Air-to-Ground (A2G) integration offers a more promising solution than satellite links, due to lower latency and higher throughput. However, this integration faces significant challenges, particularly co-channel interference, which necessitates the development of advanced interference mitigation strategies. This paper investigates the coexistence of aerial uplink (UL) and ground downlink (DL) communications in dynamic Time-Division Duplexing (D-TDD) systems, where UL transmissions from aerial users introduce severe interference to the DL transmissions of TN users. To address the issue of user-to-user interference (UL-DL) in A2G system, this work proposes a novel Codebook-Based Interference Mitigation (CBIM) framework that incorporates a sliding codebook approach for radio frame configuration (RFC) selection and a dynamic subframe swapping mechanism to resolve subframe misalignments and reduce interference. By optimizing subframe arrangements, the framework effectively minimizes interference while improving resource utilization. Simulation results demonstrate the framework’s effectiveness, achieving a 20.37% reduction in interference and a 28.21% increase in throughput, establishing CBIM as a robust and efficient solution for the future TN-NTN integration in next-generation communication systems.

The evolution toward 6G wireless networks has positioned Non-Terrestrial Networks (NTN) as critical enablers for ubiquitous global connectivity. Among NTN architectures, Very Low Earth Orbit (VLEO) satellites operating in Ka-band frequencies offer superior link budgets and reduced latency. However, extreme orbital velocities reaching 7.7 km/s introduce severe carrier frequency offset (CFO) challenges spanning multiple subcarrier intervals far beyond conventional estimation capabilities. Unlike terrestrial systems where CFO remains within fractional subcarrier bounds, VLEO systems experience massive Doppler shifts that degrades OFDMA subcarrier orthogonality, transforming carefully designed waveforms into interference-dominated signals. Existing approaches exhibit significant performance degradation because they treat integer and fractional CFO estimation as independent sequential problems, ignoring their fundamental coupling and creating error propagation leading to sustained synchronization failures. This paper presents a dual-head Temporal Convolutional Network (TCN) architecture that addresses the coupled integer-fractional CFO estimation problem through unified machine learning. Our two-stage framework employs Stage 01 for wide-range coarse acquisition using dual-head TCN to jointly estimate integer and fractional components, while Stage 02 provides precision tracking through optimized phase-locked loop techniques for small residual offsets. Comprehensive simulations across extreme VLEO scenarios for both ground and aerial users demonstrate strong system-level performance: 97.7% integer classification accuracy, 0.1229 fractional estimation RMSE, and bit error rate within 0.1 dB of ideal compensation, showing a substantial performance improvement over existing methods that suffer system performance degradation under high-Doppler conditions. Furthermore, backbone comparisons against CNN, LSTM, and Transformer architectures confirm the TCN’s superior accuracy-complexity trade-off, and ablation experiments verify the necessity of each architectural component.

Energy-aware mobility management in dense Fifth Generation (5G) networks is increasingly challenged by frequent handovers and unnecessary activation of sleeping next-generation NodeBs (gNBs), which lead to excessive energy consumption and degraded mobility reliability. Conventional Xn-based handover schemes rely on static radio thresholds and implicitly assume always-active gNBs, while existing NWDAF-enabled approaches improve stability but do not explicitly account for energy costs during handover execution. To address these limitations, this paper proposes theIntelligent Energy-Aware Handover Framework(IEAHF), a NWDAF-orchestrated architecture that integrates coordinated agent-based control for energy-aware mobility management. The proposed framework introduces anEnergy-Aware Handover Optimization Agent (EA-HOA)to guide reliability-driven handover decisions and aHandover Energy Evaluation Agent (HEEA)to assess the energy impact of candidate handover actions, with both agents operating within a closed-loop control process enforced through Operations, Administration, and Maintenance (OAM). By reformulating handover success to incorporate energy inefficiency and enabling per-handover gNB energy reasoning at decision time, IEAHF jointly optimizes service continuity and energy efficiency. System-level simulations demonstrate that the proposed Agent-NWDAF configuration consistently outperforms baseline and analytics-only schemes, achieving tightly concentrated Energy-Aware Handover Success Rates of approximately 0.98, reducing the Energy-Aware Handover Failure Rate to the range of 0.007–0.015, and delivering up to a 32% reduction in average gNB power consumption relative to an always-on baseline. These results indicate that IEAHF provides a scalable and effective solution for energy-efficient mobility management in 5G networks and establishes a foundation for energy-aware handover control in future Sixth Generation (6G) systems.

The goal of multi-object tracking (MOT) is to estimate the location of objects and maintain their identities consistently to yield their individual trajectories. It has become a trend to fuse multi-sensor information to achieve 3D MOT, since it can leverage the advantages of different sensors to enhance tracking performance. However, it is a challenging work due to the necessity of fusing features with diverse attributes and wrong association caused by significant noise. In this paper, we propose adaptive weight parameter-based multi-feature fusion to create affinity function, alongside adaptive setting of data association searching range, aiming to augment camera-Lidar information fusion-based MOT framework. First, detected results from these two sensors are divided into three categories. Then, to fully utilize both motion and appearance information, adaptive weight parameter setting is proposed to embed appearance information into motion information, forming the basis for creating an affinity function for data association. Furthermore, to mitigate wrong association caused by object temporary occlusion or out-of-view, a method for adaptively adjusting the association searching area is introduced based on the number of frames in which tracking trajectories disappear. Finally, to prevent appearance information pollution caused by significant noise, a confidence score-based tracking trajectory appearance feature updating strategy is explored. The experiment results on KITTI and nuScenes MOT benchmark show remarkable performance improvement over other state-of-the-art MOT methods and demonstrate the effect of our designed modules.

Feature pyramid network (FPN) can highly improve the performance of object detection by extracting multiscale features. However, current FPN-based methods suffer from intrinsic correlation of local information loss in each feature map, which brings about the semantic information effective transmission problem. In addition, 1 × 1 convolution in lateral connection of FPN may cause spatial information loss. In this article, we propose a novel semantic and spatial information enhancing feature pyramid network (Dual SIE-FPN), which mainly focuses on alleviating multiscale hierarchical feature transmission loss and enhancing the feature representation. Specifically, Dual SIE-FPN contains three modules: Lateral Feature Enhancement (LFE), Global Attention Upsampling (GAU), and Multiple Information Compensation (MIC). LFE is designed to capture deep semantic representation and enhance channel information. GAU is established to make up for spatial information loss caused by upsampling, and transmit the high-level features with the compensatory information to low-level features simultaneously. MIC is designed to work with LFE in parallel to further improve the information loss resulting from 1 × 1 convolution. Experimental results on MS COCO and UAVDT dataset demonstrate that Dual SIE-FPN achieves competitive performance compared to other state-of-the-art FPNs. In addition, our proposed Dual SIE-FPN can be embedded into any multiscale feature extraction-based computer vision tasks to improve the performance.

A device‐to‐device (D2D) discovery scheme is key enabler for proximity‐based services in third generation partnership project long‐term evolution‐advanced systems for public safety (PS) and general LTE scenarios. The deployment of D2D networks results in severe co‐channel interference between conventional cellular users and D2D users, and faces proximity interference management challenges because of the co‐existence of multiple D2D users. We propose a time and energy‐efficient contention‐resolving device discovery resource allocation (TEECR‐DDRA) scheme that has the capability to enhance the success ratio for discovery of D2D users by reducing collisions among users. Moreover, the proposed TEECR‐DDRA scheme has the ability to prioritise PS users to meet their QoS and latency requirements. Furthermore, multi‐channel slotted ALOHA with energy sensing can be used to increase the probability of successful discovery of non‐PS users. This ability helps to reduce the discovery time of PS users under disaster scenarios, and also reduces the energy consumption of non‐PS users by minimising the number of beacon retransmissions. System‐level simulations show that the proposed TEECR‐DDRA scheme performs remarkably well under D2D network. Compared with the conventional random access scheme, the proposed scheme almost doubles the discovery range and significantly improves the success ratio for discovery of D2D users.

The use of polarized antenna systems has been receiving considerable attention. However, few studies have addressed to characterize the cross-polarized multiple-input multiple-output (MIMO) channel modeling. In this paper, we consider a scenario where receiver with the dual-polarized antennas moves far from the transmitter. Thus, the incoming signal can be treated to be parallel to the polarized antenna X-Y plane. Different from the conventional polarized MIMO channel models, such as spatial channel model extended (SCM-E) and the polarized channel model in IEEE 802.20 which only produce single output of complex channel gain for each individual time instance or lack of the consideration of variable mobility, the proposed channel model is simple and practical to exploit MIMO spatial multiplexing and/or diversity gains by relying on a limited number of physical parameters. As a result, beamforming technology is easy to be implemented and analyzed under the proposed channel model. The performance of polarized antenna systems with beamforming technology is finally evaluated via a detailed analysis on bit-error-rate (BER) in this paper.

PHY of ship ad-hoc network (SANET) based on 3GPP LTE and IEEE 802.11p (WAVE) specifications are implemented. However, the measured maritime channel has a longer delay spread (DS) than the length of guard interval (GI) of both 3GPP LTE and IEEE 802.11p systems. For the purpose of eliminating severe inter-symbol interference (ISI) due to insufficient GI length, double antenna pattern scheme and advanced time domain decision-feedback equalizer (DFE) are respectively suggested for those two systems.

TransferJet is a new type of close proximity wireless transfer technology, which can achieve high speed transmission by touching two electronic devices. This paper overviews this novel transmission architecture and simulates its performance under white Gaussian noise (AWGN) channel. In addition, we propose a multiple access scheme on TransferJet by modifying the function of data spreader, and we also observe the link performance of the proposed scheme.

Three scalar quantization strategies for practical codebook generation are proposed in this paper. All of these three strategies are implemented in MISO beamforming systems. Achievable capacities of these scenarios are derived and discussed. The numerical results show that our proposed codebook generation strategies have lower computational burden compared with other strategies based on higher dimensional vector quantization, and provide quite a small capacity loss only. Furthermore, our ongoing work shows that the proposed strategies work well for MIMO precoding systems also.

One of the most attractive research topics about multiple-input multiple-output (MIMO) techniques is interference mitigation with limited feedback. Codebook design based on the vector quantization (VQ) algorithms with less quantization error and computational burden is the key for the codebook based precoding. Novel VQ algorithm is proposed in this paper which needs less execution time and less n umber of iterations to converge than conventional VQ Linde-Buzo-Gray (LBG) algorithm. The discussions and simulation results show that great benefits are achieved by the proposed algorithm.

Lenstra-Lenstra-Lovasz (LLL) algorithm, which is one of the lattice reduction (LR) techniques, has been extensively used to obtain better basis of the channel matrix. In this paper, we jointly apply Seysen's lattice reduction algorithm (SA), instead of LLL, with the conventional linear precoding algorithms. Since SA obtains more orthogonal lattice basis compared to that obtained by LLL, lattice reduction aided (LRA) precoding based on SA algorithm outperforms the LRA precoding with LLL. Simulation results demonstrate that a gain of 0.5dB at target BER of 10-5is achieved when SA is used instead of LLL for the LR stage.

Tomlinson-Harashima precoding (THP) is considered as a prominent precoding scheme due to its capability to efficiently cancel out the known interference at the transmitter side. Therefore, the information rates achieved by THP are superior to those achieved by conventional linear precoding schemes. In this paper, a new lower bound on the achievable information rate for the regularized THP scheme under additive white Gaussian noise (AWGN) channel with multiuser interference is derived. Analytical results show that the lower bound derived in this paper is tighter than the original lower bound particularly for a low SNR range, while all lower bounds converge to 0.5·log2(6SNR/¿e) as SNR¿¿.

In the downlink of 3GPP LTE system, primary synchronization signal (PSS) and secondary synchronization signal (SSS) sequences are used for initial cell search and synchronization. The user equipment (UE) detects slot timing, frequency offset, and cell ID by PSS in the time domain. After Fast Fourier Transform (FFT), it detects frame timing, cell group ID, and cyclic prefix (CP) length by using SSS in the frequency domain. But in 3GPP LTE system, there are two kinds of CP length, so we operate FFT twice with different CP length. In this paper, we propose a CP length pre-decision metric which is able to reduce the arithmetic complexity by half at most, with negligible performance degradation.

In the uplink of OFDMA (Orthogonal Frequency Division Multiple Access) based M-WiMAX (Mobile-Worldwide Interoperability for Microwave Access) system, linear phase shift is caused by signals transmitted from multiuser with different delay time and thus, MAI (Multiple Access Interference) occurs. MAI degrades the performance of ranging code detection and delay time estimation in the uplink. Therefore, in this paper, we propose a ranging algorithm, applying SIC (Successive Interference Cancellation) to the conventional ranging algorithm, for the MAI minimization and ranging performance improvement. The proposed ranging algorithm is verified through a Monte Carlo simulation, which shows the enhanced performance of ranging code detection and delay time estimation compared to the conventional algorithms.

In this paper, we address the transmit antenna selection in multi-user MIMO systems with precoding. The optimum and reduced complexity sub-optimum antenna selection algorithms are introduced. QR-decomposition (QRD) based antenna selection is investigated and the reason behind its sub-optimality is analytically derived. We introduce the conventional QRD-based algorithm and propose an efficient QRD-based transmit antenna scheme (maxR) that is both implementation and performance efficient. Moreover, we derive explicit formulae for the computational complexities of the aforementioned algorithms. Simulation results and analysis demonstrate that the proposed maxR algorithm requires only 1% of the computational efforts required by the optimal algorithm for a degradation of 1dB and 0.1dB in the case of linear zero-forcing and Tomlinson-Harashima precoding schemes, respectively.

Fixed-complexity sphere decoder (FSD), which consists of ordering stage and tree-search stage, achieves a quasiML performance while requiring a fixed computational effort independent of the noise power and channel conditioning. Nevertheless, it requires a specific signal ordering using the VBLAST algorithm which has a high complexity due to the iterative pseudo-inversion of the channel matrix. In this paper, we propose two schemes to reduce the complexity of FSD algorithm in the ordering and tree-search stages, respectively, while achieving quasi-ML performance. In the ordering stage, we propose QR-decomposition-based FSD signal ordering (FSDSQRD) that requires only a few number of additional complex flops compared to the unsorted QRD. In the tree-search stage, we introduce a threshold-based complexity reduction approach for FSD depending on the reliability of the signal with the lowest received SNR. Numerical results show that in a 4×4 system, the proposed FSD-SQRD requires only 17.2% of the computational efforts required by a reduced-complexity VBLAST approach. Moreover, using 16-QAM, simulation results show that when the proposed threshold-based approach is employed, FSD requires only 69.5% of its full complexity.

QR-decomposition with M-algorithm (QRDM) achieves quasi-ML performance in multiple-input multiple output (MIMO) multiplexing systems. Nevertheless, QRDM performs avoidable computations because of its systematic search strategy and its unawareness of the channel and noise conditions. Another drawback is that QRDM has a sequential nature which limits the capabilities of pipelining. In this paper, we propose semi-ML adaptive parallel QRDM (APQRDM) and iterative QRDM (AIQRDM) algorithms based on set grouping. Using the set grouping, the tree-search stage of QRDM algorithm is divided into partial detection phases (PDP). Therefore, when the tree search stage of QRDM is divided into 4 PDPs, the APQRDM latency is one fourth of that of the QRDM, and the hardware requirements of AIQRDM is approximately one fourth of that of QRDM. Moreover, simulation results show that in 4 × 4 system and at Eb/Noof 14 dB, APQRDM decreases the average computational complexity to approximately 43% of that of the conventional QRDM. Also, at Eb/Noof 0 dB, AIQRDM reduces the computational complexity to about 54% and the average number of metric comparisons to approximately 10% of those required by the conventional QRDM and AQRDM.

Radio frequency identification (RFID) system is a contactless automatic identification system, which comprises readers and tags. In RFID systems, a reader collision occurs when the communication between one reader and the tags is interfered by the signals from other readers. The reader collision problem is considered as the fundamental problem affecting high density RFID reader installations. In this paper, we analyze the conventional reader anti-collision algorithms. We also propose a pulse protocol-based reader anti-collision algorithm using slot occupied probability. The implementation of this improvement is simple but effective to mitigate most of the reader collisions in dense reader mode as shown in our simulation. That is, the proposed algorithm reduces the identification time, and increases system throughput compared with the conventional reader anti-collision algorithms.

Abstract Adaptive modulation and coding (AMC) is a well‐known technique that selects a suitable modulation level and coding rate according to the user's channel quality. The utilization of AMC in downlink (DL) requires the channel information of each user on DL to properly select the modulation and coding scheme (MCS) level. However, under a practical OFDMA system environment, it is unsuitable to feedback all the channel information over the whole frequency resources due to the limited uplink bandwidth. In this paper, to optimize the performance of the AMC system and to reduce the uplink feedback requirement, we propose a flexible block‐wise loading (FBL) algorithm combined with a novel channel quality information (CQI) feedback scheme requiring less number of CQI feedback bits, which is suitable for the general OFDMA system with AMC. The proposed FBL algorithm dynamically allocates groups of sub‐carriers to each user in DL based on the channel quality information encapsulated in a newly defined feedback signal format. As a result, the sector throughput and outage performance is improved due to the flexibility on the sub‐channel allocation and increased accuracy on the CQI feedback information by the proposed FBL algorithm. Copyright © 2008 John Wiley & Sons, Ltd.

Cooperative relaying permits one or more relay to transmit a signal from source to destination, thereby increasing network coverage and spectral efficiency. The performance of cooperative relaying is often measured as outage probability. However, appropriate measure for the channel quality is outage capacity. Although outage probability for cooperative relaying protocol has been analyzed before, very little research has been addressed for outage capacity. This paper is the first of its kind in which we derive a closed-form analytical solution of outage capacity using fixed decode and forward relaying and amplify and forward relaying in dissimilar Rayleigh fading channels, considering channel coefficients known to the receiver side. Analytical results show a tradeoff between SNR and number of relays for specific outage capacity. From the comparison between decode and forward relaying and amplify and forward relaying, it is observed that decode and forward relaying outperforms amplify and forward relaying for a large number of relays.

EPCglobal Gen2 for passive RFID system uses probabilistic slotted ALOHA with Q algorithm, which is a kind of dynamic framed slotted ALOHA (DFSA), as the tag anti-collision algorithm. In this paper, we analyze the performance of Q algorithm used in Gen2 and compare the tag estimation methods for DFSA. We also propose a new hybrid anti-collision Q algorithm, which combines the conventional Q algorithm with Chebyshevpsilas inequality. The simulation results show that the proposed algorithm outperforms the conventional Q algorithm. That is, the proposed algorithm reduces the total number of slots and increases the throughput and system efficiency compared with the conventional Q algorithm used in Gen2.

AMC (Adaptive Modulation and Coding) is a well-known technique that selects a suitable modulation level and coding rate according to the user’s channel quality. The utilization of AMC in DL (downlink) requires the DL channel information of each user to properly select the MCS (Modulation and Coding Scheme) level. However, under a practical OFDMA system environment, it is unsuitable to feed back all the channel information over the whole frequency resources due to the limited uplink bandwidth. In this paper, to optimize the performance of the AMC system we propose a FBL (Flexible Block-Wise Loading) algorithm) combined with a novel CQI (Channel Quality Information) feedback scheme with a reduced number of required bit. The proposed FBL algorithm dynamically allocates groups of sub-carriers to each user based on the channel quality information in a newly defined feedback signal format, thereby improving the sector throughput and outage probability performance.

In this paper, we analyze the M-WiMAX UL capacity limits under 2-tier cell layout, considering the effects of random user position, path loss models, fading channel and adjacent channel interference from WCDMA downlink. To account for the requirement of the system packet error rate and the supported MCS (modulation and coding scheme) levels, we propose a MCS-based capacity analysis method, which is verified through system-level Monte-Carlo simulation. Furthermore, a comparison between the conventional Shannon method and the proposed MCS-based method is presented.

This paper introduces a novel channel prediction technique for OFDM/FDD system to support adaptive modulation and coding (AMC) scheme over rapidly time-varying multipath fading channel. Most channel prediction techniques assume that there is no channel variation in the predefined time duration, e.g., a slot. As a result, those techniques can not compensate the degradation of packet error rate (PER) performance resulting from the rapid variation of channel over the slot duration. In this paper, we propose a novel channel prediction technique that considers the time-varying nature of channel over the duration of interest. Simulation results show that the AMC scheme of OFDM/FDD system utilizing the proposed channel prediction technique can guarantee the target PER of 1% without any loss of system throughput compared with the case supported by the conventional channel prediction under ITU-R Veh A 30 km/h.

Recent studies on downlink resource allocation algorithms applying SDMA have achieved the maximization of system throughput and cell coverage in a single cell environment only. In this paper, we propose an OFDM/SDMA-based downlink resource allocation algorithm that considers QoS parameters of traffic data, while minimizing the loss of system throughput under a multi-cell cellular environment in order to account for inter-cell interference from adjacent cells. We manifest the performance of the proposed algorithm under a SCME (spatial channel model extensions) MIMO channel model.

This paper introduces a reuse partitioning-based dynamic channel allocation algorithm that guarantees quality of service (QoS) by considering fairness among mobile stations in an OFDMA/FDD system. To improve the SINR values for users around the cell edge and increase the overall system throughput compared with the conventional OFDMA/FDD system of frequency reuse factor (FRF) 1, an effective transmit power allocation algorithm is also combined with the proposed dynamic channel allocation to adjust the transmit power per user according to the average received SINR value. Simulation results show that the proposed DCA algorithm increases the sector throughput by about 25% when compared with the conventional case that do not apply the proposed DCA algorithm. When the proposed transmit power allocation algorithm is combined with the proposed DCA algorithm, a further increase in the sector throughput of about 6% is achieved than when using just the proposed DCA algorithm.

This paper solves the problem of finding an intelligent subchannel allocation method to communicate with multiple users in OFDMA wireless systems. We propose an ASA (aggressive sub-channel allocation) algorithm, which is an intelligent dynamic channel allocation algorithm considering all users' channel state information conditionally to maximize throughput in an OFDMA system. We compare the ASA algorithm with round-robin, PF (proportional fair) and ACG (amplitude craving greedy) in the 2-tier cell environment and then analyze the performance of each algorithm through computer simulation in downlink OFDMA system. Simulation results show that the proposed ASA algorithm gets 24 %, 16 % and 14 % better ring throughput compared with the round-robin, PF and ACG, respectively

OFDM/OQAM-IOTA system requires the IOTA (isotropic orthogonal transform algorithm) function that has superior localization property in the time and frequency domain instead of the guard interval used in conventional OFDM/QAM system to be robust to multi-path channel. However, conventional channel estimation scheme is not valid for the OFDM/OQAM-IOTA system due to the intrinsic inter-symbol interferences of the IOTA function. In this paper, we derive the condition to make the intrinsic interferences of the IOTA function zero based on the proposed pilot structure for the perfect channel estimation. We also derive the preamble structure appropriate to the practical channel estimation for the OFDM/OQAM-IOTA system, and the simulation results show that the OFDM/OQAM-IOTA system with the proposed preamble structure performs better than the conventional OFDM system with the additional advantage of the increased transmission rate as the amount of the guard interval.

In this paper, we introduce a successive cancellation channel estimation scheme based on the preamble structure suggested in the DS-UWB proposal of IEEE P802.15.TG3a. In order to improve the transmission efficiency, we reduce the length of preamble defined in the proposal without sacrificing the channel estimation performance. The gain on the transmission efficiency is discussed for different data rates. In addition, we present the packet-error-rate (PER) and bit-error-rate (BER) performances to set the appropriate number of Rake fingers under the given requirement of the error rate criterion, applying channel estimation based on the proposed successive cancellation. A performance comparison of the finger combining methods of maximal-ratio-combining (MRC) and equal-gain-combining (EGC) applying the proposed preamble is also presented.

This paper validates the performance of wideband CDMA UE modem under the propagation conditions specified in 3GPP TS25.101. The performance graphs in this paper are obtained via Monte-Carlo simulation over a finite measurement period using the HW-equivalent fixed-point model. Employed top-down design methodology and corresponding work efforts on each task are stated to demonstrate the effectiveness of the methodology.

In the coherent CDMA systems with adaptive antenna arrays, two representing architectures for the spatial-temporal CDMA demodulator are demonstrated based on the method of weight vector multiplication, which are chip-level beamforming and symbol-level beamforming. Depending on the architecture, the implementational complexity differs by 1.5/spl sim/2.5 times. Moreover, the performance due to the method of searcher beamforming and finite word-length (FWL) effects is tightly related to the architecture of the spatial-temporal demodulator. Various beamforming algorithms are also compared in their performance under each architecture.

A loss of subchannel orthogonality due to time-variant multipath channels in orthogonal frequency division multiplexing (OFDM) systems leads to interchannel interference (ICI) which increases the error floor in proportion to the Doppler frequency. A simple frequency-domain equalization technique which can compensate for the effect of ICI in a multipath fading channel is proposed. In this technique, the equalization of the received OFDM signal is achieved by using the assumption that the channel impulse response (CIR) varies in a linear fashion during a block period and by compensating for the ICI terms that significantly affect the bit-error rate (BER) performance.

In this paper, an equalization technique for OFDM and MC-CDMA systems in a time-varying multipath fading environment is described. A loss of subchannel orthogonality due to time-variation of multipath channels leads to interchannel interference (ICI) which increases the error floor in proportion to Doppler frequency. A simple frequency domain equalizer which can compensate the effect of time-variation in a multipath fading channel is proposed by taking into account only the ICI terms significantly affecting the error performance and by modifying the previous frequency-domain equalization techniques. The effectiveness of the proposed approach is demonstrated via computer simulation by applying it to OFDM system when the multipath fading channel is time-varying.

In this paper, an adaptive data predistortion technique which can compensate for the nonlinear effect of a TWT high-power amplifier (HPA) in orthogonal frequency-division multiplexing (OFDM) systems is proposed. It is shown that the convergence time and MSE of an adaptive data predistorter can be significantly reduced by using a broadcasting technique and by designing appropriate training signals.

Direct sequence (DS) code-division multiple-access (CDMA) is a modulation and multiple access technique currently being implemented in digital cellular mobile radio communication systems. The conventional quasisynchronous (QS) DS-CDMA communication system is generalized, and the problem of optimal spreading pseudonoise (PN) sequence design for new QS DS-CDMA communication systems is formulated. The classes of optimal PN sequences which have good pseudo-randomness and very small cross-correlation values for some range of offsets are designed by using a matrix-based approach. In contrast to the case of the other sequences, the optimal PN sequences produce small multiple-access interference (MAI) which is not affected by the number of users if there are sufficiently large number of users in the link. The new results are compared with the commonly used PN sequences to prove the superiority of our designed sequences, and the system performance of the QS-CDMA systems using different PN sequences are also evaluated.

Based on the properties of wavelet orthogonal basis, three novel wavelet-based multi-carrier CDMA (MC-CDMA) systems are proposed, and their advantages and performances are investigated by the comparison with the conventional MC-CDMA systems. For the additive white Gaussian noise (AWGN) channel, all three wavelet-based MC-CDMA systems possess the same bit error rates as the corresponding MC/BPSK-CDMA and MC/QPSK-CDMA systems, but have significant higher bandwidth efficiency than the conventional MC-CDMA systems by the suitable choice of wavelet functions. Their potential applications in the broadband wireless communications to improve bandwidth efficiency and combat the fading and narrowband interference are also discussed.

No abstract available.

The improved minimum-order augmented pipelining (IMAP) algorithm, which belongs to the class of the clustered look-ahead (CLA) technique, is proposed in this paper. IMAP algorithm is optimized in the aspects of the minimization of augmented pipelining order and undesirable quantization effects simultaneously. The proposed 1-D IMAP digital filter can be easily transformed to the 2-D structure for fast video signal processing. This IMAP digital filter is especially suitable for highly computing oriented video signal processing algorithms such as spatio-temporal filtering, motion estimation or bandwidth reduction algorithm.

In this paper, the problem of optimal PN sequence design for quasi-synchronous (QS) DS-CDMA communication systems is formulated, and classes of optimal PN sequences which have good pseudorandomness and small cross-correlation values for some range of offsets are designed. The new results are compared with the commonly used PN sequences, and the system performances of the QS CDMA systems using different PN sequences are also evaluated.

The overall performance of Minimum Augmented Pipelining (MAP) filters, which belong to the class of Clustered Look-Ahead (CLA) filters is extensively analyzed to compare with the performance of Scattered Look-Ahead (SLA) filters with decomposition. Complexity, stability, quantization noise including overflow nonlinearities and the optimality of the algorithm itself are considered for the second-order prototype filter.>

Unified statistical coefficient quantization (SCQ) and round-off noise (RON) analysis for a fixed-point arithmetic model is applied to scattered look-ahead (SLA) with power-of-two decomposition filters. Assumptions under which noise power due to SCQ is the same as RON under single length accumulation are derived. Analytical results are derived for first-and second-order direct-form (DF) and minimum roundoff noise (MRON) basis filters which contradict previous claims. The application of SLA is shown to slightly increase noise for poles near z=0 and to generally decrease noise near mod z mod =1, except that the noise of DF SLA increases greatly for small regions near mod z mod =1 due to closely spaced poles.>