Spectrum sharing enables multiple wireless technologies—either from different standards (e.g., 4G and 5G) or different protocols of the same standard (e.g., IEEE 802.11 family of protocols)—to operate within the same frequency band with minimal interference. A wireless system that shares spectrum with signal/protocol awareness can allocate more spectrum for dynamic channel access. This paper introduces a Transformer-Based algorithm developed specifically for Wireless Local Area Network (WLAN) radio protocol recognition, leveraging low-cost SDR-based spectrum sensing capabilities. Unlike traditional approaches that require gigabytes of training data, our method achieves satisfactory results using only 100k (approximately 100–400megabytes of data) samples in total. The paper makes three key contributions: First, the model is trained on only 33k samples per protocol using a customized Transformer tailored for protocol classification. Second, over-the-air test datasets demonstrated near-perfect detection accuracy (exceeding 99%) at 20 dB signal-to-noise ratio (SNR) and above, enabling SDR-based spectrum sensing. Third, experiments conducted with real WLAN traffic generated using development boards achieved detection accuracy of at least 96%. We compared our Transformer-Based model with CNN and MLP classifiers and found that it consistently outperformed them in protocol recognition, even with minimal training data. Our findings suggest that intelligent spectrum sensing is achievable using low-cost devices, and that algorithms trained on compact datasets can attain state-of-the-art detection accuracy.

To achieve radio spectrum awareness for current and next generation wireless communication systems, it is critical to develop the capability of super-wideband spectrum sensing with low-cost devices. In this paper, we report a novel wideband sensing structure that uses an analog-to-digital converter (ADC) board and a band-pass-filter (BPF) to form a spectrum sensor, which achieves several gigahertz (GHz) of sensing bandwidth and includes spectrum sensing in the 6 GHz unlicensed band as one application example. This structure uses direct radio frequency (RF) sampling with the ADC board, and the BPF passes only the RF band of interest that lies in the high-order Nyquist zone, which is then aliased to the baseband and captured. This method avoids the use of RF mixers or downconverters. To test its feasibility and performance, we develop customized software-defined radio (SDR) functions that allows an SDR transmitter to send multiple arbitrary waveforms on its multiple transmission ports over a large carrier frequency range simultaneously. We use the ADC board to capture several signals transmitted in the 6 GHz band for spectrum analysis and RF parameter estimation, such as the center frequency, bandwidth, and signal-to-noise ratio (SNR) of each signal. We compare the signal parameters of the data captured by this method with those reported by a high-end, commercial-grade spectrum analyzer (SA). The measurement results show that this method can achieve a satisfactory quality of signal detection, and verify the feasibility of the super-wideband spectrum sensing approach with a simplified structure.

Efficient power allocation is crucial for mitigating intercell interference in multi-cell wireless networks. In recent years, reinforcement learning (RL) algorithms, such as Q-learning (QL), Double Q-learning (DQL), and Deep Q-Network (DQN), have been proposed for downlink power control in dynamic radio environments. In this paper, we propose a system model to simulate downlink 4G/5G intercell interference and implement Multi-Agent Deep Reinforcement Learning (MADRL) algorithms, including Multi-Agent Proximal Policy Optimization (MAPPO) and DQN with Centralized Training and Decentralized Execution (DQN-CTDE), to optimize the average cell throughput in multi-cell coexisting 4G/5G networks. In addition, we compare the effect of frequency overlap for 4G vs. 4G, 4G vs. 5G, and 5G vs. 5G systems. Due to their multi-agent framework, simulation results show that both MAPPO and DQN-CTDE outperform other traditional RL methods such as QL, DQL, and DQN. MAPPO achieves the highest average throughput, followed by DQN-CTDE. The results are useful for modeling mutual interference and selecting the most suitable multi-agent deep RL method to optimize the downlink transmit power in the 4G/5G coexistence scenarios.

We present airtime utilization measurements of the IEEE 802.11ax WLAN in the 6 GHz band in different scenarios: various numbers of access points and clients, and in MIMO and SISO configurations. The measurement setup is based on 802.11ax development boards and open-source software. We present a methodology based on physical-level measurements and compare the airtime utilization for different throughput values and bandwidths, for downlink and uplink traffic. The results show that higher bandwidths reduce airtime utilization, MIMO reduces airtime utilization by up to 36.2 %, an additional client increases airtime utilization by up to 23.9 %, and mutually interfering 802.11ax networks increase airtime utilization by up to 27.3 %. This study provides useful guidelines for researchers and policymakers in the context of wireless coexistence in the 6 GHz band and electromagnetic compatibility characterization of 802.11ax devices.

With the rapid deployment of 5G NR in the sub-6 GHz frequency bands, cellular operators need to accommodate this new technology within the limited spectrum licensed to them, occupied mainly by 4G LTE. This poses the challenge of migrating their 4G infrastructure to 5G, while supporting current 4G systems in the same band. This indicates a need for wireless coexistence between 4G and 5G systems. In this paper, we present measurements of mutual downlink interference between two adjacent 4G and 5G cells. The setup is based on software-defined radios operating with cellular open-source software. The measurements show the effect of different levels of frequency overlap, from adjacent channel to co-channel, and various levels of signal-to-interference ratio (SIR). The network performance is quantified using throughput and packet loss. The results show that higher frequency overlap and lower SIR cause lower throughput and increased packet loss and that the overlap region might affect the performance. This setup can be used to study further coexistence scenarios.

The mmWave radio frequency (RF) spectrum allocations provide a large bandwidth and an excellent dynamic spectrum sharing (DSS) opportunity for emerging 5G NewRadio unlicensed (NR-U) and Wireless Gigabit (WiGig) services. To support constructive DSS, we outline a new modeling and analytical method to jointly evaluate the effects of a multiplebeam directional listen-before-talk (MB-DLBT) protocol, intercell interferences (ICIs), and spectrum sensing errors on the NR-U and WiGig DSS system performance. Available works did not provide a systematic and analytical approach to evaluate these effects, but only relied on computer simulations. Our numerical evaluation provides an insightful observation on the performance advantage of the MB-DLBT over the single-beam DLBT and omni-directional LBT schemes. This result provides a powerful tool to support performance analysis and optimization of mmWave DSS schemes.

In this paper, we report on a software-defined radio (SDR) based test setup to emulate and evaluate the performance of two wireless coexistence scenarios. The first case we study consists of two long-term evolution (LTE) downlink channels from adjacent cells, and the second case is formed by an LTE downlink channel coexisting with a wireless local network (WLAN) channel. Different from available SDR measurement works, this test design provides new methods such as real-time adjustment of communication and inter-cell interference (ICI) channel gains, the measurement of SDR receiver internal noise power and noise figure, and the measurement of link signal-to-interference-and-noise ratio (SINR). We compare the measured LTE SINR-to-throughput mapping result with a theoretical upper bound which assumes 3GPP reference channel quality indicator (CQI) values and an ideal communication hardware. Our measurement results illustrate the SINR gap caused by the effects of imperfect SDR hardware and noise figure, and show interesting findings about LTE and WLAN performance under varying mutual interference conditions. Our SDR design and measurement methods can be extended to support the performance evaluation and optimization of more general multicell LTE and WLAN coexistence systems.

Radio spectrum is a scarce resource. To meet demands, new wireless technologies must operate in shared spectrum over unlicensed bands (coexist). We consider coexistence of Long-Term Evolution (LTE) License-Assisted Access (LAA) with incumbent Wi-Fi systems. Our scenario consists of multiple LAA and Wi-Fi links sharing an unlicensed band; we aim to simultaneously optimize performance of both coexistence systems. To do this, we present a technique to continuously estimate the Pareto frontier of parameter sets (traces) which approximately maximize all convex combinations of network throughputs over network parameters. We use a dimensionality reduction approach known as active subspaces to determine that this near-optimal parameter set is primarily composed of two physically relevant parameters. A choice of two-dimensional subspace enables visualizations augmenting explainability and the reduced-dimension convex problem results in approximations which dominate random grid search.

The radio spectrum is becoming an increasingly scarce and valuable resource to such an extent that sharing the unlicensed bands is inevitable. In this work, we consider a multi-cell, multi-user massive multiple-input multiple-output (MIMO) coexistence scenario where multiple 5G New Radio Unlicensed (NR-U) and Wireless Gigabit (WiGig) links share an unlicensed millimeter-wave band. Our aim is to enhance the performance of coexisting networks by maximizing the overall network throughput via hybrid beamforming. This throughput is a function of both operators' medium access control protocols and physical layer parameters. To maximize the overall network throughput we propose a novel hidden node aware hybrid beamforming design. The hybrid precoders and combiners are optimal in the sense that they simultaneously maximize the signal power at desired users while minimizing the received inter-cell and intra-cell interferences at undesired users (leakage). The performance of the proposed scheme is examined through simulation. A comparison among the proposed method, a beam-steering solution, and an optimal unconstrained precoding design indicates the efficiency of the proposed algorithm.

To meet the ever-growing demands of data throughput for forthcoming and deployed wireless networks, new wireless technologies like Long-Term Evolution License-Assisted Access (LTE-LAA) operate in shared and unlicensed bands. However, the LAA network must co-exist with incumbent IEEE 802.11 Wi-Fi systems. We consider a coexistence scenario where multiple LAA and Wi-Fi links share an unlicensed band. We aim to improve this coexistence by maximizing the key performance indicators (KPIs) of these networks simultaneously via dimension reduction and multi-criteria optimization. These KPIs are network throughputs as a function of medium access control protocols and physical layer parameters. We perform an exploratory analysis of coexistence behavior by approximating active subspaces to identify low-dimensional structure in the optimization criteria, i.e., few linear combinations of parameters for simultaneously maximizing KPIs. We leverage an aggregate low-dimensional subspace parametrized by approximated active subspaces of throughputs to facilitate multi-criteria optimization. The low-dimensional subspace approximations inform visualizations revealing convex KPIs over mixed active coordinates leading to an analytic Pareto trace of near-optimal solutions.

Future unlicensed spectrum sharing scenarios involve multi-cell, multi-tier access of incumbent and emerging wireless systems, such as wireless local area network (WLAN), New-Radio unlicensed (NR-U), and Long-Term Evolution (LTE) with Licensed-Assisted Access (LAA). Listen-before-talk (LBT) medium access control (MAC) is a common technique used for channel sensing and access control. Despite intense research efforts, the majority of available results have not accurately analyzed multi-cell LBT with imperfect spectrum sensing. Furthermore, while past studies involved two major spectrum sharing strategies - shared cell access (SCA) and exclusive cell access (ECA), they missed a systematic comparison between the two. In this paper, we develop a unified analytical approach which maps the effects of imperfect spectrum sensing and multi-cell, multi-tier LBT to the key performance indicators (KPIs) of LAA and WLAN cells. We provide an analytical comparison between the SCA and ECA schemes, and show that the SCA can provide a significantly higher system throughput than the ECA as a function of sensing thresholds. We program the SCA and ECA algorithms with a new simulation method and implement Monte Carlo simulations, which verify our analytical results. Numerical results provide insightful observations on effects of various parameters. These results provide powerful analytical and simulation tools to evaluate the performance of multi-tier LBT coexistence systems with imperfect sensing, and effectively support coexistence system optimization.

Dynamic spectrum access (DSA) to achieve spectrum sharing in unlicensed bands is a promising approach for meeting the growing demands of forthcoming and deployed wireless networks, such as long-term evolution license-assisted access (LTE-LAA) and IEEE 802.11 Wi-Fi systems. In this paper, we consider a coexistence scenario where multiple LAA and Wi-Fi links compete for spectrum sharing subchannel access. We introduce a reinforcement-learning-based subchannel selection technique which allows access points (APs) and eNBs to select best subchannel distributively considering their medium access control (MAC) channel access protocols along with the physical layer parameters. The performance of this scheme is investigated through simulations, including the convergence property and sum throughput. Numerical results show that the proposed reinforcement-learning scheme converges fast and the sum throughput of the LAA and Wi-Fi systems is reasonably close to the result based on exhaustive search.

Carrier sense multiple access with collision avoidance (CSMA/CA) procedures have been specified for medium access control (MAC) in several incumbent and emerging wireless systems, such as wireless local area network (WLAN) and long-term evolution (LTE) with license assisted access (LAA). Clear channel assessment (CCA) errors in carrier sensing can cause significantly degraded network performance. Analyzing the impact of CCA errors in the MAC backoff and transmission process is a challenging task, and very few works have explicitly addressed this. Existing analytical work is only valid for special cases such as independent CCA errors, and the result lacks generality for extension to coexistence systems. In this paper, we try to fill this technical gap by modelling generalized CCA sensing errors which can be either fully correlated or independent due to the fading channel. We develop a new Markov model using matrix-vector representation which captures generalized CCA error events, and analyze the impact of CCA errors on the key performance indicators (KPIs), such as the throughput of both LTE-LAA and WLAN systems. To mitigate the effects of mis-detection and collisions which can cause the network throughput to drop to nearly zero, we propose a soft-collision method to reduce the performance loss. Finally, we program the LTE-LAA and WLAN CCA algorithms and implement extensive computer simulations. Comparisons between analytical and simulation results show consistent matching, and illustrate loss caused by sensing errors and improvement brought by the soft-collision method. This result provides a powerful analytical tool on CSMA/CA MAC-layer performance evaluation with imperfect sensing, applicable to both single and coexistence systems, and has practical value for countermeasure designs against sensing errors.

To improve spectrum sharing between long-term evolution (LTE) license assisted access (LAA) and incumbent systems such as wireless local area networks (WLANs) in unlicensed spectrum, listen before talk (LBT) has been proposed as a candidate for LAA channel access. To allow for a robust spectrum sensing performance, LBT may use a backoff-slot duration that is substantially larger than its WLAN counterpart. There is potential for an unknown backoff slot-jamming (SJ) effect, which may significantly decrease channel access probability (CAP) and throughput of LAA-LBT links. In this paper, we study the SJ effect and propose an effective anti-SJ (ASJ) LBT scheme. To gain theoretical insight, we develop a new performance analysis approach on coexisting systems with different slot durations. We model the LAA backoff process with super-counters, provide an in-depth analysis of the backoff process, and derive key performance indicator (KPI) statistics. These KPIs include backoff hold time, successful transmission probability, CAP, and throughput. Simulation results thoroughly validate our analytical results, and show that the ASJ-LBT scheme is effective in mitigating the SJ effect. These results fill a major technical gap in spectrum sharing research and may be extended to support system optimization and coexistence analysis of other heterogeneous systems.

To provide differentiated quality of service in long-term evolution (LTE) license assisted access (LAA) procedure, the 3GPP has defined several channel access priority classes (CAPCs). They use distinct arbitration inter-frame space (AIFS), contention window (CW) size, and payload duration. While evaluating the effects of CW size and payload duration is relatively straightforward, accurately modelling and analyzing the effect of AIFS has not been satisfactorily addressed. Available methods on analyzing different AIFSs are accurate for only limited parameter setups, or involve systematic approximations. Different from existing results, we develop a non-homogeneous per-slot Markov chain model to represent the state of each priority class during and after the AIFS, and analyze the channel access probability (CAP), successful transmission probability (STP), and average throughput of each class. Some novel features of our method include: 1) we model and solve the per-slot class-dependent link statistics (such as CAP and STP), which vary based on the slot location; and 2) we provide an in-depth analysis on the average throughput, and design a multi-class combinatorial procedure to evaluate average time spent per successful transmission on each delay cell. We program the LAA CAPC algorithms and implement extensive Monte Carlo simulations, which validate the accuracy of our analytical results even in very low throughput region for lower priority classes, and demonstrate the effects of AIFS and other parameters in an LAA system. These results provide solid progress for evaluating priority classes in the LTE-LAA system and other spectrum sharing systems, and can be extended to support system and parameter optimization.

To support efficient spectrum sharing and related standardization efforts in unlicensed spectrum, it is important to develop analytical tools to accurately quantify coexistence performance between long-term evolution license assisted access (LTE-LAA) and incumbent systems, such as wireless local area network (WLAN). Though joint throughput of spectrum sharing LTE-LAA and WLAN systems has been extensively studied, there lacks a systematic study on a high level metric - the probability of coexistence (PoC), which indicates whether coexistence is successful or not probabilistically. Another problem is that the majority of available results either ignored delay constraints, or studied only the mean (or variance) of delay, but have not considered the delay distribution and its impact on throughput. To address these problems, we define and analyze the original PoC metrics between LTE-LAA and WLAN systems based on two practical delay constraints. The first PoC is derived from the joint distribution probability of delays for successful transmissions; and the second PoC is defined upon the joint probability of delay-constrained throughput (DCT) of LAA and WLAN systems. To address the technical difficulties involved, we design a novel analytical framework to evaluate the moment generating function and cumulative distribution function (CDF) of the delay, and a new method to evaluate the DCT and its CDF. Consequently, the PoCs can be evaluated accurately with low complexity. The analytical results are verified by our Monte Carlo simulations, which demonstrate impacts of delay and throughput requirements on the PoCs, and illustrate design tradeoffs and insightful findings. These results provide theoretical and practical value for designing improved LTE-LAA and WLAN systems, and may be extended to other emerging spectrum sharing communication systems.

With the congestion and scarcity of available spectrum resources, spectrum sharing between long-term evolution (LTE) and the IEEE 802.11 (aka. WLAN) systems is an ongoing research topic. Considering the LTE license assisted access (LAA) with the listen before talk (LBT) procedure, recent research efforts try to evaluate the performance in several LTE-LBT and WLAN coexistence scenarios. However, the available approaches have not adequately modeled and analyzed general case of LBT (such as Category 4), and the case when there are more than two types of transmissions. In this paper, to fill this technical gap, we implement a systematic modelling and analysis of the media access control (MAC) layer coexisting performance of LTE-LBT and WLAN systems. We consider the coexistence scenario of multiple LTE downlink with multiple WLAN uplink and downlink transmissions. We develop analytical results on time-efficiency throughput, transmission and collision probabilities of LTE and WLAN nodes, and then generalize the result to multiple types of transmissions (e.g., more than three types). To validate the analysis, we implement LBT and WLAN MAC algorithm programming and extensive simulations, which confirm the accuracy of our analysis. Our result shows that replacing WLAN stations with LTE transmitters may, in some cases, significantly degrade the overall throughput, depending on the original efficiencies of WLAN systems and channel access schemes. To address this, we propose a 4-way handshaking channel access scheme for LTE-LBT, which can significantly improve the coexistence performance. These results put new insight into relationship between coexistence performance and MAC parameters of LTE-LBT and WLAN systems, and may aid in the design and optimization of coexistence systems.

To enhance spectrum efficiency in next generation heterogeneous wireless systems, it is important to improve shared spectrum usage between unlicensed long-term evolution (LTE) systems, such as the license-assisted access (LAA), and legacy systems, such as wireless local area networks (WLANs). LTE-LAA uses listen-before-talk (LBT) schemes to enhance coexistence performance. However, available LAA-LBT schemes may incur several problems, such as a slot-jamming effect and a significant slot boundary tracking error, leading to degraded performance. In this paper, we develop an LBT scheme with improved design and software-defined radio (SDR)-based experimental procedure for a performance validation. We program the improved LBT algorithm in the SDR field-programmable gate array (FPGA), and compare the results with the original LBT algorithm. This work also presents an automated testing technique and new SDR functions that modify the LAA parameters in realtime (such as backoff idle slot durations). The experiment results confirm the predicted slot-jamming effect, and show that our improved design enhances LAA throughput. These results provide not only a more robust LAA-LBT design, but also a new method of SDR programming and testing, and insight into the coexistence performance of heterogeneous systems.

To enable constructive coexistence with wireless local area networks (WLANs), unlicensed long-term evolution (LTE) systems use listen before talk (LBT) as a major candidate technique. The LBT has a flexible backoff idle slot duration, which can be significantly larger than the WLAN counterpart. To our knowledge, however, available analytical results on the LTE and WLAN coexistence have considered only identical idle backoff slot durations. There is a formidable technical difficulty to coexistence analysis for different backoff slot durations. In this paper, we develop a new technical approach to address this open issue. First, we point out an LBT backoff slot jamming effect, and propose a modified LBT backoff scheme to address this problem. Second, for our proposed LBT scheme, we develop a new analytical framework to address system interactions with non-equal backoff slot durations, model the LTE backoff process as super-counters, and provide a thorough analysis on the throughput, backoff counter hold time, and successful transmission probabilities of LTE-LBT and WLAN systems. Finally, we program the algorithms and use computer simulation to validate the analysis. This result fills a major gap and provides practical value for LTE-LBT and WLAN coexistence performance analysis with heterogeneous sensing and backoff slot durations.

Spectrum sensing is of utmost importance in cognitive radio and dynamic spectrum access systems for achieving spectrum awareness. To provide reliable spectrum awareness, it is critical to develop (near-) optimal sensing techniques and understand achievable performance limits. In this paper, we study likelihood ratio test (LRT)-based methods for detection of a signal of interest (SOI) assuming multiple receive antennas in the presence of spatially correlated additive noise (colored noise). We show that with on/off status information of the SOI available at receiver, a training-based generalized likelihood ratio test (TB-GLRT) method can be designed which approximates the optimal LRT estimator-correlator (EC) detector. Using the inverse Laplace transform and complex Wishart distribution theory, we derive formulas for detection and false alarm probabilities of both LRT-EC and GLRT schemes. The convergence of the TB-GLRT to the LRT-EC is analyzed and proved based on convergence behaviors of the detectors and their decision statistics. Simulation results verify the analytical convergence properties. In addition, the results illustrate the effects of different system design parameters, and demonstrate that the TB-GLRT scheme can provide substantial performance improvement over several existing GLRT methods.

In this paper, we study the optimization of an ad-hoc cognitive radio network (CRN) coexisting with a multi-cell primary radio network (PRN) utilizing spectrum underlay. To maximize the weighted sum rate (WSR) of the CRN, in contrast to the exclusive subchannel assignment (ESA) method considered in former results, we design shared subchannel assignment (SSA) method to approach the performance limit assuming discrete-rate modulation. The considered SSA method involves interference-channel-sharing based optimization, and in cognitive radio it becomes more complicated when the CRN-to-PRN sum-interference constraint has to be strictly satisfied. We design fast-convergent SSA duality schemes and use the interior point search to satisfy the various system constraints. Additionally, we design distributed duality schemes for both SSA and ESA schemes which involve only CRN local information exchange, using multichannel parallel dual update and a novel mini-slot competition. Effects of many system parameters are presented via simulation results, which show that our SSA duality scheme can perform significantly better than the near-optimal ESA duality scheme, and that the distributed schemes entail only small overhead and convergence losses.

The resource allocation optimization for multicast service in orthogonal frequency division multiple access (OFDMA) systems is an important research topic. It is known that in traditional multicast schemes the rate in each multicast group is severely limited by the user who has the minimum channel gain (MCG) on each subchannel. To counteract this effect, in this paper, we introduce the multiple description coding (MDC) into the multiple-group multicast service optimization for the downlink OFDMA, and study the weighted sum rate (WSR) maximization methods under various system constraints and assuming discrete-rate modulation. Simulation results show that the proposed method provides a significant performance enhancement than the MCG scheme and an MDC-based near-optimal iterative bit loading (IBL) approach. Besides this, our method converges very fast and enjoys a low complexity that is linear in the numbers of users, subchannels, and modulation bit levels.

In this paper, we study the coexistence and optimization of a multicell cognitive radio network (CRN) which is overlaid with a multicell primary radio network (PRN). We propose a PRN-willingness-based design framework for coexistence and subchannel sharing, and a Lagrange duality based technique to optimize the weighted sum rate (WSR) of secondary users (SUs) over multiple cells. First, to avoid unacceptable SU interference to primary users (PUs), the PRN determines its interference margin based on its target performance metric and channel conditions, and broadcasts this information to the CRN. Second, each CRN cell optimizes its WSR and implements intercell iterative waterfilling (IC-IWF) to control the intercell interference. To account for the interference and transmit power limits at SUs, multilevel waterfilling (M-WF) and direct-power truncation (DPT) duality schemes are developed. Third, we develop a serial dual update technique which enables low-complexity and fast-convergence of the proposed duality schemes. Numerical results demonstrate the effects of multiple parameters, such as the number of SUs per cell, subchannel occupancy probability (SOP), and outage probability of the PUs. Our results show that the proposed duality schemes provide a large performance enhancement than the channel-greedy and access-fairness based resource allocation schemes.

In this paper, we study coexistence and optimization of an ad hoc cognitive radio network (CRN) coexisting with multicell primary radio networks (PRNs). We assume the PRN cells operate in multiple frequency subbands, and the ad hoc CRN can utilize several subchannels in each PRN subband using spectrum underlay, which maintains that the pre-specified PRN signal-to-interference-plus-noise ratio (SINR) outage probability is not violated. To jointly optimize the throughput of the ad hoc secondary user (SU) links, we utilize the Lagrange duality optimization tool and design fast-convergent weighted sum rate (WSR) maximization schemes under important system and quality of service constraints, including the power spectral mask (PSM), the available transmit power of SUs, the maximum-subchannel-rate, and the minimum-rate per SU link. Both continuous rate (C-rate) and discrete rate (D-rate) modulations are considered. Additionally, we design a distributed access duality scheme which uses the mini-slot competition approach and involves only CRN local information exchange for the dual update, and achieves fast and stable convergence. Effects of many system operating parameters are presented via simulation results, which show that the optimal duality scheme can perform substantially better than the suboptimal duality scheme, and that the performance loss of the distributed scheme is small compared to the centralized scheduling.

In this paper, we study the weighted sum rate (w-rate) maximization algorithms with proportional rate fairness (PRF) and delay constraints for the downlink orthogonal frequency division multiple access (OFDMA) system. First, based on the Lagrangian duality optimization tool, we design a weighted sum rate maximization scheme based on instantaneous transmit power and bit error rate (BER) constraints. Second, to meet the rate fairness constraint imposed by different users' diverse traffic demands, we design a fast algorithm to search for the optimal weight factors, and implement the traffic-matching duality scheme to achieve the long-term target PRF and enhanced revenue rate. Third, we provide analytical channel throughput formulas for equal power allocation (EPA) and waterfilling (WF) power allocations schemes, and also evaluate the actual throughput taking into account the traffic random arrival process, limited buffer size, and transmission delay deadline. Simulation results show that the proposed traffic-matching duality scheme can achieve a significantly higher revenue rate than the fixed weight duality scheme which only tries to maximize the revenue rate but does not match the incoming traffic.

In this paper, we propose a duality-optimization based framework to maximize the weighted sum throughput for a multiple-input multiple-output (MIMO) ad hoc network. The new schemes include an approximate global optimization approach and an iterative search approach based on the duality framework. Transmitter adaptive precoding and receiver minimum mean-square-error (MMSE) detection for interference suppression are considered. Simulation results show that a significantly higher throughput is achieved for the dual optimization schemes than for the fixed mode precoding schemes and the transmit iterative waterfilling (IWF) scheme. The negative effects of transmit and receive antenna correlations are also studied. Results show that the proposed schemes are more robust against both transmit and receive correlations than the fixed-mode and IWF schemes.

In this paper, we study the asymptotic behavior of the bit-error probability (BEP) and the symbol-error probability (SEP) of quadratic diversity combining schemes such as coherent maximum-ratio combining (MRC), differential equal-gain combining (EGC), and noncoherent combining (NC) in correlated Ricean fading and non-Gaussian noise, which in our definition also includes interference. We provide simple and easy-to-evaluate asymptotic BEP and SEP expressions which show that at high signal-to-noise ratios (SNRs) the performance of the considered combining schemes depends on certain moments of the noise and interference impairing the transmission. We derive general rules for calculation of these moments and we provide closed-form expressions for the moments of several practically important types of noise such as spatially dependent and spatially independent Gaussian mixture noise, correlated synchronous and asynchronous co-channel interference, and correlated Gaussian interference. From our asymptotic results we conclude that (a) the asymptotic performance loss of binary frequency-shift keying (BFSK) with NC compared to binary phase-shift keying (BPSK) with MRC is always 6 dB independent of the type of noise and the number of diversity branches, (b) the asymptotic performance loss of differential EGC compared to MRC is always 3 dB for additive white Gaussian noise but depends on the number of diversity branches and may be larger or smaller than 3 dB for other types of noise, and (c) not only fading correlation but also noise correlation negatively affects the performance of quadratic diversity combiners.

In this paper, we provide a unified framework for the asymptotic performance analysis of space-time codes (STCs) in correlated Ricean fading and non-Gaussian noise and interference. In particular, we derive simple and asymptotically tight expressions for the pairwise error probability (PEP) of coherent and differential STCs which are valid for any type of noise and interference with finite moments and detection with general Mahalonobis distance (MD) metrics including Euclidean distance (ED) and noise decorrelating (ND) metrics. These PEP expressions can be combined with truncated union bounds to obtain accurate asymptotic approximations for the bit, symbol, and frame error probabilities of STCs. We show that while the diversity gain of an STC is independent of the type of noise and the type of MD metric used, the coding gain is not and depends on certain moments of the noise and interference. We provide closed-form expressions for these moments for several practically relevant types of noise and interference. We show that for correlated noise significant performance gains can be achieved with the ND metric compared to the ED metric. While noise correlations are beneficial at high signal-to-noise ratios if they can be exploited by the metric, they are harmful if this is not the case and the simple ED metric is employed. All our analytical findings are confirmed by simulations for various popular STCs and several different types of noise and interference.

In this paper, we propose and study several sum rate maximization algorithms for uplink orthogonal frequency division multiple access (OFDMA). For uplink scheduling without fairness consideration, we propose two Lagrangian duality optimization-based methods to maximize the weighted sum rate, which include a cyclic dual-update algorithm and a per-stage dual-update algorithm. For a low-complexity alternative, we design and analyze the transmit power and signal-to-noise ratio (SNR) product (PSP) based selective multiuser diversity (SMuD) schemes. Next, for fair scheduling, we propose rate maximization schemes under access proportional fairness (APF) and rate proportional fairness (RPF) constraints, respectively. The APF is achieved using normalized channel SNR (n-SNR) ranking-based SMuD for user selection per carrier, and the RPF is realized using dynamical carrier assignment based on the target rate ratios. Analytical throughput and fairness metrics are derived and verified via simulations. Numerical results illustrate the sum rate loss caused by rate fairness and access fairness constraints compared to the duality approach. Also, we show that unlike the downlink case, for uplink OFDMA the correlated frequency channels (carriers) cause significant ergodic sum rate degradation compared to the independent channels. These results provide new insight into the achievable uplink OFDMA performance with and without fairness constraints.

Feedback delay can severely affect the performance of transmit beamforming (TB) and the analytical quantification of the performance degradation has attracted much research interest recently. In this letter, we study the effect of delayed and limited-rate codebook index feedback on the error rate performance of TB systems over Rayleigh fading channels. We derive closed-form expressions for the moment generating function (MGF) and the probability density function (PDF) of the receiver output signal-to-noise ratio (SNR) including the effects of outdated and finite-rate feedback and further provide accurate analytical error rate expressions, which are verified by simulation results. The coding gain gap between the full-rate and limited-rate feedback and the coding gain advantage of multiple transmit antennas to the single antenna are analyzed, for limited and delayed feedback. These results are simple and concise and provide new analytical insight into the achievable diversity and combining gains and the loss caused by feedback delay for different system parameters and modulation formats.

In this paper, we study the weighted sum rate maximization of multicell cellular cognitive radio networks (CRNs) which are overlaid with multicell primary radio networks (PRNs). We assume each CRN cell is collocated with a PRN cell and has a cellular structure with access point (AP) and multiple secondary users (SUs). We propose a unified framework to determine the operation parameters of the CRNs in the multicell environment. First, to avoid unacceptable interference to primary users (PUs), we propose methods to determine the power spectral masks (PSMs) of SUs and APs in uplink and downlink transmissions at each subchannel based on the target signal-to-interference-plus-noise ratio (SINR) outage probability of PRN base station (BS) receivers. Second, we utilize the duality optimization tool and design weighted sum rate maximization schemes which include the PSM optimally. Third, we accurately model the intercell interferences between CRNs and mutual interferences between the PRNs and CRNs, as a function of multiple system parameters. Our model and approaches provide powerful design tools and deep insights into achievable performance for overlaid CRNs and PRNs.

In this paper, we study the sum rate maximization algorithms with long-term rate proportional fairness (RPF) for downlink orthogonal frequency division multiple access (OFDMA). In contrast to the rate-maximization schemes which used short-term RPF in the literature, we propose aweightedchannel signal-to-noise ratio (w-SNR) ranking based selective multiuser diversity (SMuD) scheme to achieve long-term RPF for rate maximization. In this approach, we solve the optimal SNR weight factors based on the target RPF, and then use them to implement carrier and power allocation to achieve a long-term target RPF. Analytical throughput and fairness metrics for the proposed w-SNR schemes with equal power allocation (EPA) or waterfilling (WF) over Rayleigh channels are derived. Simulation results show that the proposed long-term fairness scheme achieves a significantly higher rate than the short-term RPF schemes proposed in the literature. Besides better performance, the proposed scheme has a low complexity which is linear to numbers of users and carriers. These results put new insight into the achievable downlink OFDMA performance with proportional fairness and the effects of various system and channel parameters.

The effect of limited-rate feedback on the transmit beamforming (TB) channel capacity has been well studied in the literature, but the negative effects of outdated feedback and imperfect channel estimation (ICE) have not been adequately addressed yet. In this paper, we study the joint effects of receiver ICE and delayed and limited feedback on the capacity of transmit beamforming over Rayleigh fading channels. Our results show that with perfect receiver channel state information (CSI) the TB capacity may not monotonically decrease even as the delay increases. However, if the delay is not properly considered in the channel estimation, the TB channel capacity may quickly degrade to zero as the feedback delay increases. As countermeasures, we propose a predictive channel feedback scheme to improve the feedback quality and a pilot symbol assisted channel estimation (PSA-CE) scheme to improve channel estimation quality. Analytical and numerical results show that the proposed scheme is much more robust against feedback delay than the traditional one, and can provide a capacity performance close to the case with perfect receiver CSI and without feedback delay. Our results provide new insight into the achievable performance of transmit beamforming impaired by limited and delayed feedback and receive ICE.

In this paper, we provide a framework for the asymptotic performance analysis of space-time codes (STCs) in correlated Ricean fading and non-Gaussian noise and interference. In particular, we derive a simple, asymptotically tight expression for the pairwise error probability (PEP) of coherent STCs which is valid for any type of noise and interference with finite moments. This PEP expression can be used to obtain accurate asymptotic approximations for the bit and symbol error probabilities of STCs. Our results show that while the diversity gain of an STC is independent of the type of noise, the coding gain is not and depends on certain moments of the noise and interference. We provide closed-form expressions for these moments for several practically relevant types of noise and interference. Our analytical findings are confirmed by simulations for Alamouti's ST block code and Tarokh's ST trellis code and several different types of noise and interference.

In this paper, we present a unified asymptotic symbol error rate (SER) analysis of linearly modulated signals impaired by fading and (possibly) non-Gaussian noise, which in our definition also includes interference. The derived asymptotic closed-form results are valid for a large class of fading and noise processes. Our analysis also encompasses diversity reception with equal gain and selection combining and is extended to binary orthogonal modulation. We show that for high signal-to-noise ratios (SNRs) the SER of linearly modulated signals depends on the Mellin transform of the probability density function (pdf) of the noise. Since the Mellin transform can be readily obtained for all commonly encountered noise pdfs, the provided SER expressions are easy and fast to evaluate. Furthermore, we show that the diversity gain only depends on the fading statistic and the number of diversity branches, whereas the combining gain depends on the modulation format, the type of fading, the number of diversity branches, and the type of noise. An exception are systems with a diversity gain of one, since their combining gain and asymptotic SER are independent of the type of noise. However, in general, in a log-log scale for high SNR the SER curves for different types of noise are parallel but not identical and their relative shift depends on the Mellin transforms of the noise pdfs.

To provide a near-optimal low-complexity solution to parallel multiuser scheduling in code-division multiple-access (CDMA), we propose generalized selection multiuser diversity (GSMuD) schemes with multi-code channel assignment and analyze their performance. The proposed GSMuD (Lc, L) schemes rank a total of L users awaiting transmissions by their signal-to- noise ratios (SNRs) and select the Lc(1les Lc les L) users with the largest absolute (or normalized) SNRs for parallel channel access, which achieve near-optimal sum rate with a low scheduling complexity. The sum and individual channel throughput rates, second order statistics, fairness, and channel access statistics of the proposed GSMuD schemes are derived, taking into account different types of generalized fading channels. Compared to the round robin (RR) scheduling without SNR ranking, the GSMuD with normalized SNR ranking achieves a substantially higher sum rate while maintaining fairness. GSMuD also significantly improves the channel access performance and the degree of fairness than selective multiuser diversity (SMuD), which selects one best user only at each time slot.

In this paper, we derive general asymptotic moment generating function (MGF) expressions of the GSC output signal- to-noise ratio (SNR) for generalized correlated fading channels assuming large average signal-to-noise ratio (ASNR). Based on the MGF result, the asymptotic diversity and combining gains for correlated-diversity GSC are derived. Our analytical results reveal that over correlated channels when the channel covariance matrix is full rank the diversity gain of GSC is to equivalent to that of maximum ratio combining (MRC) with independent fading branches. The combining gains for different modulation formats and fading types in correlated channels are also derived. As is known and analytically verified in this paper, for channels without line-of-sight (LoS) components, correlation generally degrades the GSC combining gain. However, we show that for Rician channels the LoS phase vector affects the performance, and near-optimal LoS phase vector brings a larger combining gain than even the independent fading channels.

Accurate and systematic channel simulation technique is critical for performance verification of digital transceiver design over wireless channels. Despite the abundant results on Nakagami-m channel simulation techniques available in the literature, the accurate simulation of Nakagami-m fading channels satisfying the prescribed temporal autocorrelation property is still an open problem. Furthermore, the generation of Nakagami sequences satisfying proper phase distribution has not been studied yet. In this paper, we provide a systematic procedure on the reconstruction techniques of Nakagami-m fading autocorrelation property. We propose several new cumulative distribution function (CDF) mapping methods to realize arbitrary pre-specifled Nakagami auto-correlation function and with good numerical stability. In our method, we map the real and imaginary parts of complex Rayleigh fading samples disjointly to form complex Nakagami samples, which solves the phase ambiguity problem. Furthermore, we study the mapping between Rayleigh and Nakagami auto-correlation functions, and design an approach to calculate the original Rayleigh auto-correlation function to realize a specified Nakagami correlation function. Simulation results verify that our approach can accurately reconstruct arbitrary pre-specified auto-correlation property for the Nakagami channel generation, and also satisfy the proper phase property which follows a non-uniform distribution.

In this paper, we study the effect of delayed and limited feedback of beamformer codebook index on the error rate of transmit beamforming (BF) over Rayleigh fading channels. Closed-form expressions for the moment generating function (MGF) and the probability density function (PDF) of the receiver output signal-to-noise ratio (SNR) including the effects of outdated and finite-rate feedback are derived. Based on these, we further provide analytical expressions for error rate of BF systems. Our results show that for channels with non-bandlimited fading spectra, the error rate performance monotonically degrades when the feedback delay increases. On the other hand, for channels with bandlimited fading spectra the error rate may not monotonically degrades as the delay goes to infinity. However, delayed feedback may cause the transmit diversity gain being reduced to one for high SNRs, that is, no diversity gain but only an array gain is attained. The performance loss caused by delayed feedback may be much more detrimental than the limited-rate feedback for all SNRs.

In this paper, we study the optimal power allocation for orthogonal parallel-access scheduling schemes. We propose and study a parallel access scheme called generalized selection multiuser diversity (GSMuD), which ranks the channels of a total ofLusers and selects theLcusers with the largest signal-to-noise ratios (SNRs) for channel access. Besides the equal power allocation (EPA), two optimal power allocation algorithms are designed for the selected users in the GSMuD, namely (i) one- dimensional (1-D) optimal waterfilling (WF) power allocation along the channels given a fixed total power at each time slot; and (ii) two-dimensional (2-D) optimal WF along both the time and the channels given a fixed average total power. Accurate performance analyses of the above schemes are provided. Numerical results show that the 2-D WF power allocation yields the largest sum rate, while the EPA is near-optimal for many cases of practical interest.

In this paper, we study the asymptotic behavior of the bit-error probability (BEP) and symbol-error probability (SEP) of differential M-ary phase-shift keying with differential equal gain combining (DEGC) in correlated Ricean fading and non-Gaussian noise, which in our definition also includes interference. We derive simple and easy-to-evaluate asymptotic BEP and SEP expressions which show that at high signal- to-noise ratios (SNRs) the performance of DEGC depends on certain moments of the noise and interference impairing the transmission. We provide closed-form expressions for these moments for practically important types of noise such as Gaussian noise, Gaussian mixture noise, and correlated co-channel interference. In addition, we show that the performance loss of DEGC compared to coherent maximum ratio combining (MRC) is always 3 dB independent of the type of noise if only one diversity branch is available but strongly depends on the type of noise if multiple diversity branches are combined.

In this paper, the author studies the sum throughput maximization with proportional fair scheduling (PFS) for downlink orthogonal frequency division multiple access (OFDMA) channels. The author proposes selective multiuser diversity (SMuD) schemes with normalized channel signal-to-noise ratio (n-SNR)-based ranking for user selection at each carrier, and assigns the transmit power to the assigned carriers using either equal power allocation (EPA) or water-filling (WF). The author also proposes a modified absolute channel SNR (a-SNR)-ranking based SMuD scheme, which provides an improved performance than the originala-SNR SMuD scheme. Closed-form throughput and average access probability (AAP) expressions for bothn-SNR anda-SNR SMuD schemes with EPA over independent but not necessarily identically distributed (i.n.d.) Rayleigh channels (for different users and carriers) are derived. These results put new insight into the achievable downlink OFDMA performance with proportional fairness and the effects of various system and channel parameters.

Generalized selection multiuser diversity (GSMuD) is a new scheduling scheme which provides a near-optimal low-complexity solution to parallel access multiuser scheduling. In this scheme, a total of L users awaiting transmissions are ranked by their signal-to-noise ratios (SNRs) and the Nc (1 les Ncles L) users with the largest absolute (or normalized) SNRs are selected for parallel channel access. In this paper, we analyze the second order statistics (including the level crossing rate and average fade duration) and channel access performance (including the average channel access rate, the average access time, and the average waiting time) of the proposed GSMuD scheme, taking into account different types of generalized fading channels. Simulation results verify the derived analytical formulas. Numerical results show that compared to the selective multiuser diversity (SMuD), the GSMuD significantly improves the channel access rate and access time, and reduces the access waiting time. The presented results will be useful for the cross-layer design of multiuser parallel scheduling systems.

In this paper, we present a unified asymptotic symbol error rate (SER) analysis for linearly modulated signals with equal gain combining (EGC) and selection combining (SC) at the receiver. Our analysis is general enough to encompass all commonly used fading models and (possibly) non-Gaussian noise (and interference). We show that for high signal-to-noise ratios (SNRs) the SER of EGC and SC depends on the Mellin transform of the probability density function (pdf) of the noise. Since the Mellin transform can be readily obtained for all commonly encountered noise pdfs, the provided SER expressions are easy and fast to evaluate. Furthermore, we show that the diversity gain of EGC and SC only depends on the fading statistic and the number of diversity branches, whereas the coding gain depends on the modulation format, the type of fading, the number of diversity branches, the type of noise, and the combining scheme. Therefore, in a log-log scale for high SNR the SER curves of EGC and SC for different types of noise are parallel and their relative shift depends on the Mellin transforms of the noise pdfs.

In this paper, we study the asymptotic behavior of the bit-error probability (BEP) and symbol-error probability (SEP) of coherent maximum-ratio combining (MRC) in correlated Ricean fading and non-Gaussian noise, which in our definition also includes interference. We derive simple and easy- to-evaluate asymptotic BEP and SEP expressions which show that at high signal-to-noise ratios (SNRs) the performance of MRC depends on certain moments of the noise and interference impairing the transmission. We provide closed-form expressions for these moments for practically important types of noise such as Gaussian mixture noise, correlated co-channel interference, and correlated Gaussian interference. Interestingly, our results show that not only fading correlation but also noise correlation has an adverse effect on the asymptotic BEP and SEP.

Optimal multiuser scheduling which maximizes the sum rate for parallel channel access often involves an NP-hard design problem. In this letter, we propose a low-complexity optimal solution using a two-step procedure: (1) generalized selection multiuser diversity (GSMuD) which ranks the channels of a total of users and selects the users with the largest signal-to-noise ratios (SNRs) for channel access and (2) optimal power allocation for the selected users. Besides the equal power allocation (EPA), two optimal power allocation algorithms for the GSMuD are derived, namely: (1) 1D optimal waterfilling (WF) power allocation along the channels given a fixed total power at each time slot and (2) 2D optimal WF along both the time and the channels given the average total power. Accurate performance analyses of the above schemes are provided. Numerical results show that the 2D WF power allocation yields the highest rate, while the EPA is near-optimal for many cases of practical interest.

The optimal tradeoff between diversity gain and multiplexing gain for multiple-inputmultiple-output (MIMO) channels has been studied recently under the independent and identically distributed (i.i.d.) Rayleigh-fading assumption. In this correspondence, this result is extended and the optimal tradeoff performance is derived for generalized fading channel conditions, including different fading types, nonidentical fading distributions, spatial correlation, and nonzero channel means. Our results include many known models as special cases and shed light on the effects of different channel parameters on the optimal tradeoff performance

In this paper, we study the effect of imperfect channel estimation (ICE) on the performance of M-level quadrature amplitude modulation (M-QAM) with maximum ratio combining (MRC) and pilot-symbol assisted modulation (PSAM) in generalized Rician fading channels. By expressing the bit error rate (BER) of MRC diversity M-QAM in terms of the distribution of new decision variables, we derive novel, exact, and easy-to-evaluate BER expressions for diversity M-QAM with channel estimation errors. Our results include versatile system and fading channel parameters (e.g., arbitrary spatial and temporal correlation patterns among the diversity branches), and are valid for arbitrary linear channel estimators and square and rectangular M -QAM with different constellation sizes. In addition, we evaluate the performance of minimum mean-squared error (MMSE)- and sinc-interpolator-based channel estimators with PSAM, and provide some new insights into the performance of M-QAM with PSAM in generalized fading channels

In this paper, we study the performance of predetection hybrid-selection/equal-gain combining (HS/EGC), in which a subset of branches with the largest signal-to-noise ratios (SNRs) are selected and combined per EGC rule. To enable HS/EGC diversity for non-constant modulus (NCM) modulation formats, we propose the relevant HS/EGC receiver structure and decision variable. By deriving the moment generating function (MGF) of the HS/EGC output signals and with the help of the Parseval's theorem, we develop a general analytical framework to evaluate the error and outage probabilities of pre-detection HS/EGC for a large class of modulation formats and versatile system and channel parameters. Simulation results verify the validity of our proposed receiver structure and the accuracy of our analysis. Performance comparison with HS/MRC shows that HS/EGC achieves the same diversity order as HS/MRC. Some other insightful findings including the effect of the subset combining loss are also provided.

We study the channel capacity and fairness performance of a generalized selection multiuser scheduling (GSMuS) scheme which ranks a total of L users awaiting transmission by their absolute or normalized signal-to-noise ratios (SNRs) and selects the Nc number of users for channel access. Compared to the selective multiuser scheduling (SMuS) scheme which chooses a single user with the largest SNR for channel access, the proposed GSMuS achieves both higher capacity and improved fairness.

We propose and study a generalized selection multiuser scheduling (GSMuS) scheme which ranks a total of L users awaiting transmission by their signal-to-noise- ratios (SNRs) and selects Ncusers with the largest SNRs for parallel channel access. We derive the error and outage probabilities, the individual and sum rates of the proposed GSMuS scheme with adaptive modulation. The effect of imperfect channel estimation (ICE) on the sum and individual rates is analytically evaluated. Numerical results show that as the average channel SNR (ASNR) per user increases, assigning more users for parallel transmission (for a fixed total transmission power) will significantly improve the sum throughput than scheduling one best user. Under the block static fading assumption, as the ASNR increases the effect of ICE on the spectral efficiency tends to decrease, and the performance of GSMuS with ICE approaches that with perfect channel state information (CSI).

In this paper, we provide a unified asymptotic symbol error rate (SER) analysis of linearly modulated signals impaired by fading and (possibly) non-Gaussian noise (and interference). The derived asymptotic closed-form results are valid for a large class of fading and noise processes. In particular, we show that for high signal-to-noise ratios (SNRs) the SER of linear modulation schemes depends on the Mellin transform of the probability density function (pdf) of the noise and the diversity gain of the fading channel. Since the Mellin transform can be readily obtained for all commonly encountered noise pdfs, the provided SER expressions are easy and fast to evaluate.

We propose and study a generalized selection multiuser scheduling (GSMuS) scheme which ranks a total of L users awaiting transmission by their signal-to-noise-ratios (SNRs) and selects the Nc number of users with the largest SNRs for channel access. We analyze the error and outage probabilities, the individual- and sum-rates of the proposed GSMuS scheme taking into account the effects of adaptive modulation, statistical power allocation with minimum rate constraint, and generalized fading channels. Numerical results show that as the average SNR increases, assigning more than one users for simultaneous transmission (for a fixed total transmission power) will significantly improve the sum rate. The GSMuS scheme brings about a substantial scheduling gain with respect to conventional systems without SNR ranking.

Signal acquisition is a critical step for the ultrawideband (UWB) communication link to be set up, thus, accurate acquisition performance analysis is of practical importance. In this paper, we analyze the pulse-level acquisition performance of differential coherent and noncoherent acquisition schemes combined with a novel hopping method, nonconsecutive search (NCS) and path diversity (PD) for fast and low-complexity UWB acquisition over multipath channels. We derive the receiver output statistics and acquisition probabilities valid for arbitrary order of path diversity and for both differential and noncoherent acquisitions. Furthermore, using a generating function (GF)-based method, we accurately evaluate the mean, variance and the distribution function of the acquisition time TA, accounting for the effect of multiple co-channel interferers and multipath fading channels. Simulation and numerical results verify our analysis and show the large performance enhancement realized by NCS/PD than the serial search.

We study the effect of imperfect channel estimation (ICE) on the error probability performance of M-level quadrature amplitude modulation (M-QAM) with maximum ratio combining (MRC) and equal gain combining (EGC) diversity formats in Nakagami fading channels. We provide a novel formulation of the bit error rate (BER) of M-QAM with ICE in terms of the signal constellation-dependent effective signal-to-noise ratios (SNRs) or amplitudes, which allows us to derive the general, accurate, and easy-to-evaluate BER formulas for square and rectangular diversity M-QAM with channel estimation errors. Our result shows that the performance loss caused by ICE may be manifested by the signal decision space distortion and a scaling of the effective SNR. Furthermore, we evaluate the performance of M-QAM with pilot-symbol assisted modulation (PSAM) and present some insightful findings

The effect of correlated fading on the performance of space-time block codes (STBCs) over multiple-input multiple-output (MIMO) Rician fading channels is studied. The asymptotic error probability formulas for orthogonal STBC and the asymptotic pair-wise error probability (PEP) for non-orthogonal STBC in correlated Rician MIMO channels with high average signal-to-noise ratios (ASNRs) are derived, in terms of the diversity and coding gains. We show that the phase vector Phi of the channel line-of-sight (LOS) components and the fading correlation pattern have a significant impact on the performance of STBC in correlated Rician fading channels. The asymptotic upper and lower bounds of the receiver performance as a function of vector Phi are derived. Our results show that with correlated fading the phase vector Phi affects the effective Rice K-factor at the STBC receiver output, and hence may result in a coding gain significantly higher than the independent fading case. Furthermore, when the channel covariance matrix is rank deficient and under some mild conditions, the receiver's performance approaches that in a non-fading channel

In this paper, we present a unified mathematical framework to analyze the bit-error rate (BER) performance of general linear coherent multiuser receivers with diversity reception and imperfect channel estimation for doubly selective Rician-fading asynchronous code-division multiple-access channels. BERs of linear receivers with channel state information and data-aided channel estimation are analyzed, and both exact and low-complexity approximate BER evaluation formulas are presented. Furthermore, by using a Markov chain steady-state analysis, a tight BER approximation for receivers with decision-directed channel estimation is proposed. Numerical and simulation results verify the accuracy of the proposed BER evaluation methods.

In this letter, we study the asymptotic performance of hybrid-selection/maximal-ratio combining (HS/MRC) and postdetection HS/equal-gain combining (HS/EGC) over generalized fading channels for large average signal-to-noise ratios (ASNRs). By evaluating the asymptotic moment generating function of the HS/MRC output SNR at high ASNR, we derive the diversity and coding gains for HS/MRC for a large class of modulation formats and versatile fading conditions, including different types of fading channels and nonidentical SNR statistics across diversity branches. Our analytical results reveal that the diversity gains of HS/MRC and HS/EGC are equivalent to that of MRC, and the difference in the coding gains for different modulation formats is manifested in terms of a modulation factor defined in this letter. Some new analytical results about effects of the number of combined branches for HS/MRC and noncoherent combining loss of HS/EGC are also provided.

The effect of correlated branches on the performance of coherent maximum ratio combining (MRC) and non-coherent equal gain combining (EGC) diversity receivers over Rician fading channels is studied. The asymptotic error and outage probabilities for the MRC and EGC receivers with arbitrarily correlated branches for high average signal-to-noise ratios (ASNR) are derived, in terms of the diversity and coding gains. Based on this result, we show that the phase vector /spl phi/ of the line-of-sight (LOS) components of the channel has a significant impact on the receiver performance in correlated Rician fading channels. The asymptotic upper and lower bounds of the receiver performance as a function of /spl phi/ are derived. Our results show that with correlated branches the phase vector /spl phi/ affects the effective Rice K-factor at the diversity receiver output, and hence may result in a coding gain significantly higher than that for independent branches. Further, when the channel correlation matrix is rank deficient and under some additional mild conditions, the receiver performance approaches that in a non-fading additive white Gaussian noise (AWGN) channel.

In this paper, we study the effect of imperfect channel estimation (ICE) on the performance of M-level quadrature amplitude modulation (M-QAM) with generalized selection combining (GSC) diversity and pilot-symbol assisted modulation (PSAM) in several types of fading channels (including Rayleigh, Rician and Nakagami fading). We provide a novel formulation of the bit error rate (BER) of M-QAM with ICE in terms of the signal-constellation-dependent effective signal-to-noise ratio (SNR), which allows us to derive the accurate BER results of square and rectangular M-QAM with GSC and channel estimation errors. Our new BER expressions are general and yet easy to evaluate, and simplify to a closed-form expression for the Rayleigh fading case. Using our new analytical result, we evaluate the performance of M-QAM with PSAM, and present some interesting findings.

In this paper, we study the effect of imperfect channel estimation (ICE) on the performance of M-level quadrature amplitude modulation (M-QAM) with maximum ratio combining (MRC) and pilot-symbol assisted modulation (PSAM) in generalized Rician fading channels. Via a novel formulation of the bit error rate (BER) of M-QAM in terms of the distribution of new decision variables, we derive the exact BER of M-QAM with MRC diversity and channel estimation errors. Our new result is valid for both square and rectangular M-QAM, arbitrary linear channel estimators, and unbalanced and correlated diversity branches in Rician fading. Using our new results, we evaluate the performance of minimum mean square error (MMSE)- and sinc-interpolator-based channel estimators with PSAM, and present some interesting findings.

In this paper, optimum and suboptimum diversity combining schemes for coherent and differential M-ary phase-shift keying (M-PSK) transmission impaired by general Ricean fading and impulsive Class-A noise are derived and analyzed. The proposed suboptimum coherent combining (SCC) and suboptimum noncoherent combining (SNC) schemes yield similar performance as the corresponding optimum combining schemes but require a lower computational complexity. In addition, the novel SCC and SNC strategies achieve large performance gains over conventional maximum ratio combining (MRC) and equal gain combining (EGC), respectively. For MRC and EGC, respectively, we also provide a performance analysis for coherent and differential M-PSK transmissions over general Ricean fading channels with Class-A noise. Furthermore, tight performance upper bounds for the proposed optimum and suboptimum combining schemes are derived.

In this paper, optimum (ONC) and suboptimum (SNC) noncoherent diversity combining schemes for M-ary differential phase-shift keying (MDPSK) transmission over general Rician fading channels with impulsive class-A noise are derived and analyzed. The proposed SNC scheme yields a similar performance to ONC, but requires a lower computational complexity, and achieves a large performance gain over conventional equal gain combining (EGC). We provide a performance analysis for MDPSK transmission with EGC over general Rician fading channels with class-A noise, and derive a tight lower bound on the bit error rate of ONC.

In this paper, we study the effect of imperfect channel estimation (ICE) on the performance of M-ary phase shift keying (M-PSK) with maximum ratio combining (MRC) in generalized Rician fading channels. Using decision variable (DV)-based and signal-to-noise ratio (SNR)-based moment generating function (MGF) approaches, error and outage probability formulas, and SNR statistics for the M-PSK MRC receiver are derived, taking into account the effects of ICE and all relevant system and channel parameters. We analytically quantify the average SNR (ASNR) loss of M-PSK caused by ICE, and provided a unified MGF expression for ICE and different M's. In addition, we point out a major approximation for a popular approach used in the literature to evaluate the adverse effect of Gaussian weighting errors.

The authors propose an efficient moment generating function (MGF)-based method to evaluate the performance of generalized selection combining (GSC) over different fading channels. Employing a recently proposed method which is, however, only applicable to GSC diversity with independent and identically distributed branches, they derive a general MGF expression for the GSC output signal-to-noise ratio (SNR) for generalized fading channels, where the channel statistics in different diversity branches may be nonidentical or even distributed according to different distribution families. The resulting MGF expression is applicable to the analysis of the error probability, the outage probability, and the SNR statistics for GSC in a number of wireless communications scenarios with generalized fading. Numerical examples are presented to illustrate the application of the new analysis.

In this paper, we study the performance of a general linear coherent multiuser receiver with decision-directed channel estimation (DDCE) for doubly-selective Rician-fading CDMA channels. Employing the multivariate Gaussian approximation (MGA) and a decision variable-based moment generating function (DV-MGF) approach, both exact and low-complexity approximate bit error probability (BEP) formulas for a linear detector with genie-aided DDCE are provided. Furthermore, using a Markov chain steady-state analysis, a tight BEP approximation for non-ideal DDCE is provided taking into account the error propagation in the decision feedback. Some new findings are illustrated by simulation results.

In this paper, we study the asymptotic performance of generalized selection combining (GSC) over different fading channels for large average signal-to-noise ratio (ASNR). Employing a moment generating function (MGF) method and the polynomial approximation of the fading channel probability density function (pdf), we derive general asymptotic MGF expressions for the GSC output SNR over generalized independent fading channels. The diversity and coding gains for GSC over different fading channels are derived. Our analytical results reveal that the diversity gain of GSC is equivalent to that of maximum ratio combining (MRC), for different modulations and generalized fading channels. We also show that the difference in the coding gains for different modulations is manifested in terms of a modulation factor defined in this paper, and thus the performance gaps between different modulations can be analytically predicted. Asymptotic performance gap between GSC and MRC is also studied in terms of the coding gain. Numerical examples are presented to illustrate the application of the new results.

In this paper, we propose an efficient moment generating function (MGF)-based method to evaluate the performance of generalized selection combining (GSC) over different fading channels. Employing a recently proposed method which is, however, only applicable to GSC diversity with independent and identically distributed (i.i.d.) branches, we derive a MGF expression of the GSC output signal-to-noise ratio (SNR) for generalized fading channels, where the channel statistics in different diversity branches may be non-identical, or even distributed according to different distribution families. The resulting MGF expression is applicable to the analysis of the error probability, the outage probability, and the SNR statistics for GSC in a lot of wireless communications scenarios with generalized fading. Numerical examples are presented to illustrate the application of the new analysis.

The performance of differential amplitude and phase-shift keying (DAPSK) with post-detection diversity combining over general fading channels is of great theoretical interest and practical importance. Hence, a general and accurate performance analysis is very useful. In this paper, we analyze the distribution of the phase and amplitude decision variable at the DAPSK receiver output by using the moment generating function (MGF) approach. Exact results for the error probability of DAPSK on general Rician and Nakagami fading channels are derived, taking into account the effects of all system and fading channel parameters including correlated signal branches and correlated noise. By using our analytical results, the effects of the ring ratio and the amplitude decision boundary, etc., on the DAPSK performance are investigated, and some new findings are presented.

In this paper, we design decision-feedback differential detection (DF-DD) schemes for channels with phase noise. If the DF-DD feedback filter is properly optimized, a performance similar to that of more complex, some reported schemes based on multiple-symbol detection [K. Kiasaleh (December 1997)] and expectation maximization (EM) [E. Chiavaccini and G.M. Vitetta (December 2001)] can be achieved. However, it is also shown that an error floor is unavoidable. In contrast to previously proposed receivers for channels with phase noise, the DF-DD receiver can be made robust against unknown frequency offsets by introducing a simple linear constraint.

In this letter, we design decision-feedback differential detection (DF-DD) schemes for channels with phase noise. If the DF-DD feedback filter is properly optimized, a performance similar to that of a more complex scheme, recently reported by Chiavaccini and Vitetta, based on expectation maximization, can be achieved. However, it is also shown that an error floor is unavoidable for channels with phase noise. If a constraint is introduced, the DF-DD receiver can be made robust against unknown frequency offsets.

We give a tight approximation for the bit-error rate (BER) of decision-feedback differential detection (DF-DD). The influence of error propagation is modeled by a Markov chain. A simple state reduction method is proposed to limit computational complexity. Our results show that error propagation strongly depends on the chosen feedback filter. In particular, the popular assumption that error propagation increases BER by a factor of two is not always justified.

RicianAccurate performance analysis for linear receivers over frequency- and time-selective asynchronous code-division multiple-access Rician-fading channels is very useful and a general approach to this topic is very desirable. In this paper, by using a decision variable-based moment generating function approach, we provide a unified bit-error probability (BEP) analysis framework for different linear detectors with binary or quaternary differential phase-shift keying and postdetection combining over Rician-fading channels, taking into account the effects of the spreading code correlation, the system and fading-channel parameters, diversity combining, and branch correlation. To reduce the complexity of the exact BEP evaluation, we furthermore provide an approximate multivariate Gaussian assumption (MGA)-based method which entails a low complexity for BEP evaluation. Ideal and approximate linear minimum mean-squared error diversity receivers for correlated Rician-fading channels are proposed. Numerical results show that the phases of the line-of-sight (LOS) components of the desired user significantly affect the receiver performance over correlated multipath Rician channels, and this may be exploited to improve performance. Also, when the LOS components are affected by a significant Doppler shift, automatic frequency control is very useful in improving the receiver performance.

The central issue to the error probability analysis of M-phase signaling is to determine the phase distribution of the received signal. In this paper, we take a novel approach by formulating the phase distribution in terms of joint moment generating functions (MGFs) of the real and imaginary parts of the decision variable at the receiver output. We further derive fast convergent formulas by using the two-dimensional (2-D) inverse Laplace transform enabling us to accurately evaluate the phase distribution. The new technique is very general, taking into account the effects of arbitrary diversity order, symbol alphabet size M, and arbitrary diversity branch correlation. Numerical results are also presented for illustration.

This paper discusses the performance of communication systems using binary coherent and differential phase-shift keyed (PSK) modulation, in correlated Rician fading channels with diversity reception. The presence of multiple Rician-faded cochannel users, which may have arbitrary and nonidentical parameters, is modeled exactly. Exact bit error probability (BEP) expressions are derived via the moment generating functions (MGFs) of the relevant decision statistics, which are obtained through coherent detection with maximum ratio combining for coherent PSK modulation, and differential detection with equal gain combining (EGC) for differential modulation. Evaluating the exact expressions requires a complexity that is exponential in the number of interferers. To avoid this potentially time-consuming operation, we derive two low-complexity approximate methods each for coherent and differential modulation formats, which are more accurate than the traditional Gaussian approximation approach. Two new and interesting results of this analysis are: (1) unlike in the case of Rayleigh fading channels, increasing correlation between diversity branches may lead to better performance in Rician fading channels and (2) the phase distribution of the line-of-sight or static fading components of the desired user has a significant influence on the BEP performance in correlated diversity channels.

The error probability analysis of M-ary differential phase-shift keying signals with noncoherent diversity combining over general fading channels is not available in the literature except for some simple cases. The difficulty lies in the philosophy which attempts to explicitly determine the phase distribution expressions of the received signal, and this often leads to a mathematically intractable issue. In this paper, we take a novel approach by formulating the phase distribution in terms of joint moment generating functions of the real and imaginary parts of the decision variable at the receiver output. We further derive fast convergent techniques for two-dimensional (2-D) inverse Laplace transform enabling us to accurately evaluate the phase distribution. The error probability formulas thus obtained involve a twofold integral, which can be efficiently evaluated by using our algorithms developed on the basis of the 2-D trapezoidal summation and Gauss-Chebyshev quadrature. The new technique is very general, taking into account the effects of arbitrary diversity order, symbol alphabet size M, and arbitrary diversity branches correlation. Numerical results are also presented for illustration.

A linear Kalman filter detector for code-division multiple access proposed earlier in the literature is extended to a structure that can handle arbitrary detection delays, through the mechanism of state augmentation. Because pre-detection RAKE combining is used in the detector, it is optimal for multipath channels, unlike the previous structure that performed post-detection combining. We also derive nonlinear Kalman detectors, which approximate the highly complex nonlinear minimum mean-squared-error detector, using the concept of "additional observations." Both linear and nonlinear detectors require processing at one or more times the chip rate, and knowledge of the spreading codes of interfering users. They have the advantage over many other multiuser detection algorithms of not requiring the spreading codes to be periodic at the symbol rate, or matrix inversion. In addition, two of the detectors are able to generate and update a posteriori probabilities of the transmitted symbols, making them interesting for iterative multiuser detection.

We study generalized selection combining (GSC) schemes in independent Nakagami fading channels, where N diversity branches with the largest instantaneous signal-to-noise ratios (SNRs) are selected from the total of L (N/spl les/L) branches and then coherently or noncoherently combined. We propose two different techniques to derive the moment generating function (MGF) expressions for the GSC output SNR in generalized Nakagami fading channels, where there are distinct and noninteger fading severity parameters, as well as different average SNRs in different diversity branches. For arbitrary fading severity parameter m/sub k/, k=1, /spl middot//spl middot//spl middot/L, the MGF expression is given in a summation of N-dimensional definite integrals with the limits independent of SNR or channel parameters, and therefore can be evaluated very efficiently with numerical methods. Furthermore, for integer m/sub k/ closed-form MGF expressions are derived. Specializations of our results to Rayleigh channels and independent identically distributed (i.i.d.) Nakagami channels are presented, which are either new or equivalent to previously published results. Using the newly derived MGF expression, we provide a unified error probability analysis for many coherent and noncoherent modulation/detection schemes.

In this paper, we analyze the bit error probability (BEP) of binary and quaternary differential phase shift keying (2/4 DPSK) and noncoherent frequency shift keying (NCFSK) with postdetection diversity combining in arbitrary Rician fading channels. The model is quite general in that it accommodates fading correlation and noise correlation between different diversity branches as well as between adjacent symbol intervals. We show that the relevant decision statistic can be expressed in a noncentral Gaussian quadratic form, and its moment generating function (MGF) is derived. Using the MGF and the saddle point technique, we give an efficient numerical quadrature scheme to compute the BEP. The most significant contribution of the paper, however, lies in the derivation of a closed-form cumulative distribution function (cdf) for the decision statistic. As a result, a closed-form BEP expression in the form of an infinite series of elementary functions is developed, which is general and unifies previous published BEP results for 2/4 DPSK and NCFSK for multichannel reception in Rician fading. Specialization to some important cases are discussed and, as a byproduct, a new and general finite-series expression for the BEP in arbitrarily correlated Rayleigh fading is obtained. The theory is applied to study 2/4 DPSK and NCFSK performance for independent and correlated Rician fading channels; and some interesting findings are presented.

It is shown that a first-order linear state-space model applies to the asynchronous code-division multiple-access (CDMA) channel, and thus the Kalman filter produces symbol estimates with the minimum mean-squared error (MMSE) among all linear filters, in long- or short-code systems for a given detection delay. This result may be used as a benchmark against which to compare the performance of other linear detectors in asynchronous channels. It also reveals that a time-varying recursive filter with a fixed and finite complexity implements the fixed-lag linear MMSE (LMMSE) detector, which hitherto has been assumed to require a processing window (and hence complexity) that grows with time.