This paper proposes a multi-user integrated sensing and communication (ISAC) framework based on coded generalized spatial shift keying (MU-CGSSK) that enables secure, interference-free downlink transmission alongside high-resolution radar sensing. The system adopts a separated deployment model, allowing simultaneous communication and sensing over a shared frequency band using co-located antenna arrays. A systematic linear block code is employed to generate structured antenna activation patterns that ensure low bit error rates and optimal MU separation. A key feature is the proposed two-stage physical layer security (PLS) scheme. In the first stage, a channel state information (CSI)-based precoder eliminates MU and radar-induced interference while generating implicit jamming against eavesdroppers. The second stage enhances confidentiality under partial CSI leakage by applying lightweight scrambling to antenna index mappings. An alternating optimization algorithm jointly designs the precoding vector and power allocation to maximize the achievable secrecy sum-rate. Simulation results demonstrate that the MU-CGSSK ISAC system achieves reliable MU communication, accurate multi-target detection using the MUSIC algorithm, and robust secrecy performance under asymmetric channel conditions.

This paper addresses the need for enhanced control over signal propagation in wireless communication using reconfigurable intelligent surfaces (RIS). We propose RIS-assisted backscatter communication (BC) systems, introducing a linear pre-processing-based spatial modulation (SM) technique for data transmission. Our work focuses on signaling design, phase shift optimization, and bit error rate (BER) evaluation through Monte-Carlo simulations. Results demonstrate that RIS-assisted pre-processing in BC enhances transmission reliability and energy efficiency, offering a promising solution for next-generation low-power communication systems.

In this paper, we explore the optimal use of network coding in multi-source multi-hop Internet of things (IoT) networks, focusing on minimizing the average age of information (AoI) under various system parameters. Specifically, we determine the optimal number of packets for performing network coding at intermediate nodes (servers) to optimize the average AoI performance. Through extensive simulations, we demonstrate how frequency of network coding impacts data freshness across a range of scenarios, including different numbers of sources, transmission success probabilities, and computational capacities. Simulation results provide practical insights into the deployment of network coding in real-world IoT applications, shedding light on the design process of how to implement network coding and highlighting its potential to significantly improve timeliness in data delivery.

In recent years, the increasing demand to see the status of objects over the Internet leads to an increase in the number of Internet of Things (IoT) applications. The unique nature of IoT, which involves potentially millions of interconnected devices with different data rate, power, bandwidth, and range specifications, requires different performance metrics than those conventionally employed in other communication applications. In conventional wireless communication systems such as cellular networks, performance indicators, including data rate and spectral efficiency, have become decisive, whereas in energy-constrained real-time IoT applications which require low data rate, the freshness of information has become a more prominent characteristic. Age of Information (AoI), which is the elapsed time after the last received packet update was created at the source, has emerged as a fundamental metric for determining the freshness of information and has attracted substantial research interest. In this regard, this article is dedicated to provide an overview of the current state of the art on the use of AoI for the design and optimization of a large variety IoT applications. After a brief introduction of the IoT and AoI fundamentals, this article presents a survey of the research works on common design issues, such as AoI-based optimization, scheduling for IoT networks, application of learning methods in large-scale IoT systems, real-life applications, and experimental results together with a synopsis of potential future applications and research challenges.

We investigate the timeliness in delivering updates within a multisource multihop Internet of Things (IoT) network via multicast transmissions with or without employing network coding, using a completely probabilistic model. Age of Information (AoI) is adopted to quantify the timeliness of packets. Extensive simulation results, which corroborate the theoretical findings, demonstrate that in scenarios where the number of sources is high, the number of intermediate nodes relaying to monitors is low, there are multiple monitors, the transmission success probability is low, and computational resources are sufficient, the utilization of network coding has a great potential to improve the data-freshness in multisource multihop IoT networks which closely represent the spine of the real-life scenarios.

Backscatter communications (BC) have gained significant attention in recent years, especially within the realm of internet of things (IoT), due to their ability to operate in a battery-free manner, maintaining the low-power and low-cost structure. The utilization of multiple antennas in BC is becoming increasingly recognized as a promising strategy to deliver robust communication performance, particularly in applications with high data demands. In this work an innovative BC system is introduced which is based on tag-side pre-processing aided receive spatial modulation (PSM). It includes the design of both zero-forcing (ZF) and minimum mean squared-error (MMSE) precoders for the transmitter tags, which enables the activation of a single receive antenna at the reader node (RN). Transmitting information via receive antenna indices presents several advantages when compared to other spatial modulation (SM)-based benchmark approaches employed for BC such as reduced complexity, enhanced energy efficiency, superior bit error rate (BER) performance and robustness to channel estimation errors. These advantages are shown via both both theoretical analysis and also simulation results in this paper.

We consider the timeliness in delivering an update consisting of multiple message packets to multiple users via multicast transmissions with or without employing network coding where Age of Information (AoI) is adopted to quantify the timeliness of packets. The expressions for peak and average expected AoIs are analytically derived for both uncoded and network coded transmissions for both 2-user and generalized$k$-users scenarios where the computational burden stemming from network coding is taken into account. The behavioral analyses of a number of network parameters are investigated, and the effect of data rate and computational capacity of nodes is analyzed. Simulations are performed for various Internet of Things (IoT) deployments, and the analyses suggest that the use of network coding for multicast transmissions can result in substantial AoI improvements, with the exception of scenarios in which sensors have extremely limited computational capabilities.

Since it uses active antenna indices to transmit information, spatial modulation (SM) is highly sensitive to transmit antenna and channel correlations, and precoding techniques to reduce this sensitivity are now well documented in the literature for single-stream SM with one active antenna. In this paper, we address the correlation issue for multi-stream SM (MSM) in which multiple antennas are active at a time. We show that conventional techniques fall short of efficiently compensating antenna and channel correlations in this case, and we introduce a novel precoding technique that significantly improves performance. Considering an MSM system with 4 transmit antennas and 2 parallel streams, we describe three variants of the proposed technique and evaluate its performance on Rayleigh fading and Rician fading channels. The results show a substantial improvement over conventional techniques, particularly on Rician fading channels.

We consider the physical layer security (PLS) of multi-user (MU) multiple-input-multiple-output visible light communication (VLC) systems with an eavesdropper (Eve) and propose a novel spatial constellation design technique based on generalized space shift keying (MU-GSSK-SCD). The received signals of the legitimate users are optimized jointly, such that their bit error ratios (BERs) are minimized and Eve's BER is significantly degraded. The emission power of randomly selected light-emitting diodes is adjusted, by exploiting users' channel state information at the transmitter. Our strategy ensures that legitimate users receive confidential messages fully in an undistorted fashion, while any meaningful leakage to Eve is strongly prohibited, without any artificial noise addition. Every user can decode only its information, hence inter-user security is also guaranteed. The PLS improvements are presented in terms of both BERs and achievable secrecy rates in practical VLC scenarios. For various user configurations, it is shown that MU-GSSK-SCD increases the BER at Eve to the 0.5 level, while providing minimized BERs to the legitimate users. The achievable secrecy rate region is derived for MU-GSSK-SCD and it is shown that full secrecy can be achieved at 0 dB signal-to-noise ratio (SNR) level with a user separation as small as 90 cm.

In some recent papers, the present authors revived an early non-orthogonal multiple access (NOMA) concept, which uses two sets of orthogonal signal waveforms and iterative interference cancellation. The beauty of this concept, which was introduced back in the year 2000, is that it fully avoids the power imbalance requirements of power-domain NOMA on which the current NOMA literature is heavily based. Using different type of receivers, these papers reported channel overload factors up to 25% on additive white Gaussian noise (AWGN) channels. In this paper, we investigate uplink performance on Rayleigh fading channels and we introduce a dynamic user grouping strategy, which leads to a substantial increase of the channel overload capability. Using this strategy, we show that the channel overload factor can be increased up to 100% at the expense of a virtually zero degradation of the signal-to-noise ratio (SNR).

Spatial modulation (SM) has a strong sensitivity to transmit antenna and channel correlations, because some of the information bits are assigned to active antenna selection, and the correlation limits the detection reliability of these bits. Recent approaches for the solution of this problem rely on either unequal error protection (UEP) of antenna and symbol bits with the addition of a channel encoder/decoder pair to the transceiver or precoding in the form of antenna-dependent rotation (or joint rotation and amplitude scaling) of the signal constellation. The UEP approaches have been shown to offer only limited efficiency in compensating for the adverse channel effects while increasing the latency and complexity due to the addition of the encoder/decoder. The precoding based approaches achieve good results for BPSK and QPSK signals, but the performance quickly degrades for higher-level QAM signal constellations. Also, the complexity of the precoder optimization problem increases with the number of transmit antennas and the modulation order, making this approach not very practical to use for large spectral efficiencies. This paper introduces a novel approach to this problem whose performance is independent of the modulation order. The key idea is to use signature constellations for different transmit antennas with an inter-constellation minimum Euclidean distance that is independent of the modulation order. The theoretical analysis and the simulation results show that compared to previous methods the new approach gives significant performance improvements in terms of robustness to transmit antenna correlation, particularly for Rician fading channels.

Enhanced inter-cell interference coordination (eICIC) techniques are designed to mitigate cross-tier interference in heterogeneous networks. Another advantage of eICIC is energy saving by the suppression of the data transmission over almost blank subframes (ABS). In this paper, we present the area spectral efficiency and worst-region capacity analysis, and then present an energy efficiency optimization problem with respect to the number of ABS's. The analysis comprises open access networks of macro/pico-cells and closed access networks of macro/femto-cells. We propose an optimization algorithm to evaluate the feasible regions for both open and closed access networks. The results include valuable feasible region comparisons and show energy efficiency gains achieved by the optimal number of ABS's for different network parameters.

In this paper, we consider the two prominent SON functionalities, namely load balancing (LB) and resource allocation (RA), in NOMA-enabled multi-cellular heterogeneous networks. Specifically, we propose distributed algorithms where the users are handed-over from the congested tiers to provide LB and RA is done in a way that co-channel interference is minimized. In order to reduce the effects of increased cochannel and the inter-user interference, a hybrid NOMA method is also adopted. Numerical results demonstrate that the joint consideration SON functions provides significant improvements in the data rate and fairness among users and as the number of users and base stations increases, application of hybrid NOMA is more beneficial in interference coordination. In addition, it is shown that NOMA can provide higher data rates compared to the existing orthogonal frequency division multiple access (OFDMA) schemes with proper user grouping methods.

Non-Orthogonal Multiple Access (NOMA) has been a hot research topic over the past few years, particularly because it is widely recognized that this technique represents a promising technology for massive Machine-Type Communications (mMTC) in future 5G cellular networks. The NOMA literature today is heavily focused on the so-called Power-Domain NOMA, which requires a strong power imbalance at the receiver between user signals. In some recent papers ([1] and [2]), the present authors revived a NOMA concept introduced back in the year 2000 and completely overlooked in the recent NOMA literature. This NOMA concept, which uses two sets of orthogonal signal waveforms and iterative interference cancellation at the receiver, fully avoids the power imbalance requirements of power-domain NOMA and makes it possible to grant the same data rates and performance levels to different users. In this paper, we first shed further light on the limitations of today's power-domain NOMA and we give insight on the potential of superposing the signals of two user groups with different characteristics instead of superposing two user signals. Next, we propose a new variant of the NOMA technique proposed in [1] and [2], which avoids the use of a complex interference canceler. This scheme achieves a 25% channel overloading factor at a negligible degradation of the signal-to-noise ratio (SNR) using a very simple maximumlikelihood (ML) receiver.

Non-orthogonal multiple access (NOMA) is considered one of the key techniques to increase spectral efficiency for 5G technologies. However, the superposition of non-orthogonal signals degrades the edge user performance due to additional interference from serving base stations. Therefore, the interference coordination becomes essential to provide fair service to all users. This paper presents an extensive coverage analysis of NOMA with well-known interference coordination schemes in the form of fractional frequency reuse in heterogeneous networks. The analysis include coexistence scenarios of NOMA with strict fractional frequency reuse and soft frequency reuse in both open and closed access $K$-tier heterogeneous networks. The numerical results indicate potential performance enhancements, especially in dense heterogeneous networks.

The densification of base station deployment for the next generation cellular networks raises the motivation to design energy efficient networks. In practice, most of the orthogonal frequency-division multiple access (OFDMA) based cellular networks employ fractional frequency reuse (FFR) to coordinate the resource block allocations. In this paper, we address stochastic geometry-based analysis and optimization of cellular networks employing OFDMA and FFR under energy efficiency constraints. Our analysis includes results for the average total capacity of a base station and the average capacity in the worst signal-to-interference-plus-noise ratio (SINR) region. Through the analytical derivations, two different optimization problems are formulated with the energy efficiency considerations. Numerical results indicate that resource block allocation in FFR is more energy efficient than transmit power adjustment for fulfilling the energy consumption and capacity constraints.

Non-orthogonal multiple access (NOMA) is recognized today as a most promising technology for future 5G cellular networks and a large number of papers have been published on the subject over the past few years. Interestingly, none of these authors seems to be aware that the foundation of NOMA actually dates back to the year 2000, when a series of papers introduced and investigated multiple access schemes using two sets of orthogonal signal waveforms and iterative interference cancellation at the receiver. The purpose of this paper is to shed light on that early literature and to describe a practical scheme based on that concept, which is particularly attractive for machine-type communications (MTC) in future 5G cellular networks. Using this approach, NOMA appears as a convenient extension of orthogonal multiple access rather than a strictly competing technology, and most important of all, the power imbalance between the transmitted user signals that is required to make the receiver work in other NOMA schemes is not required here.

We present a precoding approach for spatial modulation to provide robustness against both the Rayleigh/Rician fading effects and also spatial correlations among transmit antennas. This approach, based on phase-rotation and/or amplitude scaling of the transmitted symbols according to the active transmit antenna, can be implemented while preserving the average power budget and without any explicit knowledge of the channel coefficients at the transmitter. The optimum values of the precoding coefficients are determined so as to minimize the asymptotic average bit-error rate. Both theoretical analysis and simulation results indicate significant performance improvements even in the case of heavily correlated transmit antennas. Moreover, it is also shown that optimal precoding significantly compensates for the vulnerability of the antenna index bits against direct line-of-sight channel components and/or heavy inter-antenna correlations at the transmitter.

We present a precoding approach for spatial modulation (SM) to provide robustness against both the Rician fading effects and also spatial correlations among transmit antennas. This approach, based on phase-rotation and/or amplitude scaling of the transmitted symbols according to the active transmit antenna, can be implemented while keeping the average power budget and without any explicit knowledge of the channel state information at the transmitter. The optimum values of the precoding coefficients are determined so as to minimize the asymptotic average bit-error rate (ABER). Both theoretical analysis and simulation results indicate significant performance improvements even in the case of heavily correlated transmit antennas.

While multiple-input multiple-output (MIMO) is considered as the key enabling technology for high data rate wireless communications, it faces several major challenges in the 5th generation MIMO systems due to limited number of radio frequency (RF) chains and space restrictions. In light of this, generalized-spatial modulation (GSM) and dual- polarized (DP) antenna arrays are two potential technologies to tackle these challenges. In this paper, we propose a novel two-stage optimum antenna grouping scheme in GSM with DP antennas. In the first stage of the proposed scheme, we select antennas with their polarizations as group indicators followed by the second stage, which determines the potential antennas and polarizations that can be selected within each group. The proposed algorithm directly chooses the activated antennas and therefore, completely eliminates the necessity of search over an extensive space. We use the average bit error probability (ABEP) to analyze the performance of the system and validate them by extensive Monte Carlo simulations.

In this work, we propose an optimization framework for joint mobility load balancing (MLB), mobility robustness optimization (MRO) and inter-cell interference coordination (ICIC). The centralized optimization framework achieves balanced network load, avoids MLB related handover problems and considers interference management of the network. Although, this optimization framework forms a theoretical bound for the system capacity, it may also cause an excessive computational complexity to implement. That is why, we also propose a heuristic ICIC compatible conflict avoidance algorithm that provides a distributed solution to the same problem. The results obtained through extensive simulations show that the proposed distributed mobility management algorithm approximates to the optimal solution and offers significant improvements.

In this work, we propose a mobility management optimization framework for the networks employing full-frequency reuse. The mobility management issue is considered in the context of two main self-organizing networks (SON) functionalities, i.e mobility load balancing (MLB) and mobility robustness optimization (MRO) as a user-to-BS assignment problem. A central optimization method, which aims to maximize the load balance among the neighboring cells and minimize the HO related problems is given to solve the problem. Although the centralized optimization program forms a theoretical bound for the system capacity, it may also cause an excessive computational complexity to implement. That is why, we also propose a heuristic MRO, MLB conflict avoidance algorithm that provides a distributed solution to the same problem. Simulation results reveal the fact that proposed distributed mobility management algorithm approximates to the optimal solution significant and offers performance improvements in terms of the degrees of load balance and cell-edge throughput in comparison to the systems without mobility management and those employing conventional approaches.

We address multiple-input multiple-output (MIMO) communication employing spatial modulation (SM) with dual-polarized (DP) antennas. The proposed architecture adds the polarization dimension to the conventional SM mappings and offers performances, which are comparable to or under certain conditions even better than those of the uni-polarized systems while occupying half as much space. We consider the generalized spatially correlated Rayleigh and Rician fading channel models and present an average bit-error probability upper bounding framework for the proposed DP SM-MIMO system. The theoretical error analysis is also extended to the case where the channel coefficients are estimated with Gaussian estimation errors. This upper bounding method is also used to determine the conditions in which the dual-polarized SM is better than equivalent systems with uni-polarized antennas. Theoretical derivations are also validated by extensive simulations, both corroborating that SM combined with dual-polarization forms an attractive alternative not only for its improved multiplexing gains and space efficiency but also for performance gains over correlated channels.

We propose a novel multiple-input-multiple-output (MIMO) optical modulation method that combines binary polarization shift keying (BPOLSK) with pulse position modulation (PPM). The proposed approach, denoted BPOLSK-PPM, offers a good promise between power and spectral efficiencies compared to standard uses of PPM and BPOLSK. We provide a theoretical analysis to evaluate the performance of BPOLSK-PPM over free space optical (FSO) atmospheric turbulence channels and provide average bit error probability (ABEP) bounds for both uncoded and coded performances. The theoretical derivations are also corroborated via extensive simulation results and comparisons with conventional modulation approaches.

We investigate the error performance of both multilevel polarization shift keying (MPOLSK) and spatial modulation based MPOLSK (SM-MPOLSK) architectures for multiple-input-multiple-output (MIMO) communication over atmospheric turbulence channels. We first show that bit groups corresponding to each signalling dimension of these architectures are affected unequally from the turbulence induced scintillation and then propose unequal error protection (UEP) to increase the performance gains that can be attained by error control coding. We show by extensive simulation results that protection of each bit group with different protection ratios brings performance and spectral efficiency advantages over conventional approaches.

We consider a cooperative multiple access channel (MAC) with two energy harvesting transmitters. The transmitters perform delay constrained transmission, i.e., every information block is encoded, transmitted and decoded between two consecutive energy harvests. We aim to maximize the achievable departure region over a finite transmission duration. We formulate the departure region maximization as a convex optimization problem. We propose an iterative algorithm which uses a directional waterfilling strategy to calculate the optimal power components. The departure region obtained by cooperation is shown to be significantly larger than that of a MAC without cooperation under the same energy arrival patterns. As a special case, we also analyze an energy harvesting relay channel with full duplex cooperation.

In this work, multiple-input multiple-output (MIMO) communication employing spatial modulation (SM) is considered with dual-polarized antennas over correlated Rayleigh and Rician channels. A general average bit-error probability (ABEP) upper bounding framework is presented for the dual-polarized SM-MIMO systems. This framework is used to derive a closed form condition for the asymptotic feasibility regions for employing dual-polarization versus using uni-polarized antennas. Theoretical derivations are validated with extensive simulation results. Both analysis and simulation results indicate that especially in the case of correlated channels, the use of dual-polarized antennas for SM is more feasible in terms of both allocated space and error performance than equivalent systems implemented with uni-polarized antennas.

We consider the joint load imbalance and inter-cell interference (ICI) problems and propose a novel mobility load balancing (MLB) algorithm that is compatible with the well-known ICI coordination (ICIC) approaches relying on fractional frequency reuse (FFR). The algorithm is simulated both under the FFR as well as reuse-1 and - 3 frequency planing schemes. In addition, the simulations are performed with commonly used schedulers which show that the proposed MLB+ICIC algorithm provide significant improvements in the degree of load balance, cell-edge spectral efficiency and the number of unsatisfied users.

We propose spatial pulse position amplitude modulation (SPPAM) as a novel optical signaling scheme with the capability of having higher power and spectral efficiencies than those of conventional optical modulation techniques. We evaluate the performance of SPPAM in free space optical (FSO) communication systems over weak-to-moderate and moderate-to-strong atmospheric turbulence channels and provide average bit error probability (ABEP) bounds for both uncoded and coded performances. Theoretical derivations are validated with simulation results which show that SPPAM forms a feasible alternative to other FSO modulation approaches.

A polar coding scheme for bit-interleaved coded modulation (BICM) is proposed. Code construction is performed by extending Arikan's heuristic to parallel channels. A lower-complexity and numerically robust implementation of list decoding with cyclic redundancy check is adopted. The performance of the design methods used for the construction of proposed bit-interleaved polar coded modulation (BIPCM) system is evaluated over 16-ary quadrature-amplitude modulation with different mapping schemes. It is shown that the proposed BIPCM architecture provides significant performance advantages over the BICM schemes implemented with other well-known codes for moderate block lengths.

In this paper, we present a dynamic fractional frequency reuse (D-FFR) scheme for OFDMA based cellular networks. The proposed approach is extended from the so-called strict FFR architecture by allowing a fraction of the cell-edge frequencies to be shared by the edge users of the neighboring cells. This sub-band sharing flexibility not only alleviates the spectral deficiency of the strict FFR against soft frequency reuse (SFR) but also improves the already superior performance metrics such as the cell-edge signal-to-noise-plus-interference-ratio (SINR), outage probability and network sum rate throughput. It also provides robustness against sudden and uneven bursts of traffic in one of the cells of the networks. To this end, we provide an analytical framework to determine the coverage probability and the achievable rate of the proposed D-FFR scheme using the parametric models based on stochastic geometry and illustrate the benefits over static (strict or soft) frequency reuse methods via simulation results.

We present a general framework for the analysis of the effects of channel estimation errors on the average bit error probability (ABEP) of spatial modulation over correlated Rayleigh and Rician channels. The proposed approach is useful in obtaining the upper bound on the ABEP exactly for M-ary PSK constellations and with a very close approximation for M-ary QAM constellations. The framework is applicable to any number of transmit/receive antennas and to other linear constellations as well. Theoretical derivations are validated via simulation results.

We address coded spatial modulation (CSM) and present a novel approach denoted as bit-interleaved coded spatial modulation (BICSM) with iterative demodulation/decoding. The proposed transceiver architecture alleviates some drawbacks of the previously proposed CSM systems, such as being limited to a particular class of trellis codes or being effective only in limited channel scenarios. We specifically address the performance of BICSM over correlated Rayleigh and Rician fading channels and provide a general framework for the error performance analysis. Simulation results illustrate that BICSM provides not only significant performance improvements against channel fading in comparison to other CSM approaches but also higher robustness against antenna correlation effects.

We present a general upper bounding framework for the average bit error probability of spatial modulation over correlated Rayleigh and Rician channels. The proposed approach provides a closed form upper bound for correlated Rayleigh fading conditions whereas for correlated Rician channels it leads to the numerical evaluation of a single integral formula. The framework is applicable to a general class of linear modulation alphabets and any number of transmit/receive antennas. Theoretical derivations are validated via simulation results.

In this paper, a channel precoding technique is proposed for M-ary continuous phase modulation (CPM) for multipath downlink channels. The proposed pre-equalizer, based on the approximation of CPM signals by complex exponential functions, applies modulo-arithmetic operations to ensure the stability as in Tomlinson-Harashima method. Spectrally efficient precoded signals are obtained with small envelope variations by employing a transmit antenna selection technique. Because the equalization functions are transferred to the base station, the complexity in the mobile terminals is reduced significantly. The simulation results depict the power spectral density of the transmitted signals and the bit-error rate. An upper bound on the error performance is computed and the relation between the number of transmit antennas and the spectral efficiency is derived.

In this paper, two novel iterative chip-level synchronization methods, one blind and the other data-aided, are proposed for chip-interleaved time-hopping (TH) ultra-wideband signals that are subject to intersymbol interference (ISI) and multiple access interference (MAI). Both algorithms are soft-input, soft-output devices which receive the a posteriori probability of each chip from the minimum mean-square error (MMSE) filter that suppresses both ISI and MAI. Using this soft information and the structure of TH codes, the blind synchronizer produces the probabilities of time delays which are fed into the channel decoder. In addition to the knowledge of TH codes and the soft information coming from the MMSE filter, the data-aided synchronizer uses a training sequence in the generation of the probabilities of time delays. Although the channel decoder for chip-interleaved systems is rather simple, here it is redesigned to incorporate the soft information. The resulting receivers perform as well as iterative equalization with perfect timing information, and catch the single-user performance at moderate signal-to-noise ratios.

Frequency domain (FD) channel estimation and symbol detection for impulse radio ultra-wideband (IR-UWB) systems with short cyclic prefix (CP) is considered. For channel estimation FD recursive least squares (RLS) algorithm is used and equipped with a novel inter block interference (IBI) cancellation scheme. For signal detection, an iterative receiver structure is employed that is comprised of a FD soft input soft output (SISO) minimum mean squares error (MMSE) equalizer, a SISO repetition decoder and an IBI estimator. Simulation results show that the proposed receiver improves the channel estimation and signal detection significantly after only a few iterations.

In this paper, a doubly-iterative linear receiver, equipped with a soft-information aided frequency domain minimum mean-squared error (MMSE) equalizer, is proposed for the combined equalization and decoding of coded continuous phase modulation (CPM) signals over long multipath fading channels. In the proposed receiver architecture, the front-end frequency domain equalizer (FDE) is followed by the soft-input, softoutput (SISO) CPM demodulator and channel decoder modules. The receiver employs double turbo processing by performing back-end demodulation/decoding iterations per each equalization iteration to improve the a priori information for the front-end FDE. As presented by the computational complexity analysis and simulations, this process provides not only a significant reduction in the overall computational complexity, but also a performance improvement over the previously proposed iterative and noniterative MMSE receivers.

In this letter, an orthogonal space-time (ST) block coding (STBC) technique for continuous phase modulation (CPM) is proposed and combined with a frequencydomain equalizer (FDE) to obtain high performance gains over frequency-selective channels. The new method maintains the constant envelope and phase continuity of the CPM waveforms perfectly by using appropriate tail symbols during the addition of cyclic prefix and interblock transitions and, therefore, has no negative impact on the spectral efficiency. Because the STcoded CPM blocks remain orthogonal, FDE is applied as in the case of single antenna transmissions without any increase in the computational load. Simulations corroborate the performance improvement offered by STBC while also preserving the desired bandwidth efficiency of CPM.

Ultra-wideband (UWB) communication is envisaged to be deployed in indoor environments, where the noise distribution is decidedly non-Gaussian. A critical challenge for impulse radio UWB is the synchronization of nanosecond-long pulses. In this paper, we propose two acquisition schemes which are robust to uncertainties in the noise distribution and which operate directly on samples taken at symbol-rate. The only channel state information that the algorithms need can be obtained by estimation of an aggregate channel gain, avoiding channel-related complications. Following Huber's M-estimates for the Gaussian mixture noise model, the proposed robust acquisition systems outperform their traditional counterparts designed according to the Gaussian noise assumption. Necessary modifications for operation under multiple access interference are also introduced. Theoretical and simulation-based performance evaluations that reflect the asymptotic variance, normalized mean-square error and the bit error rates demonstrate the gains offered by the robust procedures.

Ultra-wideband (UWB) communications is envisaged to be deployed in indoor environments, where the noise distribution is decidedly non-Gaussian. A critical challenge for UWB is the synchronization of nanosecond-long pulses. In this paper, we propose a signal acquisition scheme that is robust to uncertainties in the noise distribution. Following Huber's M-estimates for the Gaussian mixture noise model, the successive sampling-based robust acquisition system outperforms Gaussian-optimal maximum likelihood approach. We present performance evaluation based on the normalized mean-square error and the bit-error rate.

Ultra-wideband (UWB) communications is envisaged to be deployed in indoor environments, where the noise distribution is decidedly non-Gaussian. A critical challenge for UWB is the synchronization of nanosecond-long pulses. In this paper, we propose an averaged template-based signal acquisition scheme that is robust to uncertainties in the noise distribution. Following Huber's M-estimates for the Gaussian mixture noise model, the averaged template-based robust acquisition system outperforms its traditional counterparts which are designed with Gaussian noise in mind. The authors present performance evaluation based on the asymptotic variance, normalized mean-square error, as well as the bit error rate.

In this paper, a doubly iterative receiver is proposed for joint turbo equalization, demodulation, and decoding of coded binary continuous-phase modulation (CPM) in multipath fading channels. The proposed receiver consists of three soft-input soft-output (SISO) blocks: a front-end soft-information-aided minimum mean square error (MMSE) equalizer followed by a CPM demodulator and a back-end channel decoder. The MMSE equalizer, combined with an a priori soft-interference canceler (SIC) and an a posteriori probability mapper, forms a SISO processor suitable for iterative processing that considers discrete-time CPM symbols which belong to a finite alphabet. The SISO CPM demodulator and the SISO channel decoder are both implemented by the a posteriori probability algorithm. The proposed doubly iterative receiver has a central demodulator coupled with both the front-end equalizer and the back-end channel decoder. A few back-end demodulation/decoding iterations are performed for each equalization iteration so as to improve the a priori information for the equalizer. As presented in the extrinsic information transfer (EXIT) chart analysis and simulation results for different multipath fading channels, this provides not only faster convergence to low bit error rates, but also lower computational complexity.

In this paper, a doubly-iterative receiver with a soft-information-aided frequency-domain minimum mean square error (MMSE) equalizer is proposed for coded continuous phase modulation (CPM). Equalization in the frequency-domain provides low computational complexity in long multipath fading channel responses. The front-end equalizer is followed by the soft- input soft-output (SISO) CPM and channel decoders at the back- end. The receiver exploits double turbo processing by employing back-end demodulation/decoding iterations per each equalization iteration to improve the a priori information for the front-end equalizer. Such processing results in high bit-error rate (BER) performance with less number of equalization iterations, as also shown in the simulation results.

The frequency-selective ultra-wideband (UWB) channels are subject to various types of electromagnetic noise, which is non-Gaussian (impulsive). The conventional linear receivers based on the additive white Gaussian noise assumption exhibit performance degradation. In this paper, a robust receiver using the M-estimation technique is introduced for multiple access UWB channels with impulsive noise, eliminating multiuser interference and impulsive noise at the same time, provided that accurate channel information about the users is available. Both the robust receiver and its simplified version are shown to outperform the linear receiver based on the Gaussian noise assumption.

In this paper, the convergence behavior of a doubly-iterative receiver, proposed for joint turbo equalization, modulation and decoding of coded binary continuous-phase modulation (CPM), is analyzed by using extrinsic information transfer (EXIT) charts. The doubly-iterative receiver consists of a central soft-input soft-output (SISO) CPM demodulator coupled with a front-end soft information aided minimum mean square error (MMSE) equalizer and a back-end SISO channel decoder. The EXIT chart analysis shows that performing a few back-end demodulation/decoding iterations per each equalization iteration improves the a priori information for the front-end equalizer, and provides faster convergence to low bit-error rates (BERs) with less computational complexity, as also illustrated in the BER simulations.

This paper considers the turbo equalization of trellis-coded modulated (TCM) broadband wireless signals that are affected by both intersymbol interference (ISI) due to multipath propagation and cochannel interference (CCI) due to the presence of adjacent users. Long channel dispersion causing both impediments to be severe makes the direct application of trellis-based turbo equalizers impossible, particularly for high-order signal modulations. For this reason, we present two computationally feasible space-time turbo receiver architectures employing linear antenna arrays and broadband beamformers. The first receiver uses a beamformer for joint rejection of interfering signals and shortening of the channel corresponding to the desired signal so that a scalar trellis-based turbo equalizer can be applied to its output. At each beamformer branch, the composite effect of the CCI and the white channel noise is viewed as colored noise. Because trellis search algorithms are limited to cases where the observation noise is white, this imposes quadratic noise whitening constraints on the beamformer design that is solved by a Lagrangian relaxation approach. The second receiver architecture removes the dependence on trellis search techniques for equalization by implementing the turbo equalizer directly with a soft-information-aided broadband beamformer at its front end and a soft-input soft-output (SISO) decoder at its back end. We outline the design considerations associated with each receiver and present bit error rate (BER) simulations for the turbo equalization of 8-phase-shift keying (PSK) TCM signals.

We address the doubly-iterative space-time equalization of broadband wireless signals for frequency selective multiple-input multiple-output (MIMO) systems employing M-ary modulation through bit to symbol mapping. The proposed receiver consists of a soft-information aided MMSE space-time equalizer processing antenna array observations at the front-end, followed by the serial concatenation of two soft-input soft-output (SISO) modules: a symbol-to-bit demapper and a channel decoder. In the proposed scheme, a new equalization stage is started only after several inner demapping/decoding iterations are applied to improve the soft decisions. The doubly iterative structure offers not only a reduced overall computational complexity but also a significant equalization gain as illustrated by the results.

This paper presents a space-time turbo (iterative) equalization method for trellis-coded modulation (TCM) signals over broadband wireless channels. For fixed wireless systems operating at high data rates, the multipath delay spread becomes large, making it impossible to apply trellis-based equalization methods. The equalizer proposed here consists of a broadband beamformer which processes antenna array measurements to shorten the observed channel impulse response, followed by a conventional scalar turbo equalizer. Since the applicability of trellis-based equalizers is limited to additive white noise channels, the beamformer is required to preserve the whiteness of the noise at its output. This constraint is equivalent to requiring that the finite-impulse response (FIR) beamforming filters must have a power complementarity property. The power complementarity property imposes nonnegative definite quadratic constraints on the beamforming filters, so the beamformer design is expressed as a constrained quadratic optimization problem. The composite channel impulse response at the beamformer output is shortened significantly, making it possible to use a turbo equalizer for the joint equalization and decoding of trellis modulated signals. The proposed receiver structure is simulated for two-dimensional TCM signals such as 8-PSK and 16-QAM and the results indicate that the use of antenna arrays with only two or three elements allows a large decrease in the channel signal-to-noise ratio needed to achieve a 10/sup -4/ bit-error rate.

We propose a low-complexity turbo space-time equalizer for signals transmitted over broadband wireless channels. The transmitter employs trellis coded modulation (TCM) for its bandwidth and power efficiency, and the broadband transmission is severely impaired by both intersymbol interference (ISI), due to multipath dispersion of the wireless channel, and cochannel interference (CCI), due to the presence of adjacent users. The proposed turbo equalizer consists of a broadband beamformer, which performs soft interference cancellation and space-time minimum mean-square error (MMSE) equalization, followed by a soft-in, soft-out (SISO) TCM decoder. A priori expected symbol values are used as soft inputs in the soft interference cancellation stage and then, after beamforming, the elements of the output sequence are mapped onto extrinsic log-likelihoods or probabilities using a Gaussian assumption. Because these two operations make the beamformer a SISO processor, the front-end of the space-time receiver is suitable for iterative processing. The proposed structure is implemented with small antenna arrays and simulated for turbo equalization of 8-PSK TCM signals, and simulation results indicate a relatively close performance to "no interference" bounds after only a small number of turbo iterations.

This paper presents a turbo (iterative) equalization method for complex TCM (trellis-coded modulation) signals over broadband wireless channels based on receiver antenna array measurements. The channel is highly dispersive at high data rates causing a severe intersymbol interference (ISI) effect and making the direct application of any trellis based equalization algorithm infeasible. The problem of reducing this excess interference is solved by receiver diversity combining, i.e. using a linear antenna array and a broadband beamformer in the receiver. The beamformer output that contains less ISI is viewed as the output of a serial concatenated coding system and optimum symbol detection is achieved by a turbo equalization and decoding scheme. The proposed receiver structure is simulated for two dimensional TCM signals such as 8-16 PSK and 16-QAM and the results indicate an improved performance of the diversity receiver.