Imaging is a crucial sensing function that finds wide applications in environmental reconstruction, autonomous driving, etc. However, existing radio imaging techniques require at least Gigahertz-level bandwidth for high-resolution range estimation, and cannot be applied in 6G integrated sensing and communication (ISAC) network with Megahertz-level bandwidth. In this paper, we propose two novel high-resolution radio imaging techniques that can work on the limited-bandwidth 6G signals - bandwidth-independent synthetic aperture radar (BI-SAR), where the aerial base station (BS) moves along a circular trajectory to image the static targets; as well as bandwidth-independent inverse synthetic aperture radar (BI-ISAR), where the BS is static and the targets spin along an axis. Different from conventional SAR and ISAR counterparts that rely on range estimation, our proposed schemes can simply combine the Doppler spectrogram observed over one spin period to perform imaging. We also reveal that the signal model under our BI-SAR and BI-ISAR schemes is related to that under computer tomography (CT), but with an anisotropic scattering function, instead of an isotropic attenuation function as in CT imaging. We design the iterative adaptive approach-based Doppler association (IAA-DA) algorithm to tackle the above issue. Both numerical examples and real-world experiments are provided to show the feasibility and the effectiveness of our proposed BI imaging schemes.

Sixth-generation (6G) networks are rapidly becoming a focal point of global technological innovation, driven by the need to support hyper-reliable, low-latency, and intelligent connectivity for applications such as immersive extended reality, autonomous systems, and ubiquitous sensing. While 6G promises transformative advancements in wireless communication, achieving its ambitious goals poses significant fundamental challenges. One natural direction is to scale multiple-input multiple-output (MIMO) technology to unprecedented levels; however, doing so introduces substantial hardware complexity and power consumption. To overcome these limitations, recent research has explored antenna reconfigurability as a novel degree of freedom (DoF) at the physical (PHY) layer. Among these efforts, the fluid antenna system (FAS) has emerged as a compelling concept, offering reconfigurability in both spatial positioning and physical structure. This idea has inspired related innovations, including movable antennas, flexible-position MIMO, reconfigurable MIMO architectures, and adaptive antenna arrays, collectively referred to as next-generation reconfigurable antenna (NGRA) systems. While prior work has primarily focused on spatial flexibility, this article introduces a generalized model of FAS that incorporates both structural and morphological fluidity, enabling the vision of “shapeless and formless” antennas in future wireless systems. We analyze FAS’s potential to enhance key performance metrics such as coverage, energy efficiency, reliability, and spectral capacity. In addition, we outline implementation challenges and explore synergies with key 6G enablers, including reconfigurable intelligent surfaces (RIS), non-terrestrial networks (NTN), integrated sensing and communication (ISAC), and artificial intelligence (AI). This survey provides a comprehensive overview of NGRA systems and identifies promising directions for future research in reconfigurable wireless technologies.

This paper considers communication between a base station (BS) to two users, each from one side of a simultaneously transmitting-reflecting reconfigurable intelligent surface (STAR-RIS) in the absence of a direct link. Rate-splitting multiple access (RSMA) strategy is employed and the STAR-RIS is subjected to phase errors. The users are equipped with a planar fluid antenna system (FAS) with position reconfigurability for spatial diversity. First, we derive the distribution of the equivalent channel gain at the FAS-equipped users, characterized by at-distribution. We then obtain analytical expressions for the outage probability (OP) and average capacity (AC), with the latter obtained via a heuristic approach. Our findings highlight the potential of FAS to mitigate phase imperfections in STAR-RIS-assisted communications, significantly enhancing system performance compared to traditional antenna systems (TAS) with only modest hardware complexity and negligible training or feedback overhead at the user side. Furthermore, we quantify the impact of practical phase errors on system efficiency, emphasizing the importance of robust and energy-efficient strategies for next-generation wireless networks.

Pixel antennas, based on discretizing a continuous radiation surface into small elements called pixels, are a flexible reconfigurable antenna technology. By controlling the connections between pixels via switches, the characteristics of pixel antennas can be adjusted to enhance the wireless channel. Inspired by this, we propose a novel technique denoted antenna coding empowered by pixel antennas. We first derive a physical and electromagnetic based communication model for pixel antennas using microwave multiport network theory and beamspace channel representation. With the model, we optimize the antenna coding to maximize the channel gain in a single-input single-output (SISO) pixel antenna system and develop a codebook design for antenna coding to reduce the computational complexity. We analyze the average channel gain of SISO pixel antenna system and derive the corresponding upper bound. In addition, we jointly optimize the antenna coding and transmit signal covariance matrix to maximize the channel capacity in a multiple-input multiple-output (MIMO) pixel antenna system. Simulation results show that using pixel antennas can enhance the average channel gain by up to 5.4 times and channel capacity by up to 3.1 times, demonstrating the significant potential of pixel antennas as a new dimension to design and optimize wireless communication systems.

We investigate antenna coding utilizing pixel antennas as a new degree of freedom for enhancing multiple-input multiple-output (MIMO) wireless power transfer (WPT) systems. The objective is to enhance the output direct current (DC) power under RF combining and DC combining schemes by jointly exploiting gains from antenna coding, beamforming, and rectenna nonlinearity. We first propose the MIMO WPT system model with binary and continuous antenna coding using the beamspace channel model and formulate the joint antenna coding and beamforming optimization using a nonlinear rectenna model. We propose two efficient closed-form successive convex approximation algorithms to efficiently optimize the beamforming. To further reduce the computational complexity, we propose codebook-based antenna coding designs for output DC power maximization based on K-means clustering. Results show that the proposed pixel antenna empowered MIMO WPT system with binary antenna coding increases output DC power by more than 15 dB compared with conventional systems with fixed antenna configuration. With continuous antenna coding, the performance improves another 6 dB. Moreover, the proposed codebook design outperforms previous designs by up to 40% and shows good performance with reduced computational complexity. Overall, the significant improvement in output DC power verifies the potential of leveraging antenna coding utilizing pixel antennas to enhance WPT systems.

Pixel-based reconfigurable intelligent surfaces (RISs) employ a novel design to achieve high reflection gain at a lower hardware cost by eliminating the phase shifters used in traditional RIS. However, this design presents challenges for channel estimation and passive beamforming due to its non-separable state response, rendering existing solutions ineffective. To address this, we first approximate the non-separable RIS response functions using a kernel-based method and a deep neural network, achieving high accuracy while reducing computational and memory complexity. Next, we propose a simplified cascaded channel model that focuses on dominated scattering paths with limited unknown parameters, along with customized algorithms to estimate short-term and long-term parameters separately. Finally, we introduce a low-complexity passive beamforming algorithm to configure the discrete RIS state vector, maximizing the achievable rate. Our simulation results demonstrate that the proposed solution significantly outperforms various baselines across a wide SNR range.

For a single-antenna fluid antenna system (FAS) with N fixed antenna locations or ports, analytical expressions for the error performance of four types of signaling schemes for digitally modulated data transmission and reception are found. The signaling schemes are: (1) M-ary phase-shift keying with coherent reception, (2) two-sided M-ary amplitude-shift keying (M-ASK) with coherent reception, (3) one-sided M-ASK with noncoherent reception, and (4) one-sided M-ASK with partially noncoherent reception. The N ports are evenly distributed on a line. The FAS error performance is analyzed when the ports are subject to identically distributed Rayleigh fading with uniform correlation between the channels at the ports. A series expression for the characteristic function (c.f.) of the random complex channel coefficient magnitude squared of the chosen FAS port, in terms of a series of elementary c.f.s, where each elementary c.f. is the c.f. of a sum of N independent gamma random variables, is obtained. Series expressions for the symbol error probabilities as weighted sums of functions in closed form are presented. Closed form asymptotic high signal-to-noise ratio results for error performance are also derived. Numerical are presented to show the variation of the error performance with respect to the spacing between the first and Nth ports and N.

Simultaneous Transmitting and Reflecting Reconfigurable Intelligent Surfaces (STAR-RISs) are being explored for sixth-generation (6G) wireless networks. A promising configuration for their deployment is within cell-free massive multiple-input multiple-output (MIMO) systems. However, despite the advantages that STAR-RISs could bring, challenges such as electromagnetic interference (EMI) and phase errors may lead to significant performance degradation. In this paper, we investigate the impact of EMI and phase errors on STAR-RIS-assisted cell-free massive MIMO systems and propose techniques to mitigate these effects. We introduce a tailored projected gradient descent (GD) algorithm for STAR-RIS coefficient matrix design by minimizing the local channel estimation normalized mean square error (NMSE). We also derive the novel closed-form expressions of the uplink and downlink spectral efficiency (SE) to analyze system performance with EMI and phase errors, in which fractional power control methods are introduced for performance improvement. The results reveal that the projected GD algorithm can effectively tackle EMI and phase errors to improve estimation accuracy and compensate for performance degradation with nearly 30% NMSE improvement and over 10% SE improvement. Moreover, increasing the number of access points (APs), antennas per AP, and STAR-RIS elements can also improve SE performance. However, the advantages of employing STAR-RIS are reduced when EMI and phase errors are severe. Notably, compared to conventional RISs, the incorporation of STAR-RIS in the proposed system yields better performance and presents less performance degradation in highly impaired environments.

The fluid antenna system (FAS) concept represents shape-flexible and position-flexible antenna technologies designed to enhance wireless communication applications. In this paper, we apply this concept to reconfigurable intelligent surfaces (RISs), introducing fluid RIS (FRIS), where each tunably reflecting element becomes afluid elementwith additional position reconfigurability. This new paradigm is referred to as fluid RIS (FRIS). We investigate an FRIS-programmable wireless channel, in which the fluid metasurface is divided into non-overlapping subareas, each acting as a fluid element that can dynamically adjust both its position and phase shift of the reflected signal. We first analyze the single-user, single-input single-output (SU-SISO) channel, in which a single-antenna transmitter communicates with a single-antenna receiver via an FRIS. The achievable rate is then maximized by optimizing the fluid elements using a particle swarm optimization (PSO)-based approach. Next, we extend our analysis to the multi-user, multiple-input single-output (MU-MISO) case, where a multi-antenna base station (BS) transmits individual data streams to multiple single-antenna users via an FRIS. In this case, the joint optimization of the positions and phase shifts of the FRIS element, as well as the BS precoding to maximize the sum-rate is studied. To solve the problem, a combination of techniques including PSO, semi-definite relaxation (SDR), and minimum mean square error (MMSE) is proposed. Numerical results demonstrate that the proposed FRIS approach significantly outperforms conventional RIS configurations in terms of achievable rate performance.

This paper studies the use of multiple planar fluid antennas at a full-duplex base station (BS) for integrated sensing and communication (ISAC). In this model, the BS communicates with a downlink user, an uplink user, and performs target sensing simultaneously. Our objective is to maximize the communication sum-rate of the up and downlink users while meeting the sensing and power constraints. Given that the problem is non-convex, we first reformulate the problem using the fractional programming (FP) framework. After that, we iteratively optimize the beamforming vectors of the BS, the uplink transmit power from the user, and the antenna positions of both transmit and receive fluid antenna systems (FASs) at the BS. In particular, the transmit and receive beamforming vectors are optimized by utilizing the majorization-minimization (MM) framework, and a closed-form solution for the uplink transmit power is derived. To optimize the BS antenna positions, we transform the problems into convex quadratically constrained quadratic programs (QCQP) by using Taylor series expansion. The subproblems can then be solved based on the successive convex approximation (SCA). Simulation results show that FAS can greatly improve the communication rate compared to the traditional fixed-position antenna (FPA) system.

Based on our current understanding, extreme massive access over the same physical channel is only possible if an extra-large multiple-input multiple-output (XL-MIMO) antenna is used at the base station (BS) and instantaneous channel state information (CSI) is known at the BS side for precoding design. This casts doubt on scalability and challenges in device-to-device situations in which there is not a centralized, optimized BS for transmitting the user signals. To address this problem, we revisit the massive connectivity challenge by considering the case where no CSI is available at the BS and no precoding is used. In this situation, inter-user interference (IUI) mitigation can only be performed at the user terminal (UT) side. Leveraging the position flexibility of fluid antenna system (FAS), we adopt a fluid antenna multiple access (FAMA) approach that exploits the interference signal fluctuation in the spatial domain. Specifically, we assume that we haveNspatially correlated received signals per symbol duration from FAS. Our main approach uses a simple heuristic port shortlisting method that identifies promising ports to obtain favourable received signals that can be combined via maximum ratio combining (MRC) to form the received output signal for final detection. On top of this, a pre-trained deep joint source-channel coding (JSCC) scheme is employed, which together with a diffusion-based denoising model (MixDDPM) at the UT side, can improve the IUI immunity. We refer to the proposed scheme as turbo FAMA. Simulation results show that with a physical FAS size of 20 wavelengths at each UT transmitting quaternary phase shift keying (QPSK) symbols, fast FAMA can support 50 users whileturboFAMA can handle up to 200 users if the required symbol error rate (SER) is 10-2. If a higher error tolerance is acceptable, say SER at 0.1, turbo FAMA can even serve up to 1000 users but fast FAMA is only able to handle 160 users, all remarkably achieved without CSI at the BS.

This paper investigates a multiuser millimeter-wave (mmWave) uplink system in which each user is equipped with a multi-antenna fluid antenna system (FAS) while the base station (BS) has multiple fixed-position antennas. Our primary objective is to maximize the system capacity by optimizing the transmit covariance matrices and the antenna position vectors of the users jointly. To gain insights, we start by deriving upper bounds and approximations for the capacity. Then we delve into the capacity maximization problem. Beginning with the simple scenario of a single user equipped with a single-antenna FAS, we demonstrate that a closed-form optimal solution exists when there are only two propagation paths between the user and the BS. In the case where multiple propagation paths are present, a near-optimal solution can also be obtained through a one-dimensional search method. Expanding our focus to multiuser cases, in which users are equipped with either single- or multi-antenna FAS, we show that the original capacity maximization problems can be reformulated into distinct rank-one programmings. Then, we propose alternating optimization algorithms to deal with the transformed problems. Simulation results indicate that FAS can improve the capacity of the multiple access channel (MAC) greatly, and the proposed algorithms outperform all the benchmarks.

In this work, we propose a compact millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) system utilizing electronically steerable parasitic array radiator (ESPAR). We analyze the system and channel models for the compact mmWave massive MIMO system using a beamspace formulation and demonstrate that we can optimize the spectral efficiency of the compact mmWave massive MIMO system by jointly adjusting the variable reactive loads in the ESPAR with a digital beamformer. We formulate the compact mmWave massive MIMO system optimization problem to maximize spectral efficiency and propose an unconstrained optimization based algorithm with an initialization method. The spectral and energy efficiencies of the compact mmWave massive MIMO system are evaluated in comparison to conventional mmWave massive MIMO systems of the same antenna size using full-digital, fully-connected hybrid, and partially-connected hybrid beamforming. The results show that the compact mmWave massive MIMO system provides higher spectral efficiency than partially-connected hybrid beamforming. On top of this, it can provide higher energy efficiencies of around 3.21, 2.88, and 1.22 times compared to full-digital, fully-connected hybrid, and partially-connected hybrid beamforming but with lower hardware complexity and lower cost. Therefore, compact mmWave massive MIMO systems are a promising and effective alternative to conventional massive MIMO systems in millimeter wave (mmWave) communications.

Cell-free massive MIMO is one of the core technologies for next-generation wireless networks. It is expected to bring enormous benefits, including ultra-high reliability, data throughput, energy efficiency, and uniform coverage. However, the radically distributed architecture of cell-free massive MIMO necessitates new paradigms for transceiver design, especially by exploiting efficient distributed processing algorithms. In this paper, we propose a distributed expectation propagation (EP) detector for cell-free massive MIMO, which consists of two modules: a nonlinear module at the central processing unit (CPU) and a linear module at each access point (AP). The turbo principle in iterative channel decoding is utilized to compute and pass the extrinsic information between the two modules. An analytical framework is provided to characterize the asymptotic performance of the proposed EP detector with a large number of antennas. Furthermore, a distributed iterative channel estimation and data detection (ICD) algorithm is developed to handle the practical scenario with imperfect channel state information (CSI). Simulation results will show that the proposed method outperforms existing detectors for cell-free massive MIMO systems in terms of the bit-error rate and the developed theoretical analysis can be utilized as an asymptotic lower bound. Finally, it is shown that with imperfect CSI, the proposed ICD algorithm can significantly improve the system performance and reduce the pilot overhead.

Backscatter communication (BackCom) systems play a crucial role in low-cost and low-data-rate Internet of Things (IoT) applications. However, existing research predominantly focuses on idealized scenarios using minimum scattering antennas, resulting in performance discrepancies between simulations and practical implementations. To address this limitation, we investigate the impact of the antenna-dependent parameter associated with structural mode scattering on the amplitude and phase of the backscattered signal.We reveal that the conventional assumption of a minimum scattering antenna negatively affects BackCom system performance. To overcome this challenge, we propose an innovative signal subtraction technique (SST) that effectively mitigates the issues arising from this assumption. Our proposedSSTnot only preserves the minimum scattering antenna assumption but also enhances BackCom systems. Specifically, it improves the signal-to-noise ratio (SNR) in amplitude-shift keying (ASK)-modulated BackCom systems and introduces a trade-off between SNR and bit error rate (BER) in phase-shift keying (PSK)-modulated BackCom systems. Our extensive simulations highlight the practical application ofSST, demonstrating zero performance degradation when applying optimized designs tailored for minimum scattering antennas to any tag antenna. These findings underscore the pivotal role ofSSTin optimizing ASK- and PSK-modulated BackCom systems and offer valuable insights for enhancing overall system performance.

Fluid antenna multiple access (FAMA), enabled by the fluid antenna system (FAS), offers a new and straightforward solution to massive connectivity. Previous results on FAMA were primarily based on narrowband channels. This paper studies the adoption of FAMA within the fifth-generation (5G) orthogonal frequency division multiplexing (OFDM) framework, referred to as OFDM-FAMA, and evaluate its performance in broadband multipath channels. We first design the OFDM-FAMA system, taking into account 5G channel coding and OFDM modulation. Then the system’s achievable rate is analyzed, and an algorithm to approximate the FAS configuration at each user is proposed based on the rate. Extensive link-level simulation results reveal that OFDM-FAMA can significantly improve the multiplexing gain over the OFDM system with fixed-position antenna (FPA) users, especially when robust channel coding is applied and the number of radio-frequency (RF) chains at each user is small.

A single-input multiple-output system in flat Rayleigh fading, with pilot-symbol-aided least squares channel norm estimate based energy detection of one-sided multi-level amplitude-shift keying (ASK) data symbols, is considered. A suboptimum minimum distance (SMD) receiver is presented; it minimizes, over all ASK data symbols, the square of the difference between the received signal vector norm to the power of a real-valued non-zero parameter$\alpha $and the ASK-data-symbol-scaled channel norm estimate to the power of$\alpha $. For the SMD receiver, a closed form expression for the exact SEP is derived using a characteristic function approach. Furthermore, analytical methods of optimizing the ASK levels by SEP minimization, with high signal-to-noise ratio, large number of receive diversity branches, and one pilot symbol, are obtained for$\alpha \lt 2$and$\alpha =2$. Numerical results illustrate the performance variation of this receiver with respect to system parameters.

Fluid antenna system (FAS) has recently surfaced as a promising technology for the upcoming sixth generation (6G) wireless networks. Unlike traditional antenna system (TAS) with fixed antenna location, FAS introduces a flexible component in which the radiating element can switch its position within a predefined space. This capability allows FAS to achieve additional diversity and multiplexing gains. Nevertheless, to fully reap the benefits of FAS, obtaining channel state information (CSI) over the predefined space is crucial. In this paper, we study the system with a transmitter equipped with a traditional fixed antenna and a receiver with a fluid antenna by considering an electromagnetic-compliant channel model. We address the challenges of channel estimation and reconstruction using Nyquist sampling and maximum likelihood estimation (MLE) methods. Our analysis reveals a fundamental tradeoff between the accuracy of the reconstructed channel and the number of estimated channels, indicating that half-wavelength sampling is insufficient for perfect reconstruction and that oversampling is essential to enhance accuracy. Despite its advantages, oversampling can introduce practical challenges. Consequently, we propose a suboptimal sampling distance that facilitates efficient channel reconstruction. In addition, we employ the MLE method to bound the channel estimation error by$\epsilon $, with a specific confidence interval (CI). Our findings enable us to determine the minimum number of estimated channels and the total number of pilot symbols required for efficient channel reconstruction in a given space. Lastly, we investigate the rate performance of FAS and TAS and demonstrate that FAS with imperfect CSI can outperform TAS with perfect CSI. In contrast to existing works, we also show that there is an optimal fluid antenna size that maximizes the achievable rate when considering the energy and bandwidth overheads for full CSI acquisition.

Device-free localization (DFL) using easily-obtained Wi-Fi received signal strength (RSS) has wide real-world applications for not requiring people to carry trackable devices. However, accurate multitarget DFL remains challenging due to the unknown number of targets, multipath interference (MPI), especially between nearby targets, and limited real-world data. In this study, we pioneeringly propose a transformer-based learning method with Wi-Fi RSS as input, and an attentional prior fusion module, to simultaneously locate an unknown number of people at random positions. To overcome the multitarget data collection challenges, we contribute a large-scale cross-domain real-simulation-augmentation training dataset with one and two real-world nearby non-person objects at limited positions and up to five simulated and augmented randomly distributed targets. Experimental results demonstrate our method's improved accuracy, generalization ability, and robustness with fewer Wi-Fi nodes than previous methods.

Backscatter Communication (BackCom) is gaining popularity due to its potential for sustainable and low-cost Internet of Things (IoT) applications. However, due to the limited resources of passive tags, optimizing the backscatter modulation is critical for the widespread use of this technology. Current backscatter modulation designs ignore the impact of the tag’s antenna structure, which we show in this paper to have a negative effect on system performance and lead to design discrepancies. We investigate the impact of the antenna structure parameter on the backscattered signal characteristics. Then, we propose a novel signal subtraction technique that effectively calibrates the received signal based on the tag’s antenna structure to enable accurate detection. Our simulation results demonstrate that different values of this critical parameter result in different backscattered signals, which influence the signal decoding efficiency at the receiver. Furthermore, our work provides insights for optimized system design and enhanced BackCom performance.

Holographic MIMO (HMIMO) has recently been recognized as a promising enabler for future 6G systems through the use of an ultra-massive number of antennas in a compact space to exploit the propagation characteristics of the electromagnetic (EM) channel. Nevertheless, the promised gain of HMIMO could not be fully unleashed without an efficient means to estimate the high-dimensional channel. Bayes-optimal estimators typically necessitate either a large volume of supervised training samples or a priori knowledge of the true channel distribution, which could hardly be available in practice due to the enormous system scale and the complicated EM environments. It is thus important to design a Bayes-optimal estimator for the HMIMO channels in arbitrary and unknown EM environments, free of any supervision or priors. This work proposes a self-supervised minimum mean-square-error (MMSE) channel estimation algorithm based on powerful machine learning tools, i.e., score matching and principal component analysis. The training stage requires only the pilot signals, without knowing the spatial correlation, the ground-truth channels, or the received signal-to-noise-ratio. Simulation results will show that, even being totally self-supervised, the proposed algorithm can still approach the performance of the oracle MMSE method with an extremely low complexity, making it a competitive candidate in practice.

Energy detection for single-input multiple-output (SIMO) systems using perfect estimates of the channel norm has been shown to exhibit the same diversity order as that of a coherent system. In this work, we analyze the performance of energy detection for SIMO when only least squares estimates of the channel norm are available. The configuration of on-off keying in a flat Rayleigh fading environment is considered. A closed form expression for the approximate conditional symbol error probability (SEP), conditioned on the normalized channel norm and its estimate, is derived. A Gaussian approximation for the received signal energy is applied in the derivation. Furthermore, a closed form approximation of the SEP at high signal-to-noise ratio is obtained. Numerical results are presented to show SEP variation with system parameters and comparison of error performance with that of fully noncoherent energy detection.

This paper considers cell-free multiple-input multiple-output (MIMO) systems with multi-antenna access points (APs) and multi-antenna users in constrained spaces. Two main effects emerge in such a space-constrained design: spatial correlation and mutual coupling. We analytically study the resulting performance with conjugate beamforming and reducing inter-antenna distance. We derive the closed-form expression for the spectral efficiency (SE) as a function of the spatial correlation and mutual coupling matrices. Additionally, we consider a practical power consumption model to investigate the energy efficiency (EE) with power control coefficients. The obtained ergodic and analytical results will show essential insights into the system performance. The decreasing inter-antenna distance introduces performance loss, while an appropriate number of APs could balance the SE and EE trade-off. The number of users improves the SE performance, while an optimal number of antennas per user can be selected to achieve maximum SE performance. Moreover, more users will introduce a smaller optimal number of antennas per user.

This paper studies intelligent reflecting surface (IRS)-assisted free space optical (FSO) quantum communication systems. An IRS can relax the requirement of a line-of-sight (LoS) link between Alice and Bob for FSO quantum key distribution (QKD) applications. The IRS focuses the laser beam toward Bob by introducing a phase shift to the incoming incident beam from Alice. Both discrete variable QKD (DV-QKD) and continuous variable QKD (CV-QKD) protocols for IRS-assisted QKD systems are studied. For DV-QKD, we characterize the average quantum bit error rate (QBER) and the achievable secret key rate (SKR) under a log-normal fading turbulence model. For CV-QKD, we present the ultimate quantum information-theoretic bounds for the SKR and entanglement distribution rates. We also characterize the achievable SKR of a practical CV-QKD protocol implemented using Gaussian coherent states. Our results reveal that Alice and Bob can generate a quantum secure key even if the LoS link between them is blocked by utilizing the IRS. Furthermore, with a quadratic phase shift profile, the IRS-assisted link achieves a higher SKR as compared to the direct LoS link and a relay-assisted link for large transmission distances.

Radio tomographic imaging (RTI) is a device-free sensing technology that can image the radio frequency (RF) attenuation of physical objects in the environment. RTI uses received signal strength (RSS) information from a wireless communication network (WCN) to perform image reconstruction. However it requires a dense WCN consisting of a large number of nodes making it difficult to apply in realistic WCN. In this paper we investigate the performance of RTI when reconfigurable intelligent surfaces (RISs) are integrated into the WCN for integrated sensing and communication (ISAC). This approach can potentially enable the use of RTI in realistic WCN without a large number of nodes. Theoretical and numerical comparisons based on the Cramér-Rao Lower Bound (CRLB) are provided to verify the improvement on sensing performance brought by RIS. The scaling behavior of the reconstruction error as a function of the number of RIS element groups is also derived. Simulations are conducted to validate the proposed RIS-RTI system with a limited number of nodes. The results indicate that incorporating RIS can reduce the necessary number of nodes by more than a half while maintaining high-quality reconstruction compared to a network without RIS.

A challenge of ambient backscatter communication (AmBC) systems is signal recovery because the transmitted information bits are embedded in the ambient RF signals and these are unknown and uncontrollable. To meet this challenge, averaging-based energy detectors are typically used but consequently the data rate is low and there is an error floor. Here we propose a new detection strategy based on the ratio between signals received from a multiple-antenna Reader. The advantage of using the ratio is that ambient RF signals are removed directly from the embedded signals without averaging and hence it can increase data rates and avoid the error floor. Different from the original ratio detector that uses the magnitude ratio of the signals between two Reader antennas, in our proposed approach, we utilize the complex ratio so that phase information is preserved and propose an accurate linear channel model approximation. This allows the application of existing linear detection techniques from which we can obtain a minimum distance detector and closed-form expressions for bit error rate (BER). Methods for the estimation of channel state information (CSI) are also provided. In addition, coding and interleaving are also included to further enhance the BER. The results are also general, allowing any number of Reader antennas to be utilized in the approach. Numerical results demonstrate the proposed approach performs better than approaches based on energy detection and the original ratio detectors.

The emergence of fluid antenna systems (FAS) offers a novel technique for obtaining spatial diversity and leveraging interference fades for spectrum sharing in multiuser scenarios—a paradigm referred to as fluid antenna multiple access (FAMA). Nevertheless, as the number of users increases, the interference mitigation capability diminishes. To overcome this, opportunistic scheduling that prioritizes robust users proves to be an effective method for enhancing FAMA. This paper introduces a resilient decentralized reinforcement learning (RL) approach for opportunistic FAMA (O-FAMA), to autonomously select robust users and the port of each chosen user’s FAS jointly to maximize the network sum-rate. In order to enhance learning efficiency in this multi-agent environment, we propose a novel team-theoretic RL framework that includes a derivative network guiding the multi-agent learning of each solution’s policy networks. Our simulation results confirm the effectiveness of the proposed methodology.

Fluid antenna system (FAS) represents all forms of movable and non-movable position-flexible antenna system, and opens up the possibility of a new form of modulation schemes. In this paper, we investigate the design of position index modulation (PIM) for FAS for decreasing the bit error rate (BER) while taking advantage of the rate gain in index modulation. We further derive the BER and data rate expressions to assess the achievable performance of PIM. Simulation results are provided to illustrate the performance and some insights are drawn into the impact of both channel estimation accuracy and transmission power.

In this paper, we propose a new solution to improve the achievable rate of radio frequency (RF) powered cognitive radio networks (CRNs) with ambient backscatter communication (AmBC). Assisted with AmBC, the secondary transmitter (ST) can harvest energy and backscatter ambient signals when the primary channel is busy, which enhances the achievable rate compared with conventional RF-powered CRNs adopting the harvest-then-transmit (HTT) protocol. Our work proposes an RF-powered CRN that uses a multi-antenna ST since implementing multiple antennas on ST can enhance energy harvesting and increase the data rate. We discuss the corresponding time sharing and antenna selection tradeoffs and propose a low-complexity and time-efficient block coordinate descent (BCD)-assisted exhaustive search algorithm to find the optimal tradeoff that maximizes the data rate of the system. Simulation results show that our proposed scheme outperforms both the HTT mode and the ambient backscatter technique, leading to improved overall system performance.

In this work we present a novel linear iterative solution to an electromagnetic inverse scattering problem with phaseless data for strongly scattering, lossy media. It is based on an extended Rytov approximation that significantly widens the validity range of the conventional Rytov approximation. By modifying this extension and including it in a distorted wave iterative formulation, accurate reconstruction results for both the real and imaginary components of permittivity can be obtained. We denote the technique as the distorted wave extended phaseless Rytov iterative method (DxPRIM) and we present its derivation and numerical formulation. Using simulation and experimental examples, we demonstrate that DxPRIM can reconstruct scatterers with phaseless measurement data and show that it outperforms state-of-the-art phaseless techniques.

A method for achieving the continuous-space electromagnetic channel capacity bound using loaded$N$-port structures is described. It is relevant for the design of compact multiple-input multiple-output (MIMO) antennas that can achieve channel capacity bounds when constrained by size. The method is not restricted to a specific antenna configuration and a closed-form expression for the channel capacity limits are provided with various constraints. Furthermore, using loaded$N$-port structures to represent arbitrary antenna geometries, an efficient optimization approach is proposed for finding the optimal MIMO antenna design that achieves the channel capacity bounds. Simulation results of the channel capacity bounds achieved using our MIMO antenna design with one square wavelength size are provided. These show that at least 18 ports can be supported in one square wavelength and achieve the continuous-space electromagnetic channel capacity bound. The results demonstrate that our method can link continuous-space electromagnetic channel capacity bounds to MIMO antenna design.

Optimum and suboptimum energy detection receivers with diversity reception in Rayleigh fading, that only require limited channel state information based on the channel norm, are introduced. The importance of these channel norm based energy detection (CNBED) receivers is that they achieve the same diversity order as that of a coherent receiver. Furthermore, their performance degradation when compared to a coherent receiver can be made sufficiently low by appropriate choice of parameters. Due to their performance and the low complexity of energy detection, the CNBED techniques have potential applications to internet of things. Analysis of the CNBED receivers is performed for multi-level amplitude-shift keying (ASK). For the optimum receiver, an analytical approximation of the symbol error probability (SEP) as a sum of univariate integrals involving averaging of Gaussian$Q$-functions is derived. For the suboptimum receiver, closed form expressions for the exact SEP and for the approximate SEP under the condition of high signal-to-noise ratio (SNR) are obtained; in addition, using asymptotic approximations, expressions for the optimal ASK transmit levels with high SNR and large number of receive diversity branches, that minimize the SEP subject to an energy constraint, are found. Numerical results are provided to demonstrate the performance of the receivers.

A novel analog beamforming technique that utilizes single radio frequency (single-RF) electronically steerable parasitic array radiator (ESPAR) antennas is proposed. The ESPAR beamforming techniques are aimed at precoding in multiple antenna wireless communication systems using the single or hybrid RF approach. One advantage of ESPAR analog beamforming compared to conventional analog beamforming using phase shifters is that arbitrary patterns can be straightforwardly formed. Therefore, ESPAR analog beamforming can provide performance almost identical to digital beamforming. More importantly, ESPAR analog beamforming does not require phase shifters and power splitters, overcoming implementation challenges of conventional analog beamforming. It also has a more compact size compared to conventional beamforming using uniform antenna arrays. We analyze and optimize ESPAR analog beamforming and propose a channel approach based on beamspace pilot transmission to acquire channel state information (CSI). In addition, we propose limited feedback ESPAR analog beamforming based on a beamforming selection strategy. Simulation results for average gain show that ESPAR analog beamforming has almost identical performance to digital beamforming and better performance than analog beamforming using phase shifters. Energy efficiency simulations show that the technique has the highest efficiency among all the beamforming techniques. Therefore, ESPAR analog beamforming has near optimal performance, high energy efficiency, low circuit complexity, low cost, compact size and can be an effective alternative to conventional analog beamforming.

This month’s special issue provides an overview of the state-of-the-art technology and theory for future networks with wireless power transfer and energy harvesting. Wireless communication using radio frequency (RF) radiation has been around for over 100 years and has shaped our society significantly over the past 40 years. However, wireless is not just about communications. For very short ranges, wireless power supply by inductive power transfer has become a reality through several commercial products and standards (Wireless Power Consortium, Power Matters Alliance, Alliance for Wireless Power, and Rezence). Far-field wireless power transfer (WPT) and wireless energy harvesting (WEH) via RF (as in wireless communications) on the other hand could be used for a longer range. Although it has long been seen as a potential for powering low-power devices, it is only recently that wireless (via RF) power has been recognized as a promising technology to cope with the explosion of low-power devices in future networks. Driven by the reduction in the energy needs of electronic devices (remember Koomey’s law according to which, in 20 years, a device will require 10 000 times less energy to compute a given task) and the advent of trillions of internet device objects [Internet of Things (IoT)], there is a need to rethink the design of the network of the future so that wireless can reach its full potential not only to carry information but also to transfer energy.

This paper investigates the channel capacity of coherent reception with antenna diversity in Rayleigh fading using asymmetric constellations, such as nonbinary two-sided amplitude-shift keying (ASK) and quadrature amplitude modulation (QAM) with ≥ 8 levels. Due to the asymmetries, the capacity achieving input or a priori probability distributions deviate from uniformity. To perform the investigation, an analytical expression for the mutual information, in terms of an integral over a single variable, between the input (transmitted symbol) and the output (received signal vector comprising signals at receive antennas), is derived. For two-sided ASK, 8-QAM with cross constellation, and 16-QAM, analytical closed form expressions for the high and low signal-to-noise (SNR) approximations, respectively, of the capacity achieving input probability distribution, the capacity, and the relative gain in mutual information (between using the uniform and the capacity achieving input probability distributions) are obtained. Numerical results show that at low SNRs, the use of the capacity achieving nonuniform input probability distribution offers significant advantage over the use of the uniform input probability distribution, while at high SNRs, this advantage is significant only for configurations with one receive antenna. Furthermore, the high and low SNR approximations are shown to be reasonably accurate.

Inverse scattering problems, such as those in electromagnetic imaging using phaseless data (PD-ISPs), involve imaging objects using phaseless measurements of wave scattering. Such inverse problems can be highly non-linear and ill-posed under extremely strong scattering conditions such as when the objects have very high permittivity or are large in size. In this work, we propose an end-to-end reconstruction framework using unrolled optimization with deep priors to solve PD-ISPs under very strong scattering conditions. We incorporate an approximate linear physics-based model into our optimization framework along with a deep learning-based prior and solve the resulting problem using an iterative algorithm which is unfolded into a deep network. This network not only learns data-driven regularization, but also overcomes the shortcomings of approximate linear models and learns non-linear features. More important, unlike existing PD-ISP methods, the proposed framework learns optimum values of all tunable parameters (including multiple regularization parameters) as a part of the framework. Results from simulations and experiments are shown for the use case of indoor imaging using 2.4 GHz phaseless Wi-Fi measurements, where the objects exhibit extremely strong scattering and low-absorption. Results show that the proposed framework outperforms existing model-driven and data-driven techniques by a significant margin and provides up to 20 times higher validity range.

Imaging objects with high relative permittivity and large electrical size remains a challenging problem in the field of inverse scattering. In this work, we present a phaseless inverse scattering method that can accurately reconstruct objects even with these attributes. The novelty of the approach is that it uses a high-frequency approximation for waves passing through lossy media to provide corrections to the conventional Rytov approximation (RA). We refer to this technique as the extended phaseless Rytov approximation for low-loss media (xPRA-LM). Simulation and experimental results are provided for RF indoor imaging using phaseless measurements acquired from 2.4-GHz-based WiFi nodes. We demonstrate that the approach provides accurate reconstruction of objects up to relative permittivities of$15+1.5j$for object sizes greater than 30 wavelengths. Even at higher relative permittivities of up to$\epsilon _{r}=77+ 7j$, object shape reconstruction remains accurate; however, the reconstruction amplitude is less accurate. To the best of our knowledge, xPRA-LM is the first linear phaseless inverse scattering approximation with such a large validity range and can be used to achieve the potential of RF and microwave imaging in applications such as indoor RF imaging.

A systematic and general method for obtaining orthogonal far-field radiation patterns using any electronically steerable parasitic array radiator (ESPAR) embedded in a propagation environment with an arbitrary power angular spectrum (PAS) is described. The method is useful in designing single-RF multiple-input multiple-output (MIMO) systems where the orthogonal patterns can be utilized as a basis set for beamspace MIMO. The method utilizes the correlation matrix of the open-circuit radiation patterns and is termed the pattern correlation decomposition method (PCDM). PCDM is applicable to any antenna type (including realistic antennas with losses), array configuration, PAS and overcomes the limitations of previously proposed techniques. PCDM also provides closed-form solutions for the antenna currents to generate the orthogonal patterns. It also provides an estimate of the effective aerial degrees-of-freedom of the ESPAR. In addition, efficient optimization approaches to finding the optimal reactive loads that excite the required orthogonal radiation patterns are provided. Simulation examples using a 5-element and a 8-element planar inverted-F antenna array including material losses in various PAS are provided. These show that the proposed approach increases system capacity by up to 7 bits/s/Hz or equivalently reduces the required transmit power by up to 73% compared with previous approaches.

Reconfigurable intelligent surfaces (RISs) are an emerging technology for future wireless communication. The vast majority of recent research on RIS has focused on system level optimizations. However, developing straightforward and tractable electromagnetic models that are suitable for RIS aided communication modeling remains an open issue. In this paper, we address this issue and derive communication models by using rigorous scattering parameter network analysis. We also propose new RIS architectures based on group and fully connected reconfigurable impedance networks that can adjust not only the phases but also the magnitudes of the impinging waves, which are more general and more efficient than conventional single connected reconfigurable impedance network that only adjusts the phases of the impinging waves. In addition, the scaling law of the received signal power of an RIS aided system with reconfigurable impedance networks is also derived. Compared with the single connected reconfigurable impedance network, our group and fully connected reconfigurable impedance network can increase the received signal power by up to 62%, or maintain the same received signal power with a number of RIS elements reduced by up to 21%. We also investigate the proposed architecture in deployments with distance-dependent pathloss and Rician fading channel, and show that the proposed group and fully connected reconfigurable impedance networks outperform the single connected case by up to 34% and 48%, respectively.

Ambient radio-frequency (RF) energy harvesting can extract energy from RF signals in the ambient environment and has potential for applications in the Internet of Things. However, the power density of the ambient RF energy is low and therefore methods to maximize the average output direct current (dc) power are required. In this work we show that average output dc power in ambient RF energy harvesting is nonlinearly dependent on antenna directivity and linearly dependent on antenna port number. To maximize average output dc power it is therefore necessary to utilize directional multiport rectennas. To demonstrate the enhancements possible, the design for a directional 4-port pixel patch rectenna system to harvest ambient RF energy from the GSM-1800 frequency band is provided. The design has an average antenna size for each port of 0.3λ×0.3λ, and realized gains of 5.5 dBi. Measurement results show that the proposed rectenna can increase average output dc power by up to 6.2 and 4.5 dB compared to omnidirectional and directional single-port rectenna designs of similar size, respectively. Measurement in a real ambient environment is also conducted, showing that the proposed rectenna can achieve an output dc power of 11.2 μW which is five times higher than the two reference rectennas.

A systematic method based on the Theory of Characteristic Modes (TCM) for finding orthogonal radiation patterns of any electronically steerable parasitic array radiator (ESPAR) is described. This method can be useful for designing single-RF front-end multiple-input multiple-output (MIMO) systems in which orthogonal patterns can be utilized as a basis set for space modulation (SM) or full multiplexed MIMO systems. The method is based on the$N$-port formulation of TCM and is not restricted to antenna type or array configuration. It can also provide closed formed solutions for the antenna element currents required to generate the orthogonal patterns. In addition an approach to finding the required load reactances in ESPAR for generating the orthogonal patterns is provided and is based on the quasi-Newton method utilizing a closed form expression for the initial approximate solution. Approximate estimation of the effective aerial degrees of freedom of the ESPARs is also discussed. Two simulation examples of ESPARs, a 4-element linear dipole array and an 8-element rectangular planar inverted-F antenna array, using SM as well as full multiplexed MIMO are provided, demonstrating the effectiveness of the proposed method.

Ambient backscatter communication (AmBC) leverages the existing ambient radio frequency (RF) environment to implement communication with battery-free devices. The key challenge in the development of AmBC is the very weak RF signals backscattered by the AmBC Tag. To overcome this challenge, we propose the use of orthogonal space-time block codes (OSTBC) by incorporating multiple antennas at the Tag as well as at the Reader. Our approach considers both coherent and non-coherent OSTBC so that systems with and without channel state information can be considered. To allow the application of OSTBC, we develop an approximate linearized and normalized multiple-input multiple-output (MIMO) channel model for the AmBC system. This MIMO channel model is shown to be accurate for a wide range of useful operating conditions. Two coherent detectors and a non-coherent detector are also provided based on the proposed AmBC channel model. Simulation results show that enhanced bit error rate performance can be achieved, demonstrating the benefit of using multiple antennas at the Tag as well as the Reader.

The channel capacity of noncoherent reception of multi-level one-sided amplitude-shift keying (ASK), which is an asymmetric constellation, in Rayleigh fading with receive diversity and energy detection is considered. The asymmetries result in capacity achieving input probability distributions, that is, a priori probability distributions, that deviate from uniformity. An analytical expression for the mutual information in terms of a single integral is derived, and from it the set of equations, which can be solved to obtain the optimum or capacity achieving input probabilities, is obtained. High and low signal-to-noise ratio (SNR) approximations of the optimum input probabilities and the capacity are derived next. Furthermore, a logarithmic upper bound on the mutual information is obtained. Numerical results confirm that the uniform distribution of input probabilities is not capacity achieving. For example, with average SNR per symbol per branch of 6 dB, the relative deviation of the mutual information (with uniform input distribution) from the capacity is nearly 20% for 4-level ASK with one transmit diversity branch and two receive diversity branches. Furthermore, the derived high and low SNR approximations to the capacity are shown to be reasonably accurate.

The problem of imaging transmission line impedance profiles for fault location is considered. The approach utilized makes use of a novel adaptive probing sequence. The sequence is constrained to be unimodular and trained to obtain the minimized mean square error between the channel estimate and the true channel response. To achieve a practical approach for the reconstruction process, bandlimited passband signals are also considered so that the method can be applied to real systems with a limited bandwidth. This imposes a challenge as only bandlimited information is available for profile reconstruction. Therefore a technique for exact reconstruction with bandlimited signals is also proposed. Results are provided and it is demonstrated that the use of bandlimited passband signals performs well for transmission line impedance profile reconstruction under various conditions.

In this work we consider the one-dimensional (1D) inverse scattering problem of super-resolving the location of discrete point scatters satisfying the 1D Helmholtz equation. This inverse problem has important applications in the detection of shunt faults in electrical transmission lines and leaks in water pipelines where usually only low frequency spectral information is available from measurements. We formulate the inverse scattering problem as a sparse reconstruction problem and apply convex optimization to super-resolve the location of point scatters. We extend previous results and prove that we can super-resolve up to 4 points and 5-18 points with infinite precision if the points are separated by 1/(2fc) and 1/fcrespectively (fcis the maximum frequency we can measure). This is over 4 times closer than previous results. Simulation results are used to demonstrate the effectiveness of the approach.

In this article, three low complexity multiple-input multiple-output (MIMO) receivers using energy detection and multilevel amplitude-shift keying (ASK) for Internet of Things (IoT) applications are described. To circumvent the inherent nonlinearity of the noncoherent MIMO system, an equivalent linear system model for the channel is introduced. This allows the proposed receivers to be configured analogously to coherent-based approaches. The tradeoff is that increased numbers of receive antennas need to be used but the overall complexity is decreased compared to existing noncoherent approaches. The receivers can also easily be integrated with energy harvesting systems. The three receiver structures considered are zero forcing (ZF), ZF with ordered successive interference cancellation (ZF-OSIC), and weighted envelope detection (WENVD), and their performance in flat Rayleigh fading channels with multilevel ASK is investigated. For the WENVD receiver, the error performance under the condition of high signal-to-noise ratio is also analyzed, and closed form approximations of the conditional (conditioned on the channel matrix) symbol vector error probability (SEP) and the average of the conditional SEP are derived. It is found that the ZF receiver has the lowest complexity and the WENVD receiver the highest; however, error performance comparison through numerical results reveals that the WENVD receiver has the best performance and the ZF-OSIC receiver has the next best. When combined with multiport energy harvesting technology the receivers have significant potential for use in IoT.

Recent progress on bioresorbable and biocompatible miniature systems provides prospects for developing novel nanobots operating inside the human body. These nanoscale systems are expected to dissolve in vivo and cause no side effect after completing their tasks. Motivated by these advancements, we have developed the analytical framework of touchable communication (TouchCom) to describe the process of targeted drug delivery (TDD) using physically transient nanobots. Built upon our previous work, we develop a novel latticed channel model of TouchCom for an interconnected capillary network near a targeted tumor area. Specifically, we propose a two-dimensional grid to synthesize the microcirculation environment, which is used to describe the propagation process of nanobots. Based on this model, we consider the influence of blood pressure on the efficiency of TDD, and introduce a compensation strategy with the help of an external guiding field to mitigate the misalignment between the direction of blood pressure and the tumor location.

We propose the use of subcarrier delay spread based adaptive orthogonal frequency division multiplexing (OFDM) for communication through wideband waveguide channels. The technique has important communication applications when robots or vehicles are traveling inside waveguide channels such as tunnels or pipes. The delay spread in these mobile wideband waveguide channels varies significantly across subcarriers because propagation occurs in modes whose characteristics change significantly with frequency. Using knowledge of the delay spread in each subcarrier can then be used to adaptively select and avoid subcarriers with delay spread exceeding the cyclic prefix length. With this approach it is possible to create an OFDM system that is more efficient than systems satisfying the delay spread of all subcarriers. In this paper, we therefore propose subcarrier delay spread based adaptive OFDM to enhance the performance of OFDM systems operating in mobile wideband waveguide channels. To identify the delay spread of individual subcarriers we propose two methods. Using these methods, we provide simulation results to demonstrate the effectiveness of the technique. We also make use of experimental waveguide channel measurements to demonstrate the technique in realistic settings. Results show that performance can be significantly improved by using the proposed approach.

We consider two low-complexity receivers, namely, the energy detection (ED) receiver and the weighted envelope detection (WENVD) receiver, employing receive diversity, operating in flat Rayleigh fading with multi-level amplitude-shift keying, and having only channel magnitude information, that is, knowledge of the magnitudes of the fading gains of the receive diversity branches. A closed form expression for the approximate symbol error probability (SEP) of the WENVD receiver for high signal-to-noise ratio (SNR) is derived. Furthermore, analytical results on the optimization of the transmit symbol amplitude levels to minimize the SEP subject to a total energy constraint for high SNR and large number of receive diversity branches for both the ED and the WENVD receivers are presented. The performance improvement obtained by using these optimal levels over using symbol amplitude levels with equal spacing, that is, in arithmetic progression, for both the receivers is shown through numerical results.

A novel low complexity energy detection receiver, which utilizes knowledge of the magnitudes of the fading gains of the receive diversity branches, is presented. Its error performance in flat Rayleigh fading with multi-level amplitude-shift keying is analyzed, resulting in a closed form expression for the symbol error probability (SEP) as well as analytical results for high signal-to-noise ratios. These show that the receiver has the same diversity order as that of coherent receivers but maintains the low complexity structure of energy detectors. Numerical results show that the SEP performance of the energy detection receiver is much closer to that of a coherent receiver than to that of a noncoherent one. Furthermore, we also consider transmit constellation optimization and conclude that an equally spaced amplitude level constellation performs close to the optimal solution in Rayleigh fading. A significant advantage of this receiver is that it performs much better than noncoherent detection but maintains the low complexity structure of noncoherent detectors. Training to obtain the channel magnitudes is, however, required but the low complexity receiver can be used to perform that with the only additional overhead being the training time.

In this paper, we consider the subject of diagonal precoder matrix design for a three-input multiple-output system using spatial multiplexing with binary symbols from the constellation {0,1} and noncoherent reception in flat Rayleigh fading having a uniform transmit covariance matrix. For this system, the symbol vector error probability (SEP) tends to saturate at high values of average signal-to-noise ratio per symbol vector per diversity branch. The saturation value of the SEP is minimized with respect to the precoder parameters to obtain the best error performance. It is found that when the number of receive antennas is large, the optimal values of the precoder parameters are almost independent of the number of receive antennas. Numerical results show the advantage of using noncoherent reception over coherent reception with imperfect channel state information.

A noncoherent quadratic diversity reception system for multilevel amplitude-shift keying (ASK) signals in Rayleigh fading with different cases of the channel covariance matrix is considered. These include the important case of distributed antennas, which exhibit uncorrelated fading with distinct mean-squared channel gains (uncorrelated nonidentical fading) and weighted energy detectors, and the cases of exponentially correlated and uniformly correlated channels with equal mean-squared channel gains. For these cases, closed-form expressions for the symbol error probability (SEP) of the system are derived using the decision statistics obtained from the maximum likelihood receiver. The problem of determining the optimal amplitude levels that minimize the SEP under a total signal energy constraint is formulated and solved analytically for the high signal-to-noise ratio (SNR) configuration and numerically for the general configuration. For the high SNR configuration, it is shown that the optimal ASK levels should follow an approximately geometric progression. It is also observed that an equally spaced ASK constellation is not optimal in terms of achieving the minimum SEP. Numerical results are presented to highlight performance trends for channel gain imbalance and correlation.

We consider signal design for multiple-input multiple-output (MIMO) systems with spatial multiplexing and noncoherent reception in a flat Rayleigh fading environment. We obtain the symbol vector error probability (SEP) of noncoherent detection as a function of the signal amplitude levels and the effective precoder matrix, which depends on the precoder structure and the channel transmit covariance matrix. It is found that at high values of average signal-to-noise ratio (SNR) per symbol vector per diversity branch, the SEP tends to reach saturation. To obtain the best error performance, we need to find the optimal precoder and constellation parameters that minimize the saturation value of the SEP. Optimization of the saturation value of the SEP is carried out using the binary signal constellations {0,1} and {1, -r}, r > 1, two transmit antennas, a real valued transmit covariance matrix with equal diagonal elements, and a diagonal precoder. Results show that the optimal values of the parameters are almost independent of the number of receive antennas when the number of receive antennas is large. We also observe that the error performance of MIMO noncoherent reception is better than that of MIMO coherent reception with imperfect channel state information for a certain range of average SNR.

We focus on a full-duplex multi-user MIMO system where the base station (BS) serves multiple uplink and downlink users simultaneously. Both the BS and the mobile stations (MSs) are equipped with multiple antennas. The performance of the system is limited by the self-interference at the base station and the interference caused by the uplink users on the downlink users. To address this issue, we propose to jointly design the beamformers of the BS and MSs. An optimization problem is formulated to maximize the weighted sum data rate subject to maximum power constraints. Although the problem is non-convex, it can be solved via iterative minimization of weighted sum mean square error (MSE), and a stationary point of the problem can be obtained. Strategies to choose uplink and downlink users and to determine initial point for the optimization problem are also proposed. Simulation results show that the weighted sum data rate achieved by full-duplex system is substantially higher than that achieved by baseline half-duplex systems.

We consider a communication system with receive diversity in flat Rayleigh fading employing multi-level amplitude-shift keying (ASK) and noncoherent reception. Using the statistics of the decision variable of the quadratic receiver, a closed form expression for the symbol error probability (SEP) is derived. A formulation to determine the optimal signal amplitude levels of ASK constellation that minimize the SEP subject to a total signal energy constraint is presented. By approximating the derivative of the objective function, an approximate semi-analytical solution is obtained. We also present an asymptotic SEP expression that shows the variation of the SEP at high signal-to-noise ratio (SNR) and the diversity order of the system. An important result is that the optimum signal amplitude levels at high SNRs follow an approximately geometric progression in contrast to the more typical case of signal amplitude levels in arithmetic progression. Numerical results show the superiority of error performance of ASK with optimal signal amplitude levels as compared to that of ASK with signal amplitude levels in arithmetic progression.

Full-duplex wireless communication is becoming an important research area because of its potential for increasing spectral efficiency. The challenge of such systems lies in cancelling the self-interference. In this paper, we focus on the design of digital cancellation schemes and use them to supplement RF/analog cancellation techniques. The performance of digital cancellation is limited by the non-ideal characteristics of different subsystems in the transceiver, such as analog/digital converter (ADC), power amplifier (PA), and phase noise. It is first shown that given the pre-cancellation achieved by existing RF/analog techniques, the effects of ADC, phase noise, and sampling jitter are not the bottleneck in the system. Instead, the performance of conventional digital cancellation approaches are mainly limited by nonlinearity of the PA and transmit I/Q imbalance. In addition, the output SINR of the desired signal is limited because the estimation precision of the self-interference channel is affected by the desired signal. To overcome these issues, we propose a two-stage iterative self-interference cancellation scheme based on the output signal of the power amplifier. Analytical and simulation results reveal that the proposed cancellation scheme substantially outperforms existing digital cancellation schemes for full-duplex wireless communication systems.

Cooperative multiuser OFDMA is an important technology for current and future wireless communications systems. A critical part of this technology is performing multiuser subcarrier resource allocation and a wide variety of techniques have been suggested that can increase overall throughput, decrease total transmit power or improve other key performance measures. A particular subcarrier resource allocation approach that is of interest in this paper is a method based on nodes that transmit and receive on adjacent OFDM subcarriers simultaneously. This approach has shown significant promise, but its feasibility has not been fully investigated. In particular there will be a performance tradeoff in realistic systems as adjacent subcarriers will not be completely isolated and there will be interference on the receiving subcarriers that are adjacent to those that are transmitting. In this paper we look into the performance of such cooperative OFDMA systems under realistic conditions. We propose a transceiver structure to reduce the interference between transmitting subcarriers and receiving subcarriers. Its performance in terms of signal to interference and noise ratio (SINR) is evaluated by both analysis and simulation and is incorporated into a recently proposed cooperation strategy for OFDMA systems to examine its performance under the realistic structure. It is shown that although the cooperation strategy suffers from performance degradation due to the residual interference between the transmitting and receiving subcarriers, it still outperforms the conventional cooperation schemes.

Analysis of effective information transmission rate over fading channels has attracted much attentions in the last few years. Ergodic capacity and outage capacity, as two conventional indices, have been widely investigated in various scenarios. However, there exists a gap between them for any fixed average signal to noise ratio. Thus, one problem is raised naturally: How to fill this gap? To answer it, we shall propose a new concept, є-overflow rate, which is used to characterize the transmission capability of a fading channel when a finite size buffer is employed at the transmitter. With this buffer, the constant rate source data stream is matched with the time varying channel status so that the fading channel can support a higher rate source data stream. It will be proved that the є-overflow rate is larger than the є-outage capacity under the same outage constraint and can converge to the ergodic capacity in all signal to noise ratio region.

In this paper we describe a new method for multicarrier systems that allows the allocation of different subcarriers to their up and downlinks. Techniques utilizing such subcarrier allocation have already been used in some cooperation and resource allocation algorithms for multiuser Orthogonal Frequency Division Multiple Access (OFDMA) as well as in Orthogonal Frequency Division Duplexing (OFDD). Therefore it is useful to investigate methods that can enable them. In this work we focus on the physical feasibility of the system since the radio impairments and system imperfections are the key challenges that need to be addressed. In particular we propose a baseband echo cancellation approach to mitigate the interference between the up and downlink subcarriers. An iterative echo canceller is utilized at the receiver, with the reference samples obtained from the output of the transmit power amplifier. The system performance in terms of output signal to interference and noise ratio (SINR) and bit error rate (BER) is evaluated by computer simulations based on the configuration of 802.11a/g systems.

ABSTRACT In this paper, we consider information transmission over a block Rayleigh fading channel, where a finite size buffer is employed to match the source traffic with the channel service capability. Given the buffer size, the transmission capability of a block fading Rayleigh channel is characterized from two aspects: (i) the buffer behavior when the input traffic rate is constant; and (ii) the traffic rate that can be supported by the channel for a given overflow probability constraint. For the first problem, the stationary distribution of the queue length in the buffer is derived by discretizing the queue length using a uniform quantization strategy. It is also shown that the overflow probability of the finite size buffer decreases exponentially with buffer size. An explicit upper bound on the overflow probability is also given. For the second one, a new concept of ε‐overflow rate is proposed to measure the transmission capability of a block fading channel under overflow probability constraints. It will be shown that the ε‐overflow rate is larger than the ε‐outage capacity under the same outage constraint and will meet the great gap between outage capacity and ergodic capacity as the overflow probability constraint varies. Copyright © 2012 John Wiley & Sons, Ltd.

In this paper, we present a duplexing method for wireless communication that allows both transmission and reception to occur at the same frequency band and time slot simultaneously. The self-interference caused by coupling between the transmit and receive signals is cancelled to allow the detection of the desired receive signal. This scheme can increase the capacity of wireless communication systems since only one channel instead of two is needed for duplexing. Furthermore it also opens up the possibility of using new MAC layer wireless protocols that make use of simultaneous transmission and reception to boost the overall throughput of wireless network. In this work we use a baseband transmitter output based echo cancellation approach with a 2-stage iterative echo canceller at the receiver and the reference samples are obtained from the output of the transmit power amplifier. Implementation issues are considered, including system imperfections and RF impairments such as phase noise. The system performance is evaluated by computer simulation based on IEEE 802.11a/g system parameters. It is shown that the output SINR is sufficient to support full-duplex communication, and the overall channel capacity can be increased by a factor of up to 1.8.

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.

For multiple-input multiple-output wireless systems, we investigate the important question of how many antennas to place in fixed-length arrays, accounting for both spatial correlation and mutual coupling at the transmitter and receiver. We show that there is an optimal antenna configuration yielding the highest capacity which depends strongly on the array length and the transmission wavelength, but does not depend strongly on the signal to noise ratio (SNR). Moreover, we show that ignoring the effect of mutual coupling gives misleading results, yielding unbounded capacity growth. As another key finding, we demonstrate the surprising result that if the optimal antenna configuration is employed, then further optimizing the transmission based on the channel statistics gives very little benefit over simple equal-power spatial multiplexing. By deriving an expression for the capacity at low SNR, we provide a straightforward method for estimating the optimal number of antennas.

The success of IEEE Transactions on Wireless Communications has been incredible since its inception in 2001. The journal now receives 1600 plus submissions per year and has become one of the most downloaded journals within IEEE Xplore. However, we should not stop there, and our goal is to continuously enhance the journal and build on its current success.

In recent years, downlink multi-user multiple-input multiple-output (MU-MIMO) transmission techniques have attracted much attention because of their potential to significantly increase system capacity compared to single-user (SU) transmission. Unfortunately, accurate channel state information at the transmitter (CSIT) is crucial for these techniques to efficiently separate multiple users in the space domain so as to realize their capacity gain. In practice however accurate CSIT is difficult to obtain. In this letter we investigate the impact of imperfect CSIT on the system performance in terms of sum-rate scaling law for systems employing MU-MIMO decomposition scheme for downlink transmission. In particular, we derive the sum-rate scaling factors for various system configurations and find that imperfect CSIT has different effects on different categories of system configurations. Simulation results demonstrate the accuracy of our analysis.

In this paper, we propose a pilot-channel-assisted log-likelihood-ratio selective combining (PCA-LLR-SC) scheme for Rake receivers that will be used in long-range low-rate UWB communications targeted by the IEEE 802.15.4a specification. The pilot and data channels are constructed using quadrature sinusoidal bursts that have the same Gaussian envelope. The system parameters are optimized through jointly minimizing the channel estimation mean square error and maximizing the receiver output signal-to-noise ratio. Simulation results show that the proposed PCA-LLR-SC scheme is able to provide robust low-rate UWB communications in fast-fading multipath channels.

In this paper, we provide performance analysis for a pilot-channel-assisted log-likelihood-ratio selective combining (PCA-LLR-SC) scheme that is designed to support robust long-range low-rate UWB communications targeted by the IEEE 802.15.4a. Including the loss of orthogonality between data and pilot pulses caused by the UWB multipath channel, a closed-form bit-error-rate expression is derived, and verified by comparisons with simulation results. Our analytical result shows its accuracy in performance evaluation for the PCA-LLR-SC scheme and confirms that PCA-LLR-SC is able to support robust low-rate UWB communications in fast-fading multipath channels.

For ultra-wideband (UWB) communications with signal energy dispersed by a large number of multipath compnents, the design of a Rake receiver that can provide a desirable output signal-to-noise ratio (SNR) using only a moderate number of fingers becomes an important issue. In this paper, we propose a pilot-channel-assisted log-likelihood-ratio selective combining (PCA-LLR-SC) scheme for UWB Rake receivers to be used in long-range low-rate UWB communications envisioned by the IEEE 802.15.4a PHY specification. The pilot and data channels are constructed using quadrature sinusoidal bursts that have the same Gaussian envelope. The system parameters are optimized through jointly minimizing the channel estimation mean square error and maximizing the receiver output SNR. Extensive simulations confirm that the proposed PCA-LLR-SC scheme is capable of providing robust low-rate UWB communications in fast-fading multipath channels and in the presence of multi-user interference.

Cooperative broadcast aims to deliver common messages to all receiver nodes in the wireless network by utilizing cooperation between them. This can have many important applications like broadcasting control messages and cellular phone- based teleconference/games among a group of people. In this work, we investigate the cooperative broadcast from the diversity-multiplexing-delay (D-M-D) tradeoff point of view, which has become a popular tool in analyzing MIMO and cooperative protocols. The major contribution is that we derive the optimal D-M-D tradeoff curves for arbitrary number of receive nodes and arbitrary maximum number of automatic retransmission request (ARQ) rounds. Interestingly, it is shown that the achievable diversity gain is always restricted by two special situations. We compare our results with previous results on the achievable diversity-multiplexing (D-M) tradeoff of cooperative broadcast channels where no feedback is taken into consideration to show the significant diversity benefit of ARQ transmission.

Cooperative broadcast aims to deliver common messages to all receiver nodes in the wireless network by utilizing cooperation between them. This can have many important applications like broadcasting control messages and cellular phone-based teleconference/game among a group of people. In this paper, we will investigate the cooperative broadcast from the diversity-multiplexing-delay (D-M-D) tradeoff point of view, which has become a popular tool in analyzing multiple-input multiple-output (MIMO) and cooperative protocols. The major contribution is that we derive the optimal D-M-D tradeoff curves for arbitrary number of receive nodes and arbitrary maximum number of automatic retransmission request (ARQ) rounds. Interestingly, it is shown that the achievable diversity gain is always restricted by two special situations. Moreover, we have also compared our results with the previous results on the achievable diversity-multiplexing (D-M) tradeoff of cooperative broadcast channels where no delay is taken into consideration.

In this paper a 4 times 4 MIMO channel testbed is proposed that is based on a straightforward and modular design. The proposed testbed is designed explicitly for MIMO antenna testing and characterization and is easily configurable to a variety of needs in terms of frequency band and M times N requirements. The testbed is easily constructed and can be maintained by non-RF specialists. The data received from the testbed are stored on hard disk and post-processed offline to obtain MIMO channel estimates and other useful parameter estimates such as capacity and antenna correlation.

Previous work on antenna selection in MIMO systems, which deal with error performance, has mainly focused on frequency-flat channels. As a result, the objective was to minimize the symbol error rate (SER) or pairwise error probability (PEP). However, in present and future communication systems, where high throughput is one of the major features, wideband systems with frequency selectivity are now becoming common. Therefore, SER in flat-fading channels may not be a good measure for evaluating antenna selection in practical systems. In this paper, instead, we formulate the antenna selection problem based on a frequency-selective WLAN system. Hence the objective is to reduce the packet error rate (PER). We propose different antenna selection algorithms depending on the extent of channel state information we have. Simulation results are provided to demonstrate the effectiveness of the algorithms proposed.

Downlink multi-user multiple-input multiple-output (MU-MIMO) transmission techniques have gained much attention recently because of their potential to significantly increase system capacity compared to single-user transmission by separating multiple users in the space domain through appropriate signal processing. Unfortunately, these techniques require accurate channel state information at the transmitter (CSIT) for their proper operation. In practice however perfect CSIT is hard to obtain due to capacity-limited feedback channel in FDD systems for example. In this paper we investigate systems employing MU-MIMO decomposition transmission in the downlink with limited feedback. In particular, the essential information that enables the scheme to deal with inter-user interference is identified and the optimal codebook design in terms of minimizing the residual inter-user interference power is derived. Simulation results show that in general limited feedback has a significant impact on the mutual information achieved by MU-MIMO decomposition transmission.

Next generation wireless communication systems need to support data rates much greater than 3G systems. This will require more efficient utilization of the radio resource. Relay and MIMO (multiple input multiple output) techniques can significantly enhance system power efficiency, extend system coverage and are considered promising candidates for next generation wireless communication systems. In this paper, we propose a multi-user MIMO relay protocol which utilizes self-information to subtract the interference in two-way communication systems. It is shown that the proposed protocol achieves more than 30% capacity gain compared to previously proposed multi-user MIMO relay protocols in various system scenarios. An adaptive relay power allocation algorithm is also discussed to further increase the system power efficiency.

Cognitive radio technology facilitates spectrum reuse and alleviates spectrum crunch. One fundamental problem in cognitive radio is to avoid the interference caused by other communication systems sharing the same frequency band. However, spectrum sensing cannot guarantee accurate detection of the interference in many practical situations. Hence, it is crucial to design robust receivers to combat the in-band interference. In this paper, we first present a simple pilot aided interference detection method. To combat the residual interference that cannot be detected by the interference detector, we further propose a robust joint interference detection and decoding scheme. By exploiting the code structure in interference detection, the proposed scheme can successfully detect most of the interfered symbols without requiring the knowledge of the interference distribution. Our simulation results show that, even without any prior knowledge of the interference distribution, the proposed joint interference detection and decoding scheme is able to achieve a performance close to that of the maximum likelihood decoder with the full knowledge of the interference distribution

Link adaptation allows the transmitter to adapt to changing channel conditions. Critical to the design of link adaptation is the accuracy of channel state information at the transmitter. In this paper, we investigate the effect of imperfect channel state information and feedback delay on the performance of a multiple-input multiple-output zero-forcing receiver with adaptive power allocation. A closed-form approximate upper bound on bit error rate is derived for M-ary phase shift keying and M-ary quadrature amplitude modulation and it is valid for arbitrary numbers of transmit and. receive antennas. Comparison with Monte Carlo simulations is also provided, showing that the results derived from this analytical bound are useful for system design.

Orthogonal frequency division multiple access (OFDMA) and multicarrier code division multiple access (MC-CDMA) have recently drawn much attention for being potential candidates of future generation cellular systems. In single-cell scenario, while MC-CDMA is good at achieving frequency diversity when there is no channel state information available at the transmit side (CSIT), OFDMA achieves higher capacity than MC-CDMA due to its finer resolution in exploiting multiuser diversity with CSIT. Whether multiple-input-multiple-output (MIMO) MC-CDMA or OFDMA is a better option in multi-cell system remains unjustified in the literature. In this paper, we study the ergodic capacity and the goodput of MIMO-MC-CDMA and MIMO-OFDMA downlink systems with CSIT in multi-cell scenario assuming that the base station has the knowledge of the average inter-cell interference level only. Several types of users modeling different interference patterns are considered: (I) high data rate delay-insensitive users, (II) high data rate delay-sensitive .users, and (III) voice users (low data rate and bursty). Optimal resource allocation algorithms are used to compute the capacities of the systems, while a simple heuristic is used to obtain the achievable goodputs for both systems. The effects of path loss, number of antennas and different user types are studied and insightful results are obtained. We find that OFDMA has a higher system goodput for both Type I and Type II high data rate users, while MC-CDMA has a higher goodput for Type III users. Compared to MC-CDMA, the goodput of an OFDMA system is more sensitive to the activity factor of the voice users and suffers from noticeable loss. This demonstrates the superiority of the two systems in different practical situations.

In this paper, we examine and compare the potential maximum sum capacity of downlink multiple-input-multiple-output orthogonal frequency division multiple access (MIMO-OFDMA) and multiple-input-multiple-output multicarrier code division multiple access (MIMO-MC-CDMA) in a single-cell multiuser environment with channel side information at the transmitter, with and without a fairness constraint. The resource allocation is formulated as a cross-layer optimization framework and optimal power allocation and user selection algorithms are proposed for both scenarios. We find that for delay-sensitive applications, where fairness is imposed, the performance gain of OFDMA over MC-CDMA is quite large at moderate path loss exponents and number of antennas. However, for delay-insensitive applications, the benefits of OFDMA over MC-CDMA are significantly reduced when the path loss exponent or the number of antennas is large

By employing spatial multiplexing, multiple-input multiple-output (MIMO) wireless antenna systems provide increases in capacity without the need for additional spectrum or power. Zero-forcing (ZF) detection is a simple and effective technique for retrieving multiple transmitted data streams at the receiver. However the detection requires knowledge of the channel state information (CSI) and in practice accurate CSI may not be available. In this letter, we investigate the effect of channel estimation error on the performance of MIMO ZF receivers in uncorrelated Rayleigh flat fading channels. By modeling the estimation error as independent complex Gaussian random variables, tight approximations for both the post-processing SNR distribution and bit error rate (BER) for MIMO ZF receivers with M-QAM and M-PSK modulated signals are derived in closed-form. Numerical results demonstrate the tightness of our analysis

Downlink multi-user transmission techniques that allow several users to be served simultaneously in frequency and time have been recognized as a promising means to increase system capacity. However they require accurate channel state information (CSI) at the base station (BS) such that appropriate signal processing can be performed to separate multiple users in the space domain. In practice however, CSI cannot be perfectly known to the BS due to the capacity-limited feedback channel in FDD systems for instance. In this letter we investigate multiuser multiple-input single-output (MU-MISO) transmission with limited feedback. In particular we identify the useful information that the BS needs to deal with inter-user interference and a codebook design is derived accordingly. In addition, an adaptive threshold-based feedback approach is proposed, where only users with good feedback quality are allowed to do feedback. It is shown that the adaptive scheme can effectively improve the system performance given a fixed number of feedback bits.

Few works have addressed the effect of CFO (carrier frequency offset) on channel estimation performance. In this paper, compact analytical expressions on the mean square error of channel estimation in the presence of CFO are derived for OFDM (orthogonal frequency division multiplexing) systems employing single and multiple antennas. Concise upper bounds are also derived for SISO-OFDM systems. It is revealed that channel estimation MSE (mean square error) increases at the rate of approximately the square of the CFO and increasing the number of pilots does not contribute to better suppression of the MSE caused by CFO. In addition, it is observed that LMMSE (linear minimum mean square error) channel estimation is more resistant to CFO compared to LS (least square) in terms of channel estimation MSE. Furthermore, from the results derived herein, a clue for the pilot design of OFDM systems with CFO can be obtained

The practical challenge of capacity-achieving forward error-correcting codes (e.g., space-time turbo codes) is overcoming the tremendous complexity associated by their optimal joint maximum-likelihood (ML) decoding. For this reason, iterative soft decoding has been studied to approach the optimal ML decoding performance at affordable complexity. In multiple-input multiple-output (MIMO) channels, a judicious decoding strategy consists of two stages: 1) estimate the soft bits using list version of sphere decoding or its variants, and 2) update the soft bits through iterative soft decoding. A promising MIMO decoder is required to produce reliable soft-bit estimates at the first stage before iterative soft decoding is performed. In this paper, we focus on the overloaded (or fat) MIMO antenna systems where the number of receive antennas is less than the number of signals multiplexed in the spatial domain. In this scenario, the original form of sphere decoding is inherently not applicable and our aim is to generalize sphere decoding geometrically to cope with overloaded detection. The so-called slab-sphere decoding (SSD) proposed guarantees to obtain exact-ML hard detection while reducing complexity greatly. With the list-version of SSD, (his paper proposes an efficient MIMO soft decoder, which can generate reliable soft-bit estimates at affordable complexity as inputs for iterative soft decoding for promising performance. A case study in the IEEE 802.16 settings is carried out for performance evaluation

Downlink multiuser transmission techniques that can serve several users simultaneously in frequency and time have been recently recognized as a promising means to significantly increase system capacity. A disadvantage of these techniques is that accurate channel state information at the transmitter (CSIT) is essential for their proper operation. In practice however perfect CSIT is hard to obtain. In this paper multi-user multiple-input single-output (MU-MISO) transmission with limited feedback is investigated. In particular two feedback design strategies are introduced. One allows users to cooperate in the sense that they can do feedback jointly, which is unrealistic but may serve as an upper-bound of achievable performance of a realistic system. The other is non-cooperative where each user feeds back its CSI in an independent manner. Simulation results show that multi-user transmission needs much more accurate CSI to perform well compared to single-user transmission even when cooperation between users is allowed

In this paper, we consider the effect of CFO (carrier frequency offset) on the performances of LS (least square) and LMMSE (linear minimum mean square error) channel estimation algorithms for SISO (single input single output) OFDM (orthogonal frequency division multiplexing) systems. Compact analytical expressions on the MSE (mean square error) of the channel estimation under the effect of CFO are derived, while conventional works mainly rely on Cramer-Rao bound or Monte Carlo simulations. Based on the expressions derived, it is observed that the MSE contributed by CFO increases at the rate about the square of CFO and it can not be reduced by using more training symbols. What is more, it is also found that LMMSE is more resistant to CFO compared to LS

In this paper, we provide performance analysis for direct-sequence multiple-access ultra-wideband (UWB) systems operating in multipath environments when the effect of overlap between received pulses is included. Pulse overlap occurs when the pulse width is larger than the fine delay resolution of the UWB channel and is particularly important to consider in multidimensional pulse modulations. A closed-form bit error rate expression is derived and compared with simulations that employ UWB signals complying with the FCC UWB indoor emission mask and the channel model recommended by IEEE 802.15.3a. The detailed theoretical analysis and simulations reveal that channel-induced pulse overlap has a significant impact on UWB system performance. The results also show that compared with binary modulations, multidimensional biorthogonal pulse keying can improve power efficiency for multiple-access UWB systems under multipath fading, thereby providing an advantage for power-limited UWB communications.

Cross-layer design is a promising technique to achieve performance enhancement for wireless systems. In this paper, we seek to exploit the synergy between the PHY (physical) layer and the MAC (multiple access control) layer when a multiple-input multiple-output (MIMO) wireless system is operating at the PHY layer. We propose two optimal downlink multi-user MIMO scheduling algorithms which consider both the queueing state information from the MAC layer and the channel state information from the PHY layer when making scheduling decision. Our approaches are optimal in the sense that they can achieve maximum system throughput while at the same time guaranteeing the stability of the system. That is, they guarantee stability of the system whenever it is feasible with any other scheduling algorithm. Computer simulations demonstrate that significant gains are achieved by our cross-layer design compared to traditional strict-layered designs. Additionally, by making use of the HOL (head of line) packet waiting time our optimal scheduling algorithms can provide a more balanced delay performance for non-uniform traffic compared to the existing optimal scheduling algorithm which does not consider it

Multiple-input multiple-output (MIMO) wireless antenna systems provide increases in capacity without the need for additional spectrum or power. However the capacity increase is limited when the number of antennas at the receiver is fixed or restricted (due to mobile size constraints for example). To overcome this limitation multi-user MIMO can be used, which allows several users to be served simultaneously in frequency and time. A disadvantage of these multi-user MIMO systems, when used in the downlink however, is that they need accurate channel state information (CSI) at the transmitter and also uncorrelated channels among users. In this paper we investigate methods to address the problems of multi-user MIMO systems in spatially correlated channels. We adopt the concept of angle between subspaces to characterize the inter-user spatial correlation and adapt the algorithm to those conditions. We also investigate the impact of the accuracy of CSI at the transmitter (CSIT) and whether more limited CSI such as channel correlation information alone can be used to provide good multi-user MIMO performance. Results are presented as various simulated capacity measures and we use them to make comparisons between the various multi-user MIMO configurations

We propose a pilot-channel assisted modulation (PCAM) for pulse-based ultra-wideband systems that require accurate channel estimation for RAKE combining. The pilot channel is constructed with pulses that are orthogonal to the data-bearing pulses and each pilot pulse is transmitted together with a data pulse. PCAM parameters are designed to optimize the channel estimation and data detection performance jointly. Simulation results show that PCAM is able to provide desirable performance under channel time-variations and multi-user interference, without sacrificing the data rate.

In this paper, we develop multidimensional modulation for ultra-wideband (UWB) multiple-access (MA) impulse-radio communications in wireless multipath environments. An important advantage of multidimensional modulation over single-dimensional modulation is the possibility of higher power efficiency, and this may be critical in UWB communications. For this reason, we propose a 2MN-ary biorthogonal keying (BOK) scheme, in which N orthogonal pulse shapes in conjunction with M orthogonal codes are employed to construct MN-dimensional biorthogonal modulation. The direct sequence (DS) MA performance of the proposed scheme is analyzed. A closed-form bit-error-rate expression is derived and compared with simulations based on the Intel Labs' UWB channel model. Orthogonal pulse shapes that comply with the Federal Communications Commission UWB indoor-emission limits are used in simulations. Our results confirm the power-efficiency improvement achieved by multidimensional modulation for UWB MA communications under multipath fading.

We propose a simple power allocation (PA) scheme for wireless MIMO systems with layered space-time equalization (LSTE), which aims at minimizing the overall BERs for all data streams. This so-called MIN-BER PA scheme significantly outperforms the uniform power (UP) case in a wide range of RMS delay spreads and at high SNR, with little loss in computational complexity and bandwidth efficiency. Compared to EQ-BER PA, MIN-BER PA yields close performance, but requires much less complexity especially at high SNR. Closed-form results are provided for MIN-BER PA, based on which intensive performance analysis is made, including BER performance and signal detection ordering for LSTE with PA.

In this paper, we propose a pre-Bell Laboratories layered space-time (BLAST)-decision-feedback equalization technique for the downlink of frequency-selective fading multiple-input multiple-output (MIMO) channels to combat multiple-access interference (MAI) and intersymbol interference (ISI). In our technique, we perform MIMO pre-equalization and prelayered space-time processing at the transmitter or base station, with a simplified receiver at the mobile station that requires only limited signal processing. An important application is in the downlink, so that a simplified mobile station can be constructed. An expression for the signal-to-noise ratio (SNR) and error probability based on the Gaussian approximation of the output noise term is derived. Performance is investigated by analysis and simulation results. In particular, it is demonstrated that the diversity order of this technique is higher than that of the MIMO orthogonal frequency-division multiplexing (OFDM) with vertical (V)-BLAST and MIMO OFDM with linear transmit preprocessing. It is also noticed that this technique performs better at high SNR values.

In this letter, we introduce five different strategies of linear transmit signal processing for multiuser multiple-input multiple-output (MIMO) systems and provide performance comparisons in terms of maximum throughput in both uncorrelated and correlated channels when the number of transmit antennas is much larger than the number of receive antennas. It is shown that the multiuser MIMO schemes are preferable to time-division multiple-access (TDMA)-based MIMO schemes, hence demonstrating the power of multiuser MIMO signal processing. Our work also indicates possibilities for future research in finding efficient suboptimal algorithms. As an example, we show that our multiuser MIMO decomposition scheme can improve the maximum throughput compared to TDMA-based MIMO schemes for large number of transmit antennas or high transmit power.

We introduce a transmit preprocessing technique for the downlink of multiuser multiple-input multiple-output (MIMO) systems. It decomposes the multiuser MIMO downlink channel into multiple parallel independent single-user MIMO downlink channels. Some key properties are that each equivalent single-user MIMO channel has the same properties as a conventional single-user MIMO channel, and that increasing the number of transmit antennas of the multiuser system by one increases the number of spatial channels to each user by one. Simulation results are also provided and these results demonstrate the potential of our technique in terms of performance and capacity.

In this paper, we introduce a transmit multiple-input multiple-output (MIMO) scheme with frequency domain pre-equalization for a multipath or frequency selective channel. In this scheme, MIMO processing in the frequency domain is performed at the transmitter or base station so that the receiver or mobile station only requires limited processing. This scheme provides high data rates and also inherits from the frequency domain equalization the property of relatively low complexity in severe multipath environments. The MIMO transmit processing is derived by minimizing the minimum mean square errors (MMSE), and expressions for the signal-to-interference-plus-noise ratio and error probability based on the Gaussian approximation of the interference term are provided. Some important associated issues, such as channel errors and computational complexity, are also investigated. Numerical simulations are also provided and these demonstrate the improved performance of our proposed scheme compared to other transmit MIMO schemes. In particular, they show that the proposed system can attain multipath or frequency diversity of the channel.

This letter presents an analysis of the effect of narrowband interference (NBI) on ultrawideband (UWB) time-hopping (TH) systems in the presence of multipath fading using both analytical derivations and simulations. Our analysis demonstrates that NBI may be an issue in some instances. In addition, we suggest three NBI suppression schemes for combating NBI in UWB TH systems. Single-link performance of these schemes in conjunction with a Rake-type receiver structure is estimated for both the ideal all-Rake receiver and the simpler partial-Rake receiver in an indoor environment. Two UWB pulse shapes that meet the Federal Communications Commission rules for UWB communications are considered in the investigation.

In this letter, we propose two near maximum-likelihood detection (MLD) schemes for multiple input-multiple output antenna systems over flat fading channels. The schemes are based on utilizing an initial estimate of the received symbol and improving it by selectively updating various bits within the symbol. Simulation results show that the performance of the proposed schemes can approach that of MLD but with a significant reduction in complexity.

Frequency-domain equalization (FDE) has been shown to be an effective approach to combat frequency-selective wireless channels. In this letter, we propose a layered space-frequency equalization (LSFE) architecture for a single-carrier (SC) multiple-input multiple-output (MIMO) system, where MIMO FDE is employed at each stage or (layer) of detection. At a particular stage, a group of the best data streams in the minimum mean square error sense are detected and are canceled from the received signals. Simulation results show that our proposed LSFE structures can outperform layered space-time equalization (LSTE) structures and uncoded orthogonal frequency division multiplex (OFDM), especially at a higher delay spread. Performance is enhanced further, by incorporating the FDE with time-domain decision feedback at each stage of LSFE. We also provide performance analysis for LSFE, in comparison with OFDM.

This paper introduces a quadrature pulse amplitude modulation (QPAM) scheme for ultrawideband (UWB) wireless communications by utilizing two orthogonal pulses. An important advantage of QPAM over binary PAM is that it is more power efficient and this is critical in UWB communications. In addition we investigate the use of M-ary binary-coded QPAM signals to further increase the bit transmission rate supported by UWB communication systems. The power efficiencies of bipolar QPAM and M-ary binary-coded QPAM are compared. We also present a comparison of the role of time hopping (TH) and direct-sequence (DS) spreading in providing robust performance in multipath environments for UWB communications.

We incorporate transmit power allocation (PA) with layered space-time equalization (LSTE) for wireless MIMO systems in frequency selective channels. A so-called EQ-BER PA scheme is investigated, which aims at equalizing the BERs for all data streams. Simulation results show that EQ-BER PA can provide significant performance enhancement over the uniform power (UP) case in a wide range of RMS delay spread and at a high SNR. Intensive performance analysis is provided, of BER performance and signal detection ordering for LSTE with PA.

In this paper, optimized transmit schemes for multiple-input multiple-output (MIMO) systems with simplified receivers are proposed for the downlink of high-speed wireless communication systems. In these systems, MIMO signal preprocessing is performed at the transmitter or base station with the receiver at the mobile station having a simplified structure that requires only limited signal processing. An important potential application for our transmit MIMO techniques is in the downlink of high-speed wireless communication systems with Vertical Bell Laboratories Layered Space-Time (V-BLAST) or a similar technique utilized in the uplink, creating a high-speed duplex system with a simplified mobile station transceiver structure. Two approaches are introduced and these depend on whether or not receive diversity is employed at the receiver. Both methods require that channel state information be available at the transmitter. In addition, some important associated issues such as peak-to-average power ratio requirements at the transmitter and robustness to downlink channel errors are also investigated and various solutions are proposed. Simulation results are provided and these show that performance improvement can be achieved when compared with other MIMO transmit schemes.

We present a system to enhance signal-to-interference plus noise ratio (SINR) for multiple-input-multiple-output (MIMO) direct-sequence code-division multiple-access (DS/CDMA) communications in the downlink for frequency-selective fading environments. The proposed system utilizes a transmit antenna array at the base station and a receive antenna array at the mobile station with finite-impulse response filters at both the transmitter and receiver. We arrive at our system by attempting to find the optimal solution to a general MIMO antenna system. A single user joint optimum scenario and a multiuser SINR enhancement scenario are derived. In addition, a simplified one-finger receiver structure is introduced. Numerical results reveal that significant system performance and capacity improvement over conventional approaches are possible. We also investigate the sensitivity of the proposed system to channel estimation errors.

In this paper, we investigate the use of layered space-time (also known as the vertical Bell Laboratories layered space-time (V-BLAST) scheme) for multiuser detection in fading channels. The multiple transmit antennas in V-BLAST are treated as individual mobile station transmitters, while the base station consists of multiple receive antennas. In the proposed system, users are organized in groups and allocated a unique spreading code within the same group. Using these codes, we are able to separate the different groups, and layered space-time algorithm is then invoked to further remove the remaining interference between users. A decorrelator-type receiver-based layered space-time detection is proposed for both complex and real constellations. For the latter case, we derive our receiver after evaluating and comparing the performance of two decorrelators based on the V-BLAST scheme. It is demonstrated that a significant performance improvement and increase in system capacity is obtained with very low spreading factors. Further results are also introduced by considering reduced complexity receivers based on serial layered space-time group multiuser detection, and parallel layered space-time group multiuser detection.

In this paper, we address the problem of improving the performance of multiuser space-division multiplexing (SDM) systems where multiple independent signal streams can be transmitted in the same frequency and time slot. The problem is important in multiuser multiple-input multiple-output systems where communication from one base station to many mobile stations can occur simultaneously. Our objective is to devise a multiuser linear space-time precoder for simultaneous channel diagonalization of the multiuser channels enabling SDM. Our new approach is based on diagonalizing the multiuser channel matrices and we use a variation of successive Jacobi rotations. In addition to the diagonalization, our approach attempts to optimize the resultant channel gains for performance enhancement. Our method is valid for both frequency-flat and frequency-selective fading channels but we assume that the base station knows all the channels and that they are quasi-stationary.

We investigate layered space-time equalization (LSTE) architectures for multiple-input multiple-output (MIMO) frequency-selective channels. At each stage or layer of detection, a MIMO delayed decision feedback sequence estimator (MIMO-DDFSE) is used to tentatively detect a group of selected data streams, among which a subgroup of data streams are output and are canceled from the received signals. With the proposed architectures, the numbers of the tentatively detected data streams and output data streams can be different at different LSTE stages, while the MIMO-DDFSE can also reduce to the special cases of multiple-input single-output decision feedback equalizer (MISO-DFE), MISO-DDFSE, and MIMO-DFE, allowing tradeoffs between performance and complexity. We also derive the equalizer coefficients, discuss timing recovery, and consider channel estimation. Simulation results demonstrate the performance of the proposed LSTE structures and the tradeoffs between performance and complexity of the multistage structure and the single-stage version. We also demonstrate the impact of imperfect channel estimation, imperfect interference cancellation, the number of receive antennas, filter length, and oversampling on performance.

In this paper, we introduce an optimised transmit pre-processing technique to reduce multiple access interference in the downlink of TDD-CDMA systems with multiple transmit antennas employed at the base station. In this system, signal pre-processing is performed at the base station, so that a simplified receiver structure that consists of a one-ringer correlator can be utilized at the mobile station. Analytic solution for the optimised transmit pre-processing technique is derived by minimizing the transmit mean square error (MMSE). Numerical results are also provided and these demonstrate significant performance improvement when compared to the conventional RAKE system and the pre-RAKE MRC transmit diversity system.

We consider the problem of wireless communications in frequency selective multiple-input multiple-output (MIMO) channels. Our approach is to combine the attractive features of frequency-domain equalization (FDE) with a space-layered algorithm, which is referred to as layered space-frequency equalization (LSFE). In the LSFE architecture, at each stage of detection, a group of selected data streams are detected by using FDE, and are then cancelled from the received signals. This LSFE structure is also applied to the MIMO system with space-time block code (STBC). It is shown that the multistage LSFE significantly outperforms the previous single-stage structure, and all the LSFE structures provide better performance than their OFDM counterparts.

This paper presents a simplified bit allocation algorithm for OFDM multiple-input multiple-output (MIMO) systems that uses V-BLAST as a detection algorithm. The advantage of our approach is that only minimal feedback of information back to the transmitter is required while still maintaining good performance. We demonstrate by computer simulation that the proposed simplified bit allocation algorithm can significantly improve the system performance and still maintain a reasonable feedback loading compared to the traditional V-BLAST for an OFDM MIMO system in a frequency selective fading channel model.

We propose a layered space-time equalization (LSTE) architecture for multiple-input multiple-output (MIMO) frequency selective channels, based on the MIMO delayed decision feedback sequence estimation (MIMO-DDFSE) scheme. At each stage of detection, the MIMO-DDFSE is employed to tentatively detect a group of selected signal streams, and among them a sub-group of the best signal streams in the MMSE sense are output and are cancelled from the received signals. It is shown that this structure outperforms the previously developed LSTE structure based on the multiple-input single-output decision feedback equalization (MISO-DFE) scheme.

Space-time coding has been proposed as a coding scheme for multiple-input multiple output (MIMO) antenna systems. However, when the delay spread of the MIMO channel is too large there is significant performance degradation and there is a need for equalization. In this paper we use MLSE structures that decode the space-time codes and equalize the channel in one structure. The resulting complexity of MLSE is therefore increased and it is necessary to took at ways to minimize this. Here we compare the Forney and Ungerboeck forms and we find that the Ungerboeck form is more attractive. In particular its complexity does not depend on the number of receive antennas.

We address the problem of enhancing the performance (including the system capacity and average user bit error probability) of a multi-user multiple-input multiple-output (MIMO) system for communication from one base station to many mobile stations in multipath Rayleigh fading channels. This problem arises in multi-user space division multiplexing (SDM) systems where multiple independent signal streams can be transmitted in the same frequency band and time slot, through the exploitation of multiple antennas at both the base and mobile stations. Our objective is to devise a multi-user linear space-time precoder for simultaneous channel diagonalization of multi-user channels enabling orthogonal space division multiplexing (OSDM). Our approach is based on diagonalizing the multi-user channel matrices and we use a variation of successive Jacobi rotations. The assumption for this scheme is that the BS knows all the channels and the channel dynamics are quasi-stationary over a block of precoded bits as is typical of indoor, low mobility high speed wireless communications.

This paper presents an iterative bit and power allocation algorithm for an OFDM multiple-input multiple-output (MIMO) system in frequency selective fading channels and uses V-BLAST as a detection algorithm. Assuming knowledge of the instantaneous channel gains for all spatial channels at all the subcarriers in the receiver, bit and power is assigned to each spatial channel to minimize the total transmission power for a fixed bit error rate (BER). We demonstrate by computer simulation that the proposed iterative bit and power allocation algorithm can significantly improve the system performance compared to the traditional V-BLAST and singular value decomposition (SVD) algorithm for an OFDM MIMO system in a frequency selective fading channel model.

Currently one of the most promising techniques for realizing high spectral efficiencies over wireless links is Vertical-Bell Laboratories Layered Space-Time (V-BLAST). This technique employs multi-element antenna arrays at both the transmitter and receiver to increase the spectral efficiency. In contrast to previous work, we consider the performance of V-BLAST in a frequency-selective fading channel. In particular, we investigate the effect of delay spread on V-BLAST with various QAM modulation formats and different numbers of transmit and receive antennas for two types of delay spread distributions. Comparisons with a flat-fading channel are also provided.

This paper describes a new approach to the problem of enhancing the performance of a multiuser multiple-input-multiple-output (MIMO) system for communication from one base station to many mobile stations in both frequency-flat and frequency-selective fading channels. This problem arises in space-division multiplexing systems with multiple users where many independent signal streams can be transmitted in the same frequency and time slot through the exploitation of multiple antennas at both the base and mobile stations. Our new approach is based on maximizing a lower bound for the product of signal-to-interference plus noise ratio (SINR) of a multiuser MIMO system. This provides a closed-form (noniterative) solution for the antenna weights for all the users, under the constraint of fixed transmit power. Our solution is shown by simulation to have better performance than previously proposed iterative or noniterative solutions. In addition, our solution requires significantly reduced complexity over a gradient search-based method that directly optimizes the product SINRs while still maintaining similar performance. Our solution assumes channel state information is present at the base station or transmitter.

We provide an analysis of the performance of maximum likelihood detection (MLD) over flat fading channels in a wireless multiple input-multiple output (MIMO) antenna system. A tight union bound with an asymptotic form on the probability of symbol error rate (SER) for MIMO MLD systems with two-dimensional signal constellations (such as QAM and PSK) is introduced. Using this analytic bound, the performance of the MIMO antenna system is demonstrated quantitatively with respect to channel estimation, constellation size, and antenna configuration.

A BLAST receiver architecture based on the MIMO-DFE (multiple-input-multiple-out decision feedback equalizer) is proposed to combat FS (frequency selective) channels. At each stage of detection, an MIMO-DFE in the MMSE sense is employed to estimate signals simultaneously, and multiple signal streams are selected for output and contribute to interference cancellation. The MIMO-DFE based BLAST promises a performance advantage over the MISO-DFE (multiple-input-single-output DFE) based BLAST where a MISO-DFE is used at each stage. It is also shown that the MIMO-DFE based BLAST requires less complexity than the MISO-DFE based BLAST because fewer equalizer stages and less computation for ordering signals are required.

We assess the impact of layered space-time detection technique, known as V-BLAST, for multiuser detection over a packetized random access system based on CDMA and slotted Aloha. In this scheme, the multiple transmit antennas are treated as individual packet radio mobile stations, while the base station consists of multiple receive antennas. In addition, users are arranged in groups and allocated the same group signature sequence. The spreading technique is hence used to separate between the groups, and the layered space-time algorithm is then invoked to detect the signals from all users transmitting packets at the same time. A significant improvement in system throughput, delay and capacity are achieved.

In this paper, we investigate the use of layered space-time scheme, known as V-BLAST, for multiuser detection over the uplink of a DS/CDMA communication system. The multiple transmit antennas in V-BLAST are treated as individual mobile station transmitters, while the base station consists of multiple receive antennas. The layered space-time algorithm is then invoked to detect the signals from all users. In addition, CDMA is also applied. Groups of users are arranged and allocated the same signature sequence or spreading code. The groups of users are first separated using the group spreading codes, and the layered space-time detection algorithm is then invoked to further remove the remaining interference. It is demonstrated that a significant performance improvement and increase in system capacity are obtained with very low spreading factors.

The next generation wireless communication systems are expected to support a wide range of high-quality services which require high data rate transmission as well as high system capacities. One of the most promising techniques for realizing extraordinary spectral efficiencies over wireless links is V-BLAST (Vertical-Bell Laboratories Layered Space-Time). This is a new system proposed by Bell Laboratories as an extremely efficient scheme for high capacity communications in wireless environments. The V-BLAST technique employs a multi-element antenna array technology at both the transmitter and receiver to increase system capacity, data rate as well as spectral efficiency. In this paper, and in contrast to previous work, we consider the performance of V-BLAST in a frequency selective fading channel. In particular, we investigate the effect of time delay spread on V-BLAST.

A promising technique for significantly increasing the bandwidth efficiency and wireless transmission capacity is space division multiplexing. Vertical Bell Laboratories Layered Space-Time (V-BLAST) is one technique which exploits the rich scattered wireless channel by using multiple transmit and receive antennas. We extend the V-BLAST formulation to a multicarrier system devised for a more general frequency selective and time varying channels. In particular, we apply the spectral efficient orthogonal frequency division multiplexing (OFDM) transmission technique to V-BLAST with Reed-Solomon coding. This technique achieves high speed wireless data services and makes the system more robust against intersymbol interference (ISI). The proposed system performance is evaluated and investigated over time dispersive and multipath fading channels. The system maximum delay spread tolerance is also studied.

ALOHA systems are some of the most attractive options for wireless applications which include packet transmission. However, despite their flexibility and simplicity, they present a very low channel throughput. The objective of this paper is to analyze the performance of such a protocol based layered space-time scheme over wireless communication links. A multiuser environment is hence considered in which each user carries only one transmit antenna. A generalization of Vertical-Layered Space-Time (V-BLAST) technique for BPSK modulation is then invoked to detect the transmitted signals through the use of multiple receive antennas at the base station. We asses in this paper the gain achieved by the proposed receiver; denoted by rT-BLAST, compared to the conventional V-BLAST system. We first consider the performance of this system over flat fading channels for a variety of system parameters. Then, throughput and delay performance are analyzed under different packetized traffics. It is demonstrated through simulation results that a significant improvement in system capacity, throughput and delay are achieved.

A disadvantage of TDD systems compared to FDD systems is the additional interference that can occur between the uplink and downlink. An antenna array is incorporated at the base station in order to reduce interference problems in a TDD system. With the benefit of an approximately reciprocal channel of a TDD system, this array is not only utilized to receive signals in the uplink, but also is utilized to transmit signals in the downlink for reducing interference. New results on pre-RAKE antenna combining are used to achieve this and improved performance is demonstrated by simulation results.

Smart or adaptive antennas promise to provide significant increases in system capacity and performance in wireless communication systems. In this paper, we investigate the use of adaptive antennas at the base and mobile stations, operating jointly, to maximize the average signal-to-interference and noise ratio (SINR) of each packet in the system for frequency selective channels with prior knowledge of the channel at the transmitter. Our approach is based on deriving an analytic formula for the average packet SINR and using the Lagrange multiplier method to determine an optimum. We derive necessary conditions for an optimum solution and propose an analytical expression for the optimum. Our analytical expression is not guaranteed to be the global optimum but it does satisfy the derived necessary conditions and, in addition for frequency flat channels, our results reduce to expressions for optimal weights previously published. To demonstrate the potential of the proposed system, we provide Monte Carlo simulation results of the system bit-error rates and make comparisons with other adaptive antenna systems. These show that significant improvements in performance are possible in a wireless communications context.

The next-generation wireless personal and mobile communication systems are expected to accommodate not only high-quality voice services, but also a broad range of other multirate services. Of the various multiaccess techniques, wide-band code-division multiple access (CDMA) has been regarded as an important part of the third-generation wireless communication systems because of its high frequency utilization efficiency and suitability for handling multimedia and multirate services. In this paper, we consider a system with a simplified receiver structure for direct-sequence CDMA (DS/CDMA) wireless communication handsets, in which improved performance is demonstrated when compared to a conventional DS/CDMA system with a RAKE receiver at the mobile station. We arrive at this system by finding the optimal solution to a general multiple-input single-output (MISO) DS/CDMA smart antenna system. We find that this solution reduces to a pre-RAKE with space transmit diversity system under the assumption that a simple one-finger matched filter is used at the receiver. This system combines the advantages of pre-RAKE diversity and transmit antenna diversity. It is shown that significant system performance and capacity improvements are possible. The numerical results also reveal that this system is not too sensitive to channel estimation errors.

Several smart antenna systems have been proposed and demonstrated at the base station (BS) of wireless communications systems, and these have shown that significant system performance improvement is possible. We consider the use of adaptive antennas at the BS and mobile stations (MS), operating jointly, in combination with orthogonal frequency-division multiplexing. The advantages of the proposed system includes reductions in average error probability and increases in capacity compared to conventional systems. Multiuser access, in space, time, and through subcarriers, is also possible and expressions for the exact joint optimal antenna weights at the BS and MS under cochannel interference conditions for fading channels are derived. To demonstrate the potential of our proposed system, analytical along with Monte Carlo simulation results are provided.

We investigate the performance of a DS/CDMA system with multiple-input multiple-output (MIMO) antenna processing in the downlink. We formulate the weights for the transmit and receive antennas by trying to obtain the optimum signal-to-interference-plus-noise ratio (SINR) in a frequency selective fading channel. The gain of our MIMO CDMA system with the formulated weights is illustrated by employing computer simulations for various configurations of antennas to determine the average bit error rate (BER) performance. The simulation results reveal that our system can reduce the average BER significantly.

Wideband code-division multiple-access (CDMA) will be utilized in the third generation or 3G wireless communication systems because of its high frequency utilization efficiency and suitability for handling multimedia and multi-rate services. In this paper, we present a system with a simplified receiver structure for DS/CDMA wireless communication handsets, in which improved performance is demonstrated when compared to a conventional DS/CDMA system with a RAKE receiver at the mobile station. The proposed system is obtained by finding the optimal solution to a general multiple-input single-output (MISO) DS/CDMA smart antenna system. It is shown that this solution reduces to a pre-RAKE with space transmit diversity system under the assumption that a simplified receiver structure is invoked. Numerical results show that significant system performance and capacity improvements are possible. They also reveal that the proposed system is not too sensitive to channel estimation errors.

It is well-known that the capacity of a direct sequence CDMA system is multiple access interference limited. Adaptive antenna arrays and interference cancellation can significantly reduce the multiple access interference and can greatly enhance the system performance. This paper investigates the performance improvement that can be achieved by integrating adaptive antenna array processing and interference cancellation, where the receiver steers the beams of the adaptive antenna towards not only the desired user but the interferers as well to facilitate the interference cancellation process. We analyze how the use of an FFT beamformer preceding the 2-D RAKE receiver reduces the complexity of the receiver without severe degradation in the overall system performance.

In this paper, we investigate the use of MIMO antenna system to maximize the average SINR of each packet in the system, with prior knowledge of the channel at the transmitter. Our approach is based on deriving an analytic formula for the average packet SINR and using the Lagrange multiplier method to determine an optimum. Our proposed solution provides analytical expressions for the joint antenna weights at the base and mobile stations under frequency selective fading channels and co-channel interference conditions. To demonstrate the potential of the proposed adaptive antenna system, we provide Monte Carlo simulation results of the system bit error rates and make comparisons with conventional adaptive antenna systems. These show that significant improvements in performance are possible.

Over the years, several smart antenna systems have been proposed and demonstrated in wireless communications systems, and these have shown that significant system performance improvement is possible. In this paper, we consider the maximization of the spectral efficiency of a multiuser MIMO system for downlink communications (one base to many mobiles) in both frequency flat and selective fading channels. Each mobile (user) in the system incorporates an array of n/sub R/ antennas and in general transmits K/sub m//spl ges/1 space-time subchannels, in the same frequency spectrum and time slot. Our objective is to jointly find the antenna weights for all the users, under the constraint of fixed transmit power, so that the spectral efficiency of the system (or the average spectral efficiency per user) is maximized. An iterative procedure that successively nulls out all the broadcast interference is proposed, and simulation results show that multiuser MIMO optimization significantly outperforms single-user MIMO optimization. In addition, spectral efficiency close to an upper bound can be achieved.

We report an investigation into the effect of using smart antennas on the performance of the slotted ALOHA protocol with capture in a mobile communications environment with Rayleigh and log-normal fading. Our results demonstrate that by using smart antennas, we can achieve higher performance in terms of capture probability and throughput when compared to a conventional antenna system using the slotted ALOHA protocol.

We investigate the effect of time delay spread on trellis coded modulation (TCM) in a wireless radio environment where equalization is not employed to mitigate the effects of frequency selective fading when the time delay spread is small. Using a random variable decomposition technique and a Gaussian approximation of the intersymbol interference terms, we obtain explicit bounds for the pairwise error probability of TCM over multipath Rayleigh fading channels characterized by various power delay profiles. A method to calculate an upper bound of the bit error rate (BER) based on Jamali and LeNgoc (1995) bound is also presented. These bounds are used to evaluate TCM performance as well as investigate the delay spread tolerance limit of TCM, including I-Q TCM, over frequency selective fading channels.

Multiuser orthogonal frequency division multiplexing (OFDM) with adaptive multiuser subcarrier allocation and adaptive modulation is considered. Assuming knowledge of the instantaneous channel gains for all users, we propose a multiuser OFDM subcarrier, bit, and power allocation algorithm to minimize the total transmit power. This is done by assigning each user a set of subcarriers and by determining the number of bits and the transmit power level for each subcarrier. We obtain the performance of our proposed algorithm in a multiuser frequency selective fading environment for various time delay spread values and various numbers of users. The results show that our proposed algorithm outperforms multiuser OFDM systems with static time-division multiple access (TDMA) or frequency-division multiple access (FDMA) techniques which employ fixed and predetermined time-slot or subcarrier allocation schemes. We have also quantified the improvement in terms of the overall required transmit power, the bit-error rate (BER), or the area of coverage for a given outage probability.

The next-generation wireless communication systems are expected to support high-speed data transmission. Associated with high transmission rates, however, is the problem of multipath intersymbol interference (ISI) due to frequency-selective fading. Decision feedback equalization (DFE) and antenna diversity combining are two practical techniques for combating multipath ISI. Through simulations we investigate the performance of diversity combining, together with DFE, under various numbers of antenna branches and equalization taps, in a quasistationary frequency-selective fading environment with additive white Gaussian noise (AWGN) and cochannel interference (CCI). We consider joint optimization combining and power selection diversity combining. We simulate the combiner, using quaternary phase shift keying (QPSK) modulation with up to four antenna branches. Our results show that using antenna diversity and DFE with joint optimization combining provides performance improvement with lower computational complexity, as compared to that of using either DFE or diversity combining alone for combating ISI.

Optimal sounding sequences which satisfy a certain autocorrelation property are useful for fast channel estimation techniques which are based on noniterative channel sounding methods. We study optimal sequences consisting of complex symbols with constant magnitude. An indirect sequence construction method is derived by considering the phase difference between sequence symbols. Our construction method includes periodic and nonperiodic optimal sequences, and provides insight into the nature and properties of optimal sequences that are based on consecutive roots-of-unity phase difference sequences.

Adaptive equalization is a technique commonly used for correcting the multipath intersymbol interference (ISI) caused by frequency selective fading. For most equalization schemes, channel estimation is required. However, fast start-up channel estimation is needed to ensure quick equalizer convergence. As result, there has been much interest in finding fast channel estimation techniques which are based on non-iterative channel sounding methods. To obtain the best estimation performance, certain optimal sequences are required. Generally, it is difficult to construct optimal sequences with binary symbols because the optimal sequence length grows very rapidly as the channel impulse response length increases. In this paper, we propose a sequence construction method for sounding sequences consisting of complex symbols with constant amplitude and multiple phases. The advantage of using complex symbols is that an optimal sequence can always be constructed with a minimum sequence length. Our construction method generates new complex optimal sequences which are aperiodic in addition to the periodic sequences previously known.

Motion estimation and compensation are widely used in video coding. This paper presents two fast block matching algorithms for motion estimation. These algorithms use the subspace features of a block to determine the block distance. With a search block size of N/spl times/N, the proposed algorithms can achieve a computation reduction factor of N/2 while retaining close-to-optimal performance in the mean absolute difference (MAD) sense.

A new video coding method is proposed for application to very low bit rate coding of monochrome video. The new method depends on second generation image coding techniques. Specifically each frame of the video sequence is segmented into regions with closed boundaries which correspond to edges of objects within the frame. Novel contour motion estimation and also motion compensated coding are then introduced to achieve the very low bit rates required for transmission of visual telephony image sequences. The results show that the 256/spl times/256 "Miss America" sequences can be compressed to allow a transmission rate of lower than 64 kbits per second at a frame rate of 10 per second with acceptable quantity. Our eventual aim is to provide video telephone over plain old telephone services (POTS) at a rate lower than 10 kbit per second with reasonable quality.>

A new approach to indoor propagation prediction which is based on the Rayleigh-Gans approximation is proposed. The approach has been motivated by the observation that the indoor environment is different from the outdoor environment in that many of the structures within buildings are approximately the size of a wavelength making propagation prediction based on high frequency techniques not strictly applicable. In the paper details of the Rayleigh-Gans approximation are provided. Actual indoor propagation measurements are also provided to allow preliminary discussions on the accuracy of the Rayleigh-Gans approximation to be given. Comparisons with simulations of empirical and ray tracing models are also provided. The results indicate that further development would be worthwhile.>