and multi-carrier CDMA systems and show that these protocols can enhance the throughput and capacity of wireless networks.

In this letter, we analyze the expected value of the channel energy capture as a function of the integration interval of the correlator in a transmitted reference system. A modified Saleh-Valenzuela channel model is employed. We observe that for the system specifications (such as channel model, data rate, and signal-to-noise ratio) considered here, an integration interval that captures approximately 84%-89% of the expected value of the channel energy provides a bit-error probability close to the minimum one.

In general, the instantaneous signal-to-interference-plus-noise ratio varies across a received frame. This variation is considerable in wireless systems in particular, due to the time-varying nature of wireless channels. To exploit this variation, we divide the received frame into a number of constituent mini-frames, each mini-frame containing the received versions of every symbol in the frame. We select a subset of these mini-frames, combine them and attempt to decode the frame. If this attempt fails, we select another subset of the mini-frames and make another attempt. We continue the process until the frame is decoded without errors or all predetermined subsets of the mini-frames have been exhausted. We implement the proposed protocol in a CDMA system. Our study shows that deploying our proposed protocol in a CDMA system results in a significant reduction in the frame error rate.

In general, the instantaneous signal-to-interference- plus-noise ratio varies across a received frame. This variation is considerable in wireless systems in particular, due to the time- varying nature of wireless channels and interference. To exploit this variation, we divide the received frame into a number of constituent mini-frames, each mini-frame containing the received versions of every symbol in the frame. We select a subset of these mini-frames, combine them and attempt to decode the frame. If this attempt fails, we select another subset of the mini-frames and make another attempt. We continue the process until the frame is decoded without errors or all predetermined subsets have been exhausted. We implement the proposed protocol in a code division multiple access (CDMA) system. Our study shows that deploying our protocol in a CDMA system results in a significant reduction in the frame error rate (FER).

In this paper, we address the use of a novel low-complexity receiver, namely, a reduced-complexity hybrid receiver (HR) for the downlink of a multicell CDMA system with a transmit delay diversity transmission scheme. This receiver is designed by combining the merits of the decorrelating receiver (DR) and the conventional receiver (CR). Unlike most multiuser receivers, the reduced-complexity HR operates with the same information as CR. For a target performance metric (e.g. bit error probability (BEP) = 10-2), the reduced-complexity HR significantly outperforms CR, DR, average minimum mean square error (MMSE) receiver, signal to noise ratio (SINR) maximizing (max-SINR) receiver, and reduced-complexity MMSE receiver with estimated channel information.

In this paper, we study the problem of optimizing the pilot-to-data power ratio (PDR) for uplink code-division multiple access (CDMA) systems with partial RAKE (PRAKE) receivers. Both code-division multiplex (CDM) and time-division multiplex (TDM) reference-assisted schemes are considered. We assume Nakagami-m fading channel with uniform power delay profile (PDP) and that with exponential PDP. We derive the optinum PDR via minimizing the upper bound of the probability of bit error. For uniform PDP, we present a closed-form expression for the optimum PDR. For exponential PDP, we find the condition satisfied by the optimum PDR and obtain it numerically. For exponential PDP, unlike for uniform PDP, the optimum PDR depends on the number of combined paths. However, the effect of the number of combined paths on the optimum PDR is not significant.

The time-varying nature of radio channels deteriorates the performance of a wireless system. However, there are two code division multiple access (CDMA) based transmission systems which are capable of adapting to these variations efficiently. In one of these systems, information symbols are transmitted simultaneously and in the other system, information symbols are chip-interleaved before transmission. Both systems exploit temporal variations in the channels so efficiently that using the estimated channel coefficients they are capable of outperforming the conventional system with perfect channel state information (CSI) at the receiver. In this paper, we analyze the relative performance behavior of these two promising fade-resistant CDMA systems. We show that both fade-resistant transmission systems exhibit identical performance when the system load is high. However, when the system load is light, the chip-interleaved system slightly outperforms the system that transmits information symbols simultaneously due to higher self-interference in the latter.

Time-varying multipath fading associated with the wireless link limits the capacity of a wireless system. In order to adapt to this adverse radio environment efficiently, we investigate the use of a pilot-aided fade-resistant transmission scheme for the uplink of a chip-interleaved code-division multiple-access (CDMA) system. We analyze the tradeoff between the number of diversity branches and the channel estimation error. We derive the optimum ratio of pilot signal energy to information signal energy. Our numerical study indicates that the proposed system is capable of outperforming the conventional CDMA system depending on the transmitter energy and channel condition.

Physical limitations due to fading and interference in wireless channels pose technical challenges in achieving reliable communication. To adapt to this adverse radio environment efficiently, we propose a fade-resistant transmission system based on code division multiple access (CDMA) technology. In this system, all the symbols of a user are transmitted simultaneously using parallel sequences over a time-varying wireless channel. We derive the relationship between the self-interference and the multiple-access interference in such a system. We prove that instantaneous signal-to-interference-plus-noise ratio (SINR) at the matched filter output of a system with parallel sequences is statistically higher than that of the conventional CDMA system. Numerical results demonstrate that the parallel sequence transmission scheme can provide capacity improvement over the conventional CDMA system depending on variations in the channel.

To adapt to the adverse radio environment efficiently, we address the use of a pilot aided multicode code division multiple access (CDMA) system. This system is implemented by transmitting all the information symbols together with the pilot symbols of a user simultaneously over the wireless channel. We analyze the trade-off between the diversity order and the channel estimation error in the performance of the proposed system. Our numerical results indicate that depending on the transmitter power and the channel condition, the proposed system is capable of outperforming the conventional CDMA system with known channel state information at the receiver.

Interference and fading inherent to the radio channel limit the capacity of wireless systems. To overcome these impairments, we adopt parallel symbol transmission scheme and propose a protocol that adjusts the duration (or length) of symbols based on the past instantaneous channel and interference conditions. We demonstrate that the proposed system can provide performance improvements over the existing systems.

The capacity of a wireless system is subject to bandwidth constraints, fading, as well as temporal and spatial variations in data traffic. To adapt to this adverse radio environment efficiently, we propose a fade resistant transmission system using parallel sequences. Our analysis shows that instantaneous signal-to-interference-plus-noise ratio at the matched filter output of the proposed system is statistically higher than that of the conventional system. Numerical results demonstrate that the proposed parallel sequence transmission scheme can provide capacity improvement over the conventional system depending on variations in the channel.

Performance of a parallel symbol transmission scheme is analyzed in time-varying Nakagami fading channels. We show that instantaneous signal-to-interference-plus-noise ratio of the parallel symbol transmission scheme at the matched-filter output is higher than that of a conventional system. Furthermore, the performance gain of the parallel symbol transmission scheme over the conventional system increases as the number of independent fades within the frame increases and/or the Nakagami parameter m decreases.

The paper quantifies the robustness of linear receivers, such as minimum mean-squared error and decorrelating receivers against the near-far problem in chip asynchronous direct-sequence code-division multiple-access systems with random signatures, where both of those linear receivers achieve the optimum near-far resistance. Due to the asynchronism of the system, different symbols of a user see different interference structures which affect their performance differently. Thus, instead of concentrating on any particular symbol of a user, we analyze the average optimum near-far resistance of a randomly selected symbol of that user by providing simple tight upper and lower bounds on it.

For a multicell code-division multiple-access (CDMA) system, we propose a partial decorrelator that decodes a user by suppressing only the in-cell interferers. As a result, each user suffers only from other-cell interference and enhanced receiver noise. By analysis, we show that in random CDMA systems, the partial decorrelator outperforms the conventional receiver, within the operating regime of the conventional receiver. In simulation, we observe that when users have equal received powers at their respective receivers, a multicell system with partial decorrelator receivers yields roughly 1.5 times the capacity of the conventional system.

This paper examines the robustness of the linear receivers, such as the MMSE and the decorrelating receivers, against the near-far problem in chip asynchronous random DS/CDMA systems. In asynchronous CDMA systems, both of those linear receivers achieve the optimum near-far resistance by employing infinite-bit-long observation windows. We develop simple tight upper and lower bounds on the average optimum near-far resistance. It is shown that the average optimum near-far resistance of the asynchronous system is upper bounded by that of the synchronous system. These bounds converge to the average optimum near-far resistance of the synchronous system as the processing gain and the number of users approach infinity. A simulation study was performed to characterize the average optimum near-far resistance for finite processing gain systems.

We integrate power control with transmit diversity in the down-link to increase the capacity of third-generation (3-G) CDMA systems. First, we investigate the system performance by using power control with the conventional receiver. Here our goal is to minimize the total transmitted power by the system subject to the signal-to-interference ratio (SIR) requirements of users. We select the antenna weights of a user in such a way that the received power of that user is maximized. It is observed that the conventional system fails quickly to meet the SIR requirements as the number of users grows. To handle this situation, we propose an interference suppression technique with power control in the down-link. Under the proposed scheme, a base station simply employs the same weights at all the antennas and a user requires to know only its spreading sequences. In both cases, the power control algorithms are iterative, distributed and asynchronous. Convergence of those iterative algorithms have been shown for a multi-cell CDMA system. An experimental study is performed to compare the performance of both power control algorithms.

This paper examines truncated window decorrelators for an asynchronous direct-sequence code-division multiple-access system supporting users transmitting at different bit rates. We decode a user by extending the observation window over a sufficient number of its bits. To characterize practical window sizes, simple upper and lower bounds for the asymptotic efficiency of both the truncated window and infinite window decorrelators are developed. Empirical results show that as the length of the observation window increases, the bounds converge rapidly to the asymptotic efficiency of the infinite window decorrelator. The complexity of the receiver depends strongly on the ratio of the maximum to minimum bit rates.

For code-division multiple-access (CDMA) wireless systems employing multiuser detection, the varied bit-error rate (BER) requirements of multimedia traffic dictate the use of transmitted power control. Using a decorrelator in an asynchronous multirate direct-sequence CDMA system, it may be necessary for different users to combat the noise enhancement and the propagation losses to varying degrees depending on individual requirements. In this context, we propose a power control algorithm for a multirate decorrelator that is suitable for a class of BER-based link quality objectives. If the uplink channel gain of the desired user is known, then it is straightforward for each user to choose the transmitted power needed to meet its target BER objective. In practice, however, the uplink channel gain is often difficult to measure. To avoid this measurement, we employ stochastic approximation methods to develop a simple iterative power control algorithm. In this algorithm, each mobile uses the output of its own decorrelator to update its transmitted power in order to achieve its BER objective. We show that when a user's bits have nonzero asymptotic efficiencies, the power control algorithm converges quickly in the mean square sense to the minimum power at which a user achieves its quality-of-service objective.

This paper proposes a signature assignment technique for a dual rate DS/CDMA system that serves both low bit rate and high bit rate users. In an interval of duration T/sub 0/, a low rate user transmits one bit while a high rate user transmits M bits. Under the new signature sequence assignment technique, M low rate users share the signature of a single high rate user without wasting bandwidth. Based on the signature assignment technique, we propose a decorrelator that generates bit decisions for each high rate user in every subinterval of duration T/sub 0//M. In order to decode a low rate user, an orthogonal projection is applied to M separate decorrelated outputs of each low rate user. It is observed that applying a standard decorrelator to the interval of duration T/sub 0/ yields a computational complexity that grows with M. The proposed decorrelator significantly reduces the computational complexity of the standard decorrelator. Due to the structural simplicity, the proposed receiver slightly suffers in terms of bit error rate. However, it is observed that in several cases, the proposed receiver achieves the standard decorrelator performance.