This study addresses the challenge of access point (AP) and user equipment (UE) association in cell-free massive MIMO networks. It introduces a deep learning algorithm based on Bidirectional Long Short-Term Memory cells (a specific type of Recurrent Neural Network) and a hybrid probabilistic methodology for weight updating. This approach enhances scalability by adapting to variations in the number of UEs without requiring retraining. In addition, the study proposes a novel master-centric methodology for managing the AP-UE association process, which helps improve scalability not only with respect to the number of UEs, but also to that of APs. Furthermore, a variant of the proposed AP-UE algorithm ensures robustness against pilot contamination effects, a critical issue arising from pilot reuse in channel estimation. Extensive numerical results validate the effectiveness and adaptability of the proposed methods, demonstrating clear advantages over widely used heuristic alternatives.

This paper investigates a cell-free massive MIMO (multiple-input multiple-output) system where distributed access points (APs) perform integrated sensing and communications (ISAC) tasks, enabling simultaneous user communication and target detection/tracking. A unified framework and signal model are developed for detecting potential targets and tracking previously detected ones, even in arbitrary positions. Leveraging the Generalized Likelihood Ratio Test technique, novel detection/tracking algorithms are proposed to handle unknown target responses and interference. Scalable AP-user and AP-target association rules are evaluated, explicitly considering multi-zone sensing scenarios. Additionally, a scalable power control mechanism extends fractional power control principles to ISAC, balancing power allocation between communication and sensing tasks. For benchmarking, a non-scalable power control optimization problem is also formulated to maximize the minimum user data rate while ensuring a Quality of Service constraint for sensing, solved via successive convex approximation. Extensive numerical results validate the proposed framework, demonstrating its effectiveness in both communication and sensing, revealing the impact of interference from other targets, and highlighting fundamental trade-offs between sensing and communication performance.

This paper explores the challenges of user equipment (UE) association and downlink power control in scalable cell-free massive multiple-input multiple-output (MIMO) systems. Initially, we develop a scalable UE association algorithm, which ensures that each UE is connected to only a small set of access points (APs). This approach effectively reduces both fronthaul requirements and the computational load on the APs. The algorithm employs a competition-based mechanism to ensure that APs efficiently distribute workloads while satisfying the quality of service (QoS) requirements of UEs, preventing them from losing network connectivity. Second, we introduce a distributed downlink power control method based on deep neural networks (DNNs) to improve the long-term downlink spectral efficiency (SE) of the entire network. This method relies solely on locally collected large-scale fading information as DNN input, making it adaptable to dynamic scenarios involving varying numbers of associated UEs. To further enhance the training efficiency of the DNN, we design a distributed training framework that fully leverages the computational resources of distributed edge processors (EPs). Simulation results show that the proposed UE association algorithm and downlink power control method exhibit significant advantages over the benchmarks.

The impressive growth of wireless data networks has recently led to increased attention to the issue of electromagnetic pollution and the fulfillment of electromagnetic field (EMF) exposure limits. This paper tackles the problem of power control in user-centric cell-free massive multiple-input-multiple-output (CF-mMIMO) systems under EMF constraints. Specifically, the power allocation maximizing the minimum data rate across users is derived for both the uplink and the downlink. To solve such optimization problems, two approaches are proposed, i.e., model-based and data-driven. The proposed model-based solutions for the downlink utilize successive convex optimization and the log-sum-exp approximation for the minimum of a discrete set, whereas ordinary techniques are employed for the uplink. With regard to data-driven solutions, solutions based on both end-to-end architectures and deep unfolding techniques are explored. Extensive numerical results confirm that the proposed model-based solutions effectively fulfill the EMF constraints while ensuring very good performance; moreover, the results show that the proposed data-driven approaches can tightly approximate the performance of model-based solutions but with much lower computational complexity.

This paper tackles the problem of designing proper uplink multiple access schemes for coexistence between enhanced mobile broadband+ (eMBB+) users and massive machine-type communications+ (mMTC+) devices in a terminal-centric cell-free massive MIMO system. Specifically, the use of a time-frequency spreading technique for the mMTC+ devices has been proposed. Coupled with the assumption of imperfect channel knowledge, closed-form bounds of the achievable (ergodic) rate for the two data services are derived. Using suitable power control mechanisms, we show it is possible to efficiently multiplex eMBB+ and mMTC+ traffic in the same time-frequency resource grid. Numerical experiments reveal interesting trade-offs in the selection of the spreading gain and the number of serving access points within the system. Results also demonstrate that the performance of the mMTC+ devices is slightly affected by the presence of the eMBB+ users. Overall, our approach can endow good quality of service to both 6G cornerstones at once.

Millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) is one of the most promising technologies from 5G-based Internet of Things (IoT) to future wireless communication-based IoT, which usually relies on beamforming codebooks for data transmission. However, traditional codebooks often consist of numerous narrow beams, which causes substantial training overhead. Although centralized machine learning-based methods can address this issue to some extent, they overlook minority IoT devices scattered across various areas, which is vital for the coverage equity of the environmental adaptive codebook and the optimal average achievable rate. To circumvent the problem, we propose a distributed learning (DL) framework for codebook design in mmWave massive MIMO systems with uneven user distribution. Specifically, the user channel set is first divided into subsets by pre-classification based on the power responses of the featured combining vectors from different subregions. Then, a novel DL architecture processes these subsets, each assigned to different baseband processing boards (BPBs) in building baseband units, alleviating the centralized machine learning burden on the active antenna unit (AAU) or its directly connected BPB. Meanwhile, the current algorithms lack the hardware perspective or only implement the inference stage of the model. Thus, we deploy an FPGA-adapted DL-based codebook training prototype that runs on FPGA, which fully explores the “Backward-While-Forward" strategy for data reuse in the forward and backward passes. Simulation validates the effectiveness of distributed learning. Notably, the FPGA implementation on the embedded-level board outperforms consumer-grade CPU and GPU in terms of both latency and energy efficiency.

This paper considers an antenna structure where a (non-large) array of radiating elements is placed at short distance in front of a reconfigurable intelligent surface (RIS), herein nicknamed reconfigurable intelligent base station (RIBS). We firstly derive a closed-form expression for the channel between the array of radiating elements and the RIS that captures the near-field effects, and give some considerations on the channel hardening and favorable propagation in this scenario. Focusing on both active and passive RIS, we describe channel estimation and downlink signal processing techniques suitable for the RIBS structure. Additionally, we formulate and solve an optimization problem aimed at maximizing the fairness among the users with respect to the downlink power coefficients and RIS configuration both in the cases of active and passive RIBS. Numerical results show that the proposed structure is effective and capable of outperforming conventional non-RIS aided MIMO systems, especially in the case of active RIBS. The proposed antenna structure is thus shown to be able to approach massive MIMO performance levels in a cost-effective way with reduced hardware resources.

This article studies the cell-free massive multi-input multi-output (MIMO) two-way relay systems with low-resolution analog-to-digital converters (ADCs). Primarily, we analyze the normalized mean square error (NMSE) and derive a closed-form expression for NMSE’s expectation${\mathrm {Exp}}_{\mathrm {nmse}}$. Asymptotic analysis showcases that, with an infinite number of access point (AP) antennas M or ideal ADCs,${\mathrm {Exp}}_{\mathrm {nmse}}$converges to a finite value. Particularly, as pilot power decreases with M in a power law, the channel estimation performance can be maintained at a desired level. Secondly, we derive two closed-form expressions of spectral efficiencies (SE) for multiple-access channel (MAC) phase and broadcasting (BC) phases, respectively. The corresponding analysis implies that, as AP number$L\rightarrow \infty $, the SE tends to infinity with MAC phase and approaches to constant with BC phase. Interestingly, all SE expressions can reduce to the conventional cases with high-resolution ADCs. Finally, based on geometric programming, an effective power successive approximation (PSA) scheme is provided to maximize the sum SE. Results prove that the proposed PSA scheme can significantly improve the SE compared to baseline benchmarks, particularly for median AP antenna regime. All the derived closed-form expressions are validated through Monte Carlo simulations.

Millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) technology represents a promising technology in wireless communication. This technology relies on beamforming codebooks for initial access and transmission. However, conventional codebooks comprise a multitude of single-lobe narrow beams, resulting in redundant beams that may never be utilized in beam training. While centralized machine learning methods can partially address the concern of redundancy, they tend to overlook the presence of minority users scattered across diverse regions. The equitable coverage of environmental adaptive codebooks depends on addressing this issue. Hence, we devise a distributed learning (DL) framework for codebook design, which is tailored for scenarios with uneven user distribution and fully exploits the decentralized and online learning features of DL. Our approach begins by segmenting the user channels into various subsets through a pre-classification process. Then, we introduce a novel DL architecture designed to process the subsets that are assigned to individual user equipments (UEs). Each UE then generates a phase shift matrix that contributes to the concatenation-based global aggregation in the base station. The simulation results confirm the effectiveness of DL in improving the performance of mmWave massive MIMO systems in scenarios with unevenly distributed users.

The impressive growth of wireless data networks has recently led to increased attention to the issue of electromagnetic pollution. Specific absorption rates and incident power densities have become popular indicators for measuring electromagnetic field (EMF) exposure. This paper tackles the problem of power control in user-centric cell-free massive multiple-input-multiple-output (CF-mMIMO) systems under EMF constraints. Specifically, the power allocation maximizing the minimum data rate across users is derived for both the uplink and the downlink under EMF constraints. The developed solution is also applied to a cellular mMIMO system and compared to other benchmark strategies. Simulation results prove that EMF safety restrictions can be easily met without jeopardizing the minimum data rate, that the CF-mMIMO outperforms the multi-cell massive MIMO deployment, and that the proposed power control strategy greatly improves the system fairness.

In user-centric cell-free massive MIMO systems, a large number of low-complexity access points jointly serves a smaller number of mobile stations in the same communication bandwidth. Employing time division duplex mode and exploiting uplink/downlink channel reciprocity, the phases of uplink training and uplink/downlink data transmission sequentially take place within each channel coherence interval. This paper tackles the problem of integrated localization and communication in user-centric cell-free massive MIMO systems and proposes using the uplink decoded data as an additional virtual pilot to improve location and channel estimation for the mobile stations. In particular, after the usual training phase and uplink data transmission, the central processing unit shares the decoded uplink data with the access points, that use it as a long virtual pilot to refine the estimate of the users' locations. Extensive computer simulation results show the effectiveness of the proposed approach in the operating region of large Signal-to-Interference plus Noise Ratios.

The coupling of cell-free massive MIMO (CF-mMIMO) with Mobile Edge Computing (MEC) is investigated in this paper. A MEC-enabled CF-mMIMO architecture implementing a distributed user-centric approach both from the radio and the computational resource allocation perspective is proposed. A multi-objective optimization problem (MOOP) for the joint allocation of radio and remote computational resources is formulated, aimed at striking an optimal balance between total uplink power minimization and sum spectral efficiency maximization, under resource budget and latency constraints. In order to solve such a challenging non-convex problem, we convert the MOOP to an equivalent single-objective optimization problem (SOOP) through the weighted sum method and propose an iterative algorithm based on alternating optimization and sequential convex programming, along with an alternative heuristic resource allocation for distributed networks. Finally, we provide a detailed performance comparison between the proposed MEC-enabled CF-mMIMO architecture with its co-located counterpart, and its small-cell implementation. Numerical results reveal the effectiveness of the proposed resource allocation scheme, under different access point selection strategies, and the natural suitability of CF-mMIMO in supporting computation-offloading applications with benefits over users’ transmit power and energy consumption, the effective latency experienced, and the computation offloading efficiency.

This paper considers the problem of integrated sensing and communications in a user-centric cell-free massive MIMO system employing OFDM modulation. It is assumed that a large number of access points is using the same frequency band in order to communicate with a certain number of mobile users and to perform surveillance against potential targets in the surrounding area. The paper develops all the needed transceiver signal processing needed to implement both the communication and radar functionality, and provides expressions for the generic user downlink SINR and for the radar SNR. Numerical results are finally presented to show the effectiveness of the proposed system and to highlight the impact on the system performance of the different power split between the communication and radar functionalities, as well as of the access points and users density in the considered area.

This paper studies the downlink spectral efficiency of a two-way cell-free massive multiple-input multiple-output system with few-bit analog-to-digital converts (ADCs). By utilizing minimum mean squared error channel estimation method and maximal-ratio transmission precoder, we derive a closed-form expression for the effective downlink signal-to-interference-plus-noise ratio (SINR), which applies to any number of access point (AP) antennas M and distortion factors of ADCs in both AP and user pair sides. Additionally, the obtained analytical expression specializes to the conventional one when the ideal ADCs are adopted. Moreover, the asymptotic performance and power scaling law of the effective SINR in high M regime are studied. The corresponding analysis indicates that increasing M can provide considerable gains to compensate the rate loss caused by non-ideal ADCs and also, appropriately cutting down the pilot power and transmission power will not affect the SINR performance in high M region. Finally, all the theoretical results are verified via simulations.

The non-orthogonal coexistence between the enhanced mobile broadband (eMBB) and the ultra-reliable low-latency communication (URLLC) in the downlink of a multi-cell massive MIMO system is investigated in this work. We provide a unified information-theoretic framework blending an infinite-blocklength analysis of the eMBB spectral efficiency (SE) in the ergodic regime with a finite-blocklength analysis of the URLLC error probability. Puncturing (PUNC) and superposition coding (SPC) are considered as alternative coexistence strategies to deal with the inter-service interference. eMBB and URLLC performances are then evaluated over different precoding techniques and power control schemes, by accounting for imperfect channel state information knowledge at the base stations, pilot-based estimation overhead, spatially correlated channels, and the structure of the radio frame. Simulation results reveal that SPC is, in many operating regimes, superior to PUNC in providing higher SE for the eMBB yet achieving the target reliability for the URLLC with high probability. However, PUNC turns to be necessary to preserve the URLLC performance in scenarios where the multi-user interference cannot be satisfactorily alleviated.

In this paper, we employ a user-centric (UC) cell-free massive MIMO (CFmMIMO) network for providing ultra reliable low latency communication (URLLC) when traditional ground users (GUs) coexist with unmanned aerial vehicles (UAVs). We study power control in both the downlink and the uplink when partial zero-forcing (PZF) transmit/receive beamforming and maximum ratio transmission/combining are utilized. We consider optimization problems where the objective is to maximize either the users’ sum URLLC rate or the minimum user’s URLLC rate. The URLLC rate function is both complicated and nonconvex rendering the considered optimization problems nonconvex. Thus, we propose two approximations for the complicated URLLC rate function and employ successive convex optimization (SCO) to tackle the considered optimization problems. Specifically, we propose the SCO with iterative concave lower bound approximation (SCO-ICBA) and the SCO with iterative interference approximation (SCO-IIA). We provide extensive simulations to evaluate SCO-ICBA and SCO-IIA and compare UC CFmMIMO deployment with traditional colocated massive MIMO (COmMIMO) systems. The obtained results reveal that employing the SCO-IIA scheme to optimize the minimum user’s rate for CFmMIMO with MRT in the downlink, and PZF reception in the uplink can provide the best corresponding URLLC rate performances.

This paper addresses the problem of co-existence between a radar and a communication system that share the same frequency band. In particular, we investigate the role of a reconfigurable intelligent surface (RIS) in improving the performance of both systems and facilitating their co-existence. We consider the optimization problem of maximizing the radar signal to interference plus noise ratio (SINR) with respect to the active transmit beamformer at the radar, the passive RIS reflection coefficients, and the transmit covariance matrices of the communication system, subject to communication outage as well as radar and communication power constraints. This problem is solved through an alternating maximization procedure, first in the ideal scenario of perfect channel state information (CSI), and then in the case of incomplete CSI, using a statistical model of the CSI uncertainty. Numerical results demonstrate the effectiveness of our approach and quantify the beneficial effect of an RIS on the co-existence of a radar and a communication system.

This paper considers a monostatic multiple-input multiple-output (MIMO) radar aided by a reconfigurable intelligent surface (RIS). After modeling the received target signal as the superposition of four echoes, which may involve up to two bounces off the RIS, the phases of the reflecting elements and the radar receive filter are chosen to maximize the signal-to-noise ratio (SNR). Some examples are provided to assess the performance of this novel architecture.

This paper considers a mobile edge computing-enabled cell-free massive MIMO wireless network. An optimization problem for the joint allocation of uplink powers and remote computational resources is formulated, aimed at minimizing the total uplink power consumption under latency constraints, while simultaneously also maximizing the minimum SE throughout the network. Since the considered problem is non-convex, an iterative algorithm based on sequential convex programming is devised. A detailed performance comparison between the proposed distributed architecture and its co-located counterpart, based on a multi-cell massive MIMO deployment, is provided. Numerical results reveal the natural suitability of cell-free massive MIMO in supporting computation-offloading applications, with benefits over users’ transmit power and energy consumption, the offloading latency experienced, and the total amount of allocated remote computational resources.

As the standardization of 5G solidifies, researchers are speculating what 6G will be. The integration of sensing functionality is emerging as a key feature of the 6G Radio Access Network (RAN), allowing for the exploitation of dense cell infrastructures to construct a perceptive network. In this IEEE Journal on Selected Areas in Communications (JSAC) Special Issue overview, we provide a comprehensive review on the background, range of key applications and state-of-the-art approaches of Integrated Sensing and Communications (ISAC). We commence by discussing the interplay between sensing and communications (S&C) from a historical point of view, and then consider the multiple facets of ISAC and the resulting performance gains. By introducing both ongoing and potential use cases, we shed light on the industrial progress and standardization activities related to ISAC. We analyze a number of performance tradeoffs between S&C, spanning from information theoretical limits to physical layer performance tradeoffs, and the cross-layer design tradeoffs. Next, we discuss the signal processing aspects of ISAC, namely ISAC waveform design and receive signal processing. As a step further, we provide our vision on the deeper integration between S&C within the framework of perceptive networks, where the two functionalities are expected to mutually assist each other, i.e., via communication-assisted sensing and sensing-assisted communications. Finally, we identify the potential integration of ISAC with other emerging communication technologies, and their positive impacts on the future of wireless networks.

Driving a gradual integration of the physical and digital worlds is perceived to become a reality in the 6G era, from vehicles to drones, from surveillance facilities in cities to agricultural tools in the countryside. Jointly motivated by recent advances in communication and signal processing, radio sensing functionality can be integrated into a 6G radio access network (RAN) in a low-cost and fast manner. That is, future networks have the ability to “see” the physical world through imaging and measuring the surrounding environment, which enables advanced location-aware services, ranging from the physical to application layers. In essence, a radio emission could simultaneously convey communication data from the transmitter to the receiver and deliver environmental information from the scattered echoes. Therefore, sensing and communication (S&C) functionalities are possible to be co-designed to utilize resources efficiently and to assist each other for mutual benefits. This type of research is typically referred to as integrated sensing and communication (ISAC).

This is Part II of the double-part Special Issue (SI) on Integrated Sensing and Communication (ISAC). This SI aims at bringing together contributions from both academia and industry to highlight the recent progress of ISAC, where sensing and communication (S$\$ $C) functionalities are jointly designed to utilize wireless/hardware resources efficiently and to assist each other for mutual benefits. The 32 accepted articles of this SI are arranged into six groups, namely, 1) Fundamental Performance Bounds and Optimization, 2) Time-Frequency Signal Processing, 3) Spatial Signal Processing, 4) Networking and Resource Allocation, 5) ISAC With Emerging Communications Technologies, and 6) ISAC Applications. We kindly refer readers to Part I of this SI for a comprehensive overview written by the Guest Editorial Team, which provides both a bird’s eye view and technical details regarding state-of-the-art ISAC innovations. The contributions made by the papers in Part II are summarized as follows, which correspond to paper groups 4), 5), and 6).

Active reconfigurable intelligent surfaces (RISs) are a novel and promising technology that allows controlling the radio propagation environment while compensating for the product path loss along the RIS-assisted path. In this letter, we consider the classical radar detection problem and propose to use an active RIS to get a second independent look at a prospective target illuminated by the radar transmitter. At the design stage, we select the power emitted by the radar, the number of RIS elements, and their amplification factor in order to maximize the detection probability for a fixed probability of false alarm and a common (among radar and RIS) power budget. An illustrative example is provided to assess the achievable detection performance, also in comparison with that of a radar operating alone or with the help of a passive RIS.

In this paper, uplink transmission of a cell-free massive multiple-input multiple-output (CF-mMIMO) system coexisting with device-to-device (D2D) communication links is investigated, under the assumption that access points (APs) are equipped with low resolution analog-to-digital converters (ADCs). Lower bounds of achievable rates for both D2D users (DUEs) and CF-mMIMO users (CFUEs) are derived in closed-form, with perfect and imperfect channel state information. Next, in order to reduce pilot contamination, greedy and graph coloring-based pilot allocation algorithms are proposed and analyzed for the considered scenario. Furthermore, to control interference and improve the performance, two power control strategies are designed and their complexity and convergence are also discussed. The first power control strategy aims at maximizing CFUEs’ sum spectral efficiency (SE) subject to quality of service constraints on DUEs, while the second one maximizes the weighted product of CFUEs’ and DUEs’ signal-to-interference-plus-noise-ratios (SINRs). Numerical results show that the proposed pilot and power allocations bring a considerable improvement to the network SE. Also, it is revealed that the activation of D2D links has a positive effect on the system throughput, i.e. the network offloading ensured by the D2D links overcomes the increased interference brought by D2D communications.

This paper considers the problem of beam alignment in a cell-free massive MIMO deployment with multiple access points (APs) and multiple user equipments (UEs) simultaneously operating in the same millimeter wave frequency band. Assuming the availability of a control channel at sub-6 GHz frequencies, a protocol is developed that permits estimating, for each UE, the strongest propagation path from each of the surrounding APs, and to perform user-centric association between the UEs and the APs. Estimation of the strongest paths from nearby APs is realized at the UE in a one-phase procedure, during which all the APs simultaneously transmit on pseudo-randomly selected channels with pseudo-random transmit beamformers. An algorithm for orthogonal channels assignment to the APs is also proposed, with the aim of minimizing the mutual interference between APs that transmit on the same channels. The performance of the proposed strategy is evaluated both in terms of probability of correct detection of the directions of arrival and of departure associated to the strongest beam from nearby APs, and in terms of downlink and uplink signal-to-interference-plus-noise ratio. Numerical results show that the proposed approach is effective and capable of efficiently realizing beam alignment in a multi-UE multi-AP wireless scenario.

The problem of beam alignment (BA) in a cell-free massive multiple-input multiple-output (CF-mMIMO) system operating at millimeter wave (mmWaves) carrier frequencies is considered in this paper. Two estimation algorithms are proposed, in association with a protocol that permits simultaneous estimation, on a shared set of frequencies, for each user equipment (UE), of the direction of arrival and departure of the radio waves associated to the strongest propagation paths from each of the surrounding access points (APs), so that UE-AP association can take place. The proposed procedure relies on the existence of a reliable control channel at sub-6 GHz frequency, so as to enable exchange of estimated values between the UEs and the network, and assumes that APs can be identifies based on the prior knowledge of the orthogonal channels and transmit beamforming codebook. A strategy for assigning codebook entries to the several APs is also proposed, with the aim of minimizing the mutual interference between APs that are assigned the same entry. Numerical results show the effectiveness of the proposed detection strategy, thus enabling one shot fast BA for CF-mMIMO systems.

In this paper, a general framework for deep learning-based power control methods for max-min, max-product and max-sum-rate optimization in uplink cell-free massive multiple-input multiple-output (CF mMIMO) systems is proposed. Instead of using supervised learning, the proposed method relies on unsupervised learning, in which optimal power allocations are not required to be known, and thus has low training complexity. More specifically, a deep neural network (DNN) is trained to learn the map between fading coefficients and power coefficients within short time and with low computational complexity. It is interesting to note that the spectral efficiency of CF mMIMO systems with the proposed method outperforms previous optimization methods for max-min optimization and fits well for both max-sum-rate and max-product optimizations.

In this work, we consider the target detection problem in a sensing architecture where the radar is aided by a reconfigurable intelligent surface (RIS), that can be modeled as an array of sub-wavelength small reflective elements capable of imposing a tunable phase shift to the impinging waves and, ultimately, of providing the radar with an additional echo of the target. A theoretical analysis is carried out for closely- and widely-spaced (with respect to the target) radar and RIS and for different beampattern configurations, and some examples are provided to show that large gains can be achieved by the considered detection architecture.

Reconfigurable Intelligent Surfaces (RISs) are recently attracting a wide interest due to their capability of tuning wireless propagation environments in order to increase the system performance of wireless networks. In this paper, a multi-user single-cell wireless network assisted by a RIS is studied. First of all, for the special case of a single-user system, three possible approaches are shown in order to optimize the Signal-to-Noise Ratio with respect to the beamformer used at the base station and to the RIS phase shifts. Then, for a multi-user system, assuming channel-matched beamforming, the geometric mean of the downlink Signal-to-Interference plus Noise Ratios across users is maximized with respect to the base stations transmit powers and RIS phase shifts configurations. Numerical results show that the proposed procedures are effective and greatly improve the performance of the system.

Recently, the so-called cell-free (CF) massive multiple-input multiple-output (MIMO) architecture has been introduced, wherein a very large number of distributed access points (APs) simultaneously and jointly serve a much smaller number of mobile stations (MSs). The paper extends the CF approach to the case in which both the APs and the MSs are equipped with multiple antennas, proposing a beamfoming scheme that, relying on the zero-forcing strategy, does not require channel estimation at the MSs. We contrast the originally proposed formulation of CF massive MIMO with a user-centric (UC) approach wherein each MS is served only by a limited number of APs. Exploiting the framework of successive lower-bound maximization, the paper also proposes and analyzes power allocation strategies aimed at either sum-rate maximization or minimum-rate maximization, both for the uplink and downlink. Results show that the UC approach, which requires smaller backhaul overhead and is more scalable that the CF deployment, also achieves generally better performance than the CF approach for the vast majority of the users, especially on the uplink.

This paper considers the uplink of a massive MIMO communication system using 5G New Radio-compliant multiple access, which has to co-exist with a radar system using the same frequency band. A system model taking into account the reverberation (clutter) produced by the radar system onto the massive MIMO receiver is proposed. In this scenario, several receivers for uplink channel estimation and data detection are proposed, ranging from the simple channel-matched beamformer to the zero-forcing and linear minimum mean square error receivers for clutter disturbance rejection, under the two opposite situations of perfectly known and completely unknown clutter covariance. A theoretical analysis is also provided, deriving a lower bound on the achievable uplink spectral efficiency and the mutual information between the input Gaussian-encoded symbols and the observables available at the communication receiver of the cellular massive MIMO system: regarding the latter, in particular, it is shown that, in the large antenna number regime, and under the assumption of perfect channel state information (CSI), the effect of radar clutter at the base station is suppressed and single-user capacity may be restored. Numerical results, illustrating the performance of the proposed detection schemes, confirm the findings of the theoretical analysis, and permit quantifying the system robustness to clutter effect for increasing number of antennas at the base station.

In this paper we consider a massive multiple-input multiple-output (MIMO) communication system using 5G New Radio-compliant multiple access, which is to co-exist with a radar system using the same frequency band. Building upon a recently proposed system model taking into account the reverberation (clutter) produced by the radar system at the massive MIMO receiver, we provide a theoretical analysis, in terms of a lower bound on the achievable uplink (UL) spectral efficiency (SE) and in terms of the mutual information of the cellular massive MIMO system, showing that for large number of antennas at the base station the radar clutter effects can be suppressed. Simulation results confirm the paper theoretical findings.

Factory automation is one of the most challenging use cases for 5G-and-beyond mobile networks due to strict latency, availability and reliability constraints. In this work, an indoor factory scenario is considered, and distributed multiple- input multiple-output (MIMO) schemes are investigated in order to enable reliable communication to the actuators (ACs) active in the factory. Different levels of coordination among the access points serving the ACs and several beamforming schemes are considered and analyzed. To enforce system reliability, a max-min power allocation (MPA) algorithm is proposed, aimed at improving the signal to interference plus noise ratio (SINR) of the ACs with the worst channel conditions. Extensive system simulations are performed in a realistic scenario, which includes a new path-loss model based on recent measurements in factory scenarios, and, also, the presence of non-Gaussian impulsive noise. Numerical results show that distributed MIMO schemes with zero-forcing (ZF) beamforming and MPA have the potential of providing SINR gains in the order of tens of dB with respect to a centralized MIMO deployment, as well as that the impulsive noise can strongly degrade the system performance and thus requires specific detection and mitigation techniques.

Ultra-high reliability and low latency have not been in the mainstream in most wireless networks. Mobile networks have been driven so far by human-centric communications, delay-tolerant content, and non-critical services. The main target have been to boosting data rate and increasing coverage, adopting a rather best-effort networking approach. As wireless connectivity starts to get the status of a commodity, there is an increasing focus on support of services that rely critically on wireless links and therefore the reliability of the wireless connections. Next generation wireless systems, mainly 5G and beyond, are designed to provide wireless connectivity for massive machine-type communications (mMTC) and to support ultra-reliable, low latency communication (URLLC) for mission-critical services. URLLC scenarios impose stringent requirements in terms of latency (ranging from 1 ms and below to few milliseconds end-to-end latency depending on the use cases) and reliability (higher than 99.9999%). This does not mean that there are interesting applications where reliability is of paramount importance, while latency can be in the order of seconds, as in e.g. certain remote healthcare applications. Nevertheless, the coupling of low-latency networking and reliable communication is mainly driven by the need to push the technology boundaries and address a plethora of socially useful services and business domains that could benefit greatly from it. Some of the most challenging use cases are factory automation and industrial control, automated driving/flying, haptic communications, and real-time remote healthcare. URLLC is also expected to revolutionize processes in the areas of smart cities, smart farming, smart grid, remote manufacturing, and algorithmic trading. Although the URLLC constraints and the nature of real-time mission-critical applications imply the predominance of short packets and low-rate transmissions, future evolution of URLLC may also consider rate requirements. The emergence of immersive services, such as augmented and virtual reality (AR/VR), high-definition entertainment and gaming, and consumer robotics, calls for real-time, high-fidelity, broadband networks operating at latencies of few milliseconds.

The problem of multiple-input multiple-output (MIMO) channel estimation at millimeter-wave frequencies, both in single-user setting and in multi-user setting, is tackled in this paper. Using a subspace approach, we develop a protocol enabling the estimation of the right (respectively, left) singular vectors at the transmitter (respectively, receiver) side; then, we adapt the projection approximation subspace tracking with deflation and the orthogonal Oja algorithms to our framework and obtain two-channel estimation algorithms. We also present an alternative algorithm based on the least squares approach. The hybrid analog/digital nature of the beamformer is also explicitly taken into account at the algorithm design stage. In order to limit the system complexity, a fixed analog beamformer is used at both sides of the communication links. The obtained numerical results, showing the accuracy in the estimation of the channel matrix dominant singular vectors, the system achievable spectral efficiency, and the system bit error rate, prove that the proposed algorithms are effective and that they compare favorably, in terms of the performance-complexity tradeoff, with respect to several competing alternatives.

The universal filtered multicarrier (UFMC) modulation is among the most considered solutions for the realization of beyond orthogonal frequency division multiplexing (OFDM) air interfaces for future wireless networks. This paper focuses on the design and analysis of a UFMC transceiver equipped with multiple antennas and operating at millimeter-wave carrier frequencies. This paper provides the full mathematical model of an MIMO-UFMC transceiver, taking into account the presence of hybrid analog/digital beamformers at both ends of the communication links. Then, several detection structures are proposed, both for the case of single-packet isolated transmission and for the case of multiple-packet continuous transmission. In the latter situation, this paper also considers the case in which no guard time among adjacent packets is inserted, trading off an increased level of interference with higher values of spectral efficiency. At the analysis stage, several considered detection structures and transmission schemes are compared in terms of bit-error rate, root-mean-square error, and system throughput. The numerical results show that the proposed transceiver algorithms are effective and that the linear minimum mean-square error (MMSE) data detector is capable of well managing the increased interference brought by the removal of guard times among consecutive packets, thus yielding throughput gains of about 10%-13%. The effect of phase noise at the receiver is also numerically assessed, and it is shown that the recursive implementation of the linear MMSE exhibits some degree of robustness against this disturbance.

This paper provides results on the use of the Universal Filtered MultiCarrier (UFMC) modulation scheme in multiple-input-multiple-output (MIMO) wireless links operating at millimeter wave (mmWave) frequencies. After having provided mathematical details on the MIMO-UFMC signal model, taking into account both the hybrid analog/digital nature of the beamformers and the phase noise (PN) at the receiver, we propose adaptive algorithms, based on the normalized least-mean-squares (NLMS) and on the recursive-least-squares (RLS), for low-complexity data-detection. The proposed transceiver also includes a channel independent transmit beamformer, so as to avoid the need for channel state information at the transmitter, as well as a transmission format wherein no spacing between consecutive data packets is adopted, in order to have increased spectral efficiency. Numerical results show that the proposed algorithms exhibit a certain amount of robustness to the PN and achieve satisfactory performance.

This paper presents results on the achievable spectral efficiency and on the energy efficiency for a wireless multiple-input-multiple-output (MIMO) link operating at millimeter wave frequencies (mmWave) in a typical 5G scenario. Two different single-carrier modem schemes are considered, i.e., a traditional modulation scheme with linear equalization at the receiver, and a single-carrier modulation with cyclic prefix, frequency-domain equalization and fast Fourier transform-based processing at the receiver; these two schemes are compared with a conventional MIMO orthogonal frequency division multiplexing transceiver structure. Our analysis jointly takes into account the peculiar characteristics of MIMO channels at mmWave frequencies, the use of hybrid (analog-digital) pre-coding and post-coding beamformers, the finite cardinality of the modulation structure, and the non-linear behavior of the transmitter power amplifiers. Our results show that the best performance is achieved by single-carrier modulation with time-domain equalization, which exhibits the smallest loss due to the non-linear distortion, and whose performance can be further improved by using advanced equalization schemes. Results also confirm that performance gets severely degraded when the link length exceeds 90–100 m and the transmit power falls below 0 dBW.

In a cell-free (CF) massive MIMO architecture a very large number of distributed access points (APs) simultaneously and jointly serves a much smaller number of mobile stations (MSs); a variant of the cell-free technique is the user-centric (UC) approach, wherein each AP just decodes a reduced set of MSs, practically the ones that are received best. This paper introduces and analyzes the CF and UC architectures at millimeter wave (mmWave) frequencies. First of all, a multiuser clustered channel model is introduced in order to account for the correlation among the channels of nearby users; then, an uplink multiuser channel estimation scheme is described along with low-complexity hybrid analog/digital beamforming architectures. Interestingly, in the proposed scheme no channel estimation is needed at the MSs, and the beamforming schemes used at the MSs are channelindependent and have a very simple structure. Numerical results show that the considered architectures provide good performance, especially in lightly loaded systems, with the UC approach outperforming the CF one.

Recently, the so-called cell-free Massive MIMO architecture has been introduced, wherein a very large number of distributed access points (APs) simultaneously and jointly serve a much smaller number of mobile stations (MSs). A variant of the cell-free technique is the user-centric approach, wherein each AP just decodes the MSs that it receives with the largest power. This paper considers both the cell-free and user-centric approaches, and, using an interplay of sequential optimization and alternating optimization, derives downlink power-control algorithms aimed at maximizing either the minimum users' SINR (to ensure fairness), or the system sum-rate. Numerical results show the effectiveness of the proposed algorithms, as well as that the user-centric approach generally outperforms the CF one.

One of the key features of next generation wireless communication systems will be the use of frequencies in the range 10-100GHz (aka mmWave band) in densely populated indoor and outdoor scenarios. Due to the reduced wavelength, antenna arrays with a large number of antennas can be packed in very small volumes, making thus it possible to consider, at least in principle, communication links wherein not only the base-station, but also the user device, are equipped with very large antenna arrays. We denote this configuration as a ``doubly-massive'' MIMO wireless link. This paper introduces the concept of doubly massive MIMO systems at mmWave, showing that at mmWave the fundamentals of the massive MIMO regime are completely different from what happens at conventional sub-6 GHz cellular frequencies. It is shown for instance that the multiplexing capabilities of the channel and its rank are no longer ruled by the number of transmit and receive antennas, but rather by the number of scattering clusters in the surrounding environment. The implications of the doubly massive MIMO regime on the transceiver processing, on the system energy efficiency and on the system throughput are also discussed.

After about a decade of intense research, spurred by both economic and operational considerations, and by environmental concerns, energy efficiency has now become a key pillar in the design of communication networks. With the advent of the fifth generation of wireless networks, with millions more base stations and billions of connected devices, the need for energy-efficient system design and operation will be even more compelling. This survey provides an overview of energy-efficient wireless communications, reviews seminal and recent contribution to the state-of-the-art, including the papers published in this special issue, and discusses the most relevant research challenges to be addressed in the future.

This paper addresses the problem of energy-efficient resource allocation in the downlink of a cellular orthogonal frequency division multiple access system. Three definitions of energy efficiency are considered for system design, accounting for both the radiated and the circuit power. User scheduling and power allocation are optimized across a cluster of coordinated base stations with a constraint on the maximum transmit power (either per subcarrier or per base station). The asymptotic noise-limited regime is discussed as a special case. Results show that the maximization of the energy efficiency is approximately equivalent to the maximization of the spectral efficiency for small values of the maximum transmit power, while there is a wide range of values of the maximum transmit power for which a moderate reduction of the data rate provides large savings in terms of dissipated energy. In addition, the performance gap among the considered resource allocation strategies is reduced as the out-of-cluster interference increases.

In this paper, the issue of energy-aware competitive resource allocation in an amplify-and-forward (AF) relay-assisted multiple-antenna interference network is considered. A non-cooperative game-theoretic approach is taken and the EE of each communication link is defined as the ratio of the achievable rate over the consumed power. The proposed resource allocation algorithm jointly allocates the relay AF, the users' transmit powers and receive filters. The resulting resource allocation algorithm is shown to converge to a unique fixed point and to have limited feedback and computational requirements. Numerical results are provided to illustrate the performance gain with respect to resource allocation policies that do not perform a joint allocation of the network resources.

What will 5G be? What it will not be is an incremental advance on 4G. The previous four generations of cellular technology have each been a major paradigm shift that has broken backward compatibility. Indeed, 5G will need to be a paradigm shift that includes very high carrier frequencies with massive bandwidths, extreme base station and device densities, and unprecedented numbers of antennas. However, unlike the previous four generations, it will also be highly integrative: tying any new 5G air interface and spectrum together with LTE and WiFi to provide universal high-rate coverage and a seamless user experience. To support this, the core network will also have to reach unprecedented levels of flexibility and intelligence, spectrum regulation will need to be rethought and improved, and energy and cost efficiencies will become even more critical considerations. This paper discusses all of these topics, identifying key challenges for future research and preliminary 5G standardization activities, while providing a comprehensive overview of the current literature, and in particular of the papers appearing in this special issue.

This paper considers the problem of energy-efficient communication in the downlink of a cellular OFDMA network. User scheduling and power allocation are jointly optimized across a cluster of coordinated base stations so as to maximize the weighted sum of the energy efficiencies on the available resource slots under a per-subcarrier power constraint. The asymptotic noise-limited regime is also discussed as a special case. Numerical results show that there is a wide range of operating regimes where a moderate reduction of the data rate can provide a large saving in terms of dissipated energy.

In this paper, the issue of competitive, energy- efficient power control in a relay-assisted interference channel is considered. The energy efficiency is measured in bit/Joule and is defined as the ratio of a SINR-based function, divided by the sum of the transmit power plus the circuit power consumed to operate the device. Taking also into account the direct path between transmitters and receivers, a non-cooperative power control game is devised. The proposed game is shown to always admit a Nash equilibrium and, based on its best-response dynamics, a power control algorithm that can be implemented in a fully distributed way is provided. Finally, numerical results are provided to show the merits of the proposed algorithms.

We propose a new spread spectrum (SS) system based on continuous-phase modulations (CPMs). The main idea is to exploit the sequence of modulation indices of a multi-h CPM as a frequency-hopping (FH) sequence. Spectral spreading, flatness and smoothness can be easily achieved by an appropriate choice of the maximum value of the modulation index and of the length of the index sequence. We will show that the proposed CPM-based spread spectrum system achieves an overall spectral efficiency larger than that of a single-user single-h CPM transmission even when a single-user detector is employed at the receiver. It also outperforms other solutions in the literature. In addition, we will also derive some suboptimal multi-user detectors.

Competitive power control for energy efficiency maximization in wireless interference networks is addressed, for the scenarios in which the users' SINR can be expressed as either (a) γ = (αp)/(φp + ω), or (b) γ = (αp + βp2)/(φp + ω), with p the user's transmit power. The considered SINR expressions naturally arise in relay-assisted systems. The energy efficiency is measured in bit/Joule and is defined as the ratio of a proper function of the SINR, divided by the consumed power. Unlike most previous related works, in the definition of the consumed power, not only the transmit power, but also the circuit power needed to operate the devices is accounted for. A non-cooperative game theoretic approach is employed and distributed power control algorithms are proposed. For both SINR expressions (a) and (b), it is shown that the competitive power allocation problem always admits a Nash equilibrium. Moreover, for the SINR (a), the equilibrium is also shown to be unique and the best-response dynamic is guaranteed to converge to such unique equilibrium. For the two-user case, the efficient computation of the Pareto frontier of the considered game is addressed, and, for benchmarking purposes, a social optimum solution with fairness constraint is derived.

We propose a new spread spectrum (SS) system based on continuous phase modulations (CPMs). The main idea is to exploit the sequence of modulation indices of a multi-h CPM as a frequency hopping (FH) sequence. We will show how the sequence of indices impacts on the CPM signal bandwidth and power spectral density (PSD). Spectral spreading, flatness and smoothness can be easily achieved by an appropriate choice of the maximum value of the modulation index and of the length of the index sequence. We will show that a CPM-based spread spectrum system achieves an overall spectral efficiency larger than that of a single-user single-h CPM signal even when a single-user detector is employed at the receiver.

In this paper, the issue of non-cooperative, energy-efficient power control in a relay-assisted interference channel is considered. The energy efficiency of a given terminal is defined as the ratio between the throughput of that terminal and the consumed power. As far as the computation of the consumed power is concerned, not only the transmit power, but also the power dissipated in terminal's electronic circuitry to operate the device is considered. A non-cooperative power control game is devised, which admits a unique Nash equilibrium, and whose best-response-dynamics is guaranteed to converge to the unique equilibrium. A cooperative power control algorithm is also devised, which is used as a benchmark for the non-cooperative game. Finally, numerical results are provided to show the merits of the proposed algorithms.

This paper considers the issue of spreading code allocation and receiver optimization in a CDMA-based multiuser data network. Assuming that non-linear serial interference cancellation is performed at the receiver, the problem of noncooperative SINR maximization with respect to each user's spreading code and uplink receiver is first considered. It is shown that iterative SINR maximization converges in a finite number of steps, and that the equilibrium resulting from noncooperative behavior is also Pareto-optimal. Next, the problem of optimal multiuser detection for a system using the above optimal spreading codes is also considered, and it is shown that, for such a system, maximum likelihood detection entails a computational complexity that is exponential in the ratio between the number of users and the system processing gain, thus providing huge savings with respect to the general case wherein the optimal receiver has a complexity exponential in the number of users. While initially considering a simple frequencyflat synchronous CDMA system, the obtained results are then extended to more general scenarios, such as asynchronous CDMA systems, multipath CDMA channels, and multiuser multiantenna systems. Finally, the issue of non-cooperative power minimization and choice of the spreading code subject to a QoS constraints is also considered, and comparisons with the corresponding cooperative solution are also discussed. Numerical results corroborate the validity of the theoretical analysis, and show that the use of non-linear interference cancellation coupled with waveform adaptation brings remarkable performance gains with respect to linear multiuser receivers.

The issue of noncooperative transceiver optimization in the uplink of a multiuser wireless code division multiple access data network with widely linear detection at the receiver is considered. While previous work in this area has focused on a simple real signal model, in this paper, a baseband complex representation of the data is used so as to properly take into account the I and Q components of the received signal. For the case in which the received signal is improper, a widely linear reception structure, processing separately the data and their complex conjugates, is considered. Several noncooperative resource allocation games are considered for this new scenario, and the performance gains granted by the use of widely linear detection are assessed through theoretical analysis. Numerical results confirm the validity of the theoretical findings and show that exploiting the improper nature of the data in noncooperative resource allocation brings remarkable performance improvements in multiuser wireless systems.

The problems of detecting the presence of a new user and of estimating the delays of its multipath replicas in a direct-sequence/code-division-multiple-access (DS/CDMA) system are investigated. Despite previous works, we consider a doubly-dispersive fading channel model and we propose a new code-aided detection algorithm which relies on the application of a powerful statistical tool known as the method of sieves. The proposed detector is blind and bounded constant false alarm rate. As a byproduct of the detection stage, a new blind procedure to estimate the multipath channel delays of the detected user is also derived.

This paper is focused on the design and analysis of power control procedures for the uplink of multipath code-division-multiple-access (CDMA) channels based on the large system analysis (LSA). Using the tools of LSA, a new decentralized power control algorithm aimed at energy efficiency maximization and requiring very little prior information on the interference background is proposed; moreover, it is also shown that LSA can be used to predict with good accuracy the performance and operational conditions of a large network operating at the equilibrium over a multipath channel, i.e. the power, signal-to-interference-plus-noise ratio (SINR) and utility profiles across users, wherein the utility is defined as the number of bits reliably delivered to the receiver for each energy-unit used for transmission. Additionally, an LSA-based performance comparison among linear receivers is carried out in terms of achieved energy efficiency at the equilibrium. Finally, the problem of the choice of the utility-maximizing training length is also considered. Numerical results show a very satisfactory agreement of the theoretical analysis with simulation results obtained with reference to systems with finite (and not so large) numbers of users.

This paper focuses on the cross-layer issue of joint multiuser detection and resource allocation for energy efficiency in wireless code-division multiple-access (CDMA) networks. In particular, assuming that a linear multiuser detector is adopted in the uplink receiver, the situation considered is that in which each terminal is allowed to vary its transmit power, spreading code, and uplink receiver in order to maximize its own utility, which is defined as the ratio of data throughput to transmit power. Applying a game-theoretic formulation, a non-cooperative game for utility maximization is formulated, and it is proved that a unique Nash equilibrium exists, which, under certain conditions, is also Pareto-optimal. Theoretical results concerning the relationship between the problems of signal-to-interference-plus noise ratio (SINR) maximization and mean-square error (MSE) minimization are given, and, by applying the tools of large system analysis, a new distributed power control algorithm is implemented, based on very little prior information about the user of interest. The utility profile achieved by the active users in a large CDMA system is also computed, and, moreover, the centralized socially optimal solution is analyzed. Considerations concerning the extension of the proposed framework to a multi-cell scenario are also briefly detailed. Simulation results confirm that the proposed non-cooperative game largely outperforms competing alternatives, and that it exhibits negligible performance loss with respect to the socially optimal solution, and only in the case in which the number of users exceeds the processing gain. Finally, results also show an excellent agreement between the theoretical closed-form formulas based on large system analysis and the outcome of numerical experiments.

This paper considers the problem of parameter estimation and data detection in multiuser bandlimited long-code DS/CDMA systems. Centralized (i.e., multiuser) and decentralized (i.e., single-user) estimation procedures for the delay, amplitude and phase offset of the users' CDMA received signals are derived. The proposed estimation procedures may be devised as two-steps ones: indeed, first a composite channel impulse response is estimated and, then, such an estimate is further processed in order to obtain the parameter estimates. Closed-form formulas for the Cramer-Rao Lower Bound (CRLB) are derived, and the performance of the proposed estimators is numerically contrasted to that of the CRLB and of competing alternatives. The problem of multiuser detection is also considered, and indeed we report the performance of some relevant multiuser detectors built upon the estimates provided by the proposed estimation algorithms. We are thus able to assess the impact that the proposed estimation algorithms have on the bit error rate performance of the system.

Power control is a fundamental task accomplished in any wireless cellular network; its aim is to set the transmit power of any mobile terminal, so that each user is able to achieve its own target SINR. While conventional power control algorithms require knowledge of a number of parameters of the signal of interest and of the multiaccess interference, in this paper it is shown that in a large CDMA system much of this information can be dispensed with, and effective distributed power control algorithms may be implemented with very little information on the user of interest. An uplink CDMA system subject to flat fading is considered with a focus on the cases in which a linear MMSE receiver and a non-linear MMSE serial interference cancellation receiver are adopted; for the latter case new formulas are also given for the system SINR in the large system asymptote. Experimental results show an excellent agreement between the performance and the power profile of the proposed distributed algorithms and that of conventional ones that require much greater prior knowledge.

The problem of joint data detection and channel estimation for a code division multiple access system adopting aperiodic spreading codes is considered. Assuming that each transmitted data frame contains a short preamble of known symbols, a detection strategy is proposed that relies on an iterative exchange of information between the data detector and the channel estimator. This strategy, which is termed "multipass," is shown to be capable of alleviating, at the price of some attendant increase in the computational complexity (or, equivalently, in the detection delay), the performance degradation induced by the lack of prior knowledge about the channel state and the users' timing offsets. Both the mobile-to-base (uplink) and base-to-mobile (downlink) communication hauls are considered, and algorithms suited for each of these scenarios are proposed. Analytical findings and extensive computer simulations confirm that the proposed strategy achieves excellent results.

The problem of blind multiuser detection for a DS-CDMA system employing multiple transmit and receive antennae over a fading dispersive channel is considered. Relying upon a well known signal representation, we develop a new family of linear receivers adapted to account for MIMO channels. Linear receivers share the key property of substantial immunity to co-channel interference, without requiring any prior knowledge on the signals to be decoded, except for the spreading sequence. The performance assessment, conducted through semianalytical methods - whenever possible - and validated through Monte Carlo counting techniques, shows that the newly proposed receivers perform pretty close to their non-blind counterparts, which rely on prior knowledge of the spreading codes, symbol timings and channel impulse responses for all of the active users.

Recently, a new class of linear multiuser receivers for direct-sequence code-division multiple-access (CDMA) systems employing binary phase-shift keying modulation has been introduced. Unlike classical decorrelating and minimum mean-square error linear multiuser detectors, the new receivers exploit the information contained in the pseudo-autocorrelation of the observables, and are, thus, capable of achieving much better performance. We present new results on the performance analysis of this class of new receivers. In particular, with reference to a CDMA system with deterministic spreading codes, we show that the new receivers outperform the classical ones in terms of both error probability and near-far resistance. With regard, instead, to CDMA systems with random spreading, we compute the average system near-far resistance, showing that the new receivers can accommodate twice the number of users accommodated by the classical linear multiuser receivers.

In this paper the problem of joint data detection and channel estimation for the uplink of a CDMA system employing aperiodic spreading codes is considered. Assuming that each transmitted data-frame contains a short preamble of known bits, the detection strategy that is proposed here relies on an iterative exchange of information between the data detector and the channel estimator. This strategy, which is termed "multi-pass," is shown to be capable of alleviating, at the price of some attendant increased computational complexity increase, the performance degradation induced by the lack of prior knowledge on the channel state and on the users' timing offsets. Extensive computer simulations confirm that the proposed strategy achieves excellent results.

The problem of joint multiaccess interference (MAI) and intersymbol interference (ISI) suppression in DS/CDMA systems operating over fading dispersive channels is considered. A timing-free, blind and code-aided detection algorithm is proposed, i.e. the procedure requires knowledge of neither the interfering users' parameters (spreading codes, timing offsets and propagation channels), nor the timing and channel impulse response of the user of interest, but only of its spreading code. The proposed structure is a two-stage one. The first stage is aimed at suppressing the multiuser interference, while the second-stage performs channel estimation and data detection. The proposed system is shown to incur a very limited loss with respect to the non blind MMSE detector; moreover, it outperforms other previously known blind systems, and is near-far resistant. A major advantage of the new structure is that it admits an adaptive implementation with quadratic (in the processing gain) computational complexity. This adaptive algorithm, which couples a recursive-least-squares estimation of the blocking matrix and subspace tracking techniques, achieves effective steady-state performance.

The push toward more efficient and flexible use of the radio spectrum has led to the consideration of the overlay of spread-spectrum (SS) communication networks on preexisting narrow-band networks. Such systems are already in widespread and rapidly expanding use in the lightly regulated spectrum where personal networking is largely centered and they are of increasing interest in the more tightly regulated spectrum due to a dearth of spectrum for new services, the desire to incorporate multi-rate (e.g., multimedia) traffic in the same network and the survival of legacy systems. Even though SS signals are inherently robust to the effects of narrower bandwidth cochannel signals, it has been shown that the use of additional processing aimed at interference suppression can result in substantial performance improvement. Motivated by this consideration, the past quarter century has seen the development of a very large body of techniques for improving the performance of SS communications systems in the presence of narrow-band interference (NBI). Early techniques (up to late 1980s) have been reviewed in the survey by Milstein (1988). Since that time, more sophisticated strategies have been developed, making use of advances from the fields of beamforming, multiuser detection (MUD), and adaptive filtering. Also, the focus of interest has shifted from techniques aimed primarily at the suppression of NBI from single-user SS systems to systems in which the SS signaling is being used to implement a code-division multiple-access (CDMA) protocol. This paper provides a tutorial overview of the progress made in this area over the past 15 years. The focus of the paper is on direct-sequence CDMA (DS/CDMA) systems and on the so-called "code-aided" techniques for NBI suppression, a term coined to indicate those strategies in which knowledge of the spreading code of a SS signal of interest is explicitly exploited in suppressing NBI. Particular attention is devoted to the case in which the CDMA signals are subject to frequency-selective fading and to the issue of blind adaptive MUD in the presence of external NBI. In particular with regard to the former issue, the effects and implications of channel-state information on system design and performance are discussed. With regard to the latter issue, it is observed that the external NBI may introduce the need for a periodically time-varying detection rule, which has significant implications in the design of blind adaptive MUD algorithms for overlaid DS/CDMA systems. The performance of the techniques discussed is compared through analysis and simulation, as well as through considerations of their relative computational complexity and required prior information. Finally, the paper is concluded by a discussion of several challenging open problems in this area.

It has been shown that in a direct-sequence/code-division multiple-access (DS/CDMA) system employing binary phase-shift keying (BPSK) modulation the baseband equivalent of the CDMA multiplex is, under very mild assumptions, an improper complex random process, i.e., it has a nonzero pseudoautocorrelation function. The problem of linear multiuser detection for asynchronous DS/CDMA systems with improper multiaccess interference (MAI) is considered. A new mean-output-energy (MOE) cost function is introduced, whose constrained minimization leads to two new linear multiuser detectors, exploiting the information contained in the pseudoautocorrelation of the observables, and which generalize the classical decorrelating and minimum mean-square error (MMSE) receivers. The problem of blind adaptive receiver implementation based on subspace tracking is also tackled. Finally, the superiority of the new detectors with respect to the classical linear detection structures present in the literature is demonstrated through both theoretical considerations and computer simulations.

In this paper, the authors consider an asynchronous direct-sequence code division multiple access (DS/CDMA) system wherein users are allowed to transmit their symbols at one out of two available data rates. Three possible access schemes are considered, namely, the variable spreading length (VSL), the variable chip rate (VCR), and the variable chip rate with frequency shift (VCRFS) formats. Their performance is compared for the case that a linear one-shot multiuser receiver is employed. It is also shown that detection of the users transmitting at the higher rate requires a periodically time-varying processing of the observables. Moreover, the problem of blind adaptive receiver implementation is studied, and a cyclic blind recursive-least-squares (RLS) algorithm is provided which is capable of converging to the periodically time-varying high-rate users detection structure. Numerical results show that the proposed receivers are near-far resistant, and that the VCRFS access technique achieves the best performance. Finally as to the adaptive blind receiver implementation, computer simulations have revealed that the cyclic RLS algorithm for blind adaptive high-rate users demodulation outperforms the conventional RLS algorithm in most cases of primary importance.

The problems of channel estimation and multiuser detection for direct sequence code division multiple access (DS/CDMA) systems employing long spreading codes are considered. With regard to channel estimation, several procedures are proposed based on the least-squares approach, relying on the transmission of known training symbols but not requiring any timing synchronization. In particular, algorithms suited for the forward and reverse links of a single-rate DS/CDMA cellular system are developed, and the case of a multirate/multicode system, wherein high-rate users are split into multiple virtual low-rate users, is also considered. All of the proposed procedures are recursively implementable with a computational complexity that is quadratic in the processing gain, with regard to the issue of multiuser detection, an adaptive serial interference cancellation (SIC) receiver is considered, where the adaptivity stems from the fact that it is built upon the channel estimates provided by the estimation algorithm. Simulation results show that coupling the proposed estimation algorithms with a SIC receiver may yield, with a much lower computational complexity, performance levels close to those of the ideal linear minimum mean square error (MMSE) receiver, which assumes perfect knowledge of the channels for all of the users and which (in a long-code scenario) has a computational complexity per symbol interval proportional to the third power of the processing gain.

In this work, the problem of joint suppression of multiple-access and narrow-band interference (NBI) for an asynchronous direct-sequence code-division multiple-access (CDMA) system operating on a frequency-selective fading channel is addressed. The receiver structure we consider can be deemed as a two-stage one: the first stage consists of a bank of minimum mean-square-error (MMSE) filters, each keyed to a given replica of the useful signal, and aimed at suppressing the overall interference; the second stage, assuming knowledge of the fading channel coefficients realizations, combines the MMSE filters outputs according to a maximal-ratio combining rule. Due to the presence of the NBI, the resulting structure is in general time-varying, and becomes periodically time-varying if the NBI bit-rate has a rational ratio to that of the CDMA system. Moreover, enlarging the observation window beyond the signaling interval and oversampling the signal space may yield a noticeable performance improvement. For the relevant case that the said ratio is rational, a new cyclic blind recursive least squares (RLS)-based algorithm is introduced, capable of tracking the periodically time-varying receiver structure, and allowing adaptive interference cancellation with a moderate complexity increase. We also come up with a closed-form expression for the conditional bit-error rate (BER), which is useful both to evaluate semi-analytical methods to assess the unconditional BER and to derive bounds on the system near-far resistance. The results indicate that the receiver achieves very satisfactory performance in comparison to previously known structures. Computer simulations also demonstrate that the cyclic blind RLS algorithm exhibits quite fast convergence dynamics.

We deal with interference suppression in asynchronous direct-sequence code-division multiple-access (CDMA) systems employing binary phase-shift keying modulation. Such an interference may arise from other users of the network, from external low-rate systems, as well as from a CDMA network coexisting with the primary network to form a dual-rate network. We derive, for all of these cases, a new family of minimum mean-square-error detectors, which differ from their conventional counterparts in that they minimize a modified cost function. Since the resulting structure is not implementable with acceptable complexity, we also propose some suboptimum systems. The statistical analysis reveals that both the optimum and the suboptimum receivers are near-far resistant, not only with respect to the other users, but also with respect to the external interference. We also present a blind and a recursive least squares-based, decision-directed implementation of the receivers wherein only the signature and the timing of the user to be decoded and the signaling time and the frequency offset of the external interferer are assumed known. Finally, computer simulations show that the proposed adaptive algorithm outperforms the classical decision-directed RLS algorithm.

A timing-free blind multiuser detection technique is proposed for differentially encoded direct-sequence/code division multiple access (DS/CDMA) networks. Unlike previously derived blind multiuser detectors, the proposed algorithm does not rely on any information beyond the spreading code of the desired user, namely neither the complex amplitude nor the symbol timing of the signal of interest is assumed to be known to the receiver. The proposed detector structure is immune to cochannel interferers with arbitrarily large powers, and, as computer simulation results show, compares favorably with competing alternatives. Moreover, the proposed detector achieves performance quite close to that of the ideal minimum mean square error (MMSE) multiuser receiver, which requires knowledge of the spreading codes, timing offsets, and received energies for the signals of all active users.

In this work we consider the problem of M-ary signal detection over a single-input-multiple-output channel affected by time- and/or frequency-dispersive Rayleigh-distributed fading and in the presence of non-Gaussian noise, modeled as a spherically invariant random process (SIRP). We derive the optimum (minimum error-probability) detector, and show that its structure is canonical, i.e. it is independent of the actual noise statistics. Finally, the performance analysis of the receiver highlights that the adoption of diversity represents a suitable means to restore performance also in the presence of dispersive fading and impulsive non-Gaussian noise.

In this paper, we consider the problem of channel estimation in a multirate/multicode DS/CDMA system employing long spreading codes. The problem is of interest since the most part of the previously derived adaptive techniques for channel estimation relies on the short-code assumption and cannot be adopted in future wireless networks. The proposed procedure requires the transmission of known training bits and is based on a least-squares approach. It does not require timing synchronization, has a computational complexity which is quadratic in the processing gain, and may be adopted both in the uplink and in the downlink. Simulation results confirm that it may achieve satisfactory performance levels, as well as that in a multicode scenario the high-rate users propagation channels may be acquired faster than low-rate users ones.

In this work, we propose an MMSE multiuser detector for asynchronous DS/CDMA systems operating over frequency-selective fading channels. It is shown that computation of a conditional MMSE estimate of the bit to be decoded may be carried out with a computational burden linear in the processing gain N. We also give a closed-form formula for the error probability and the near-far resistance of the proposed detector, and curves of such performance measures, showing that the new receiver is near-far resistant and outperforms the previously derived decorrelating detector for frequency-selective fading channels.

In this work we introduce a new multiuser detector for interference suppression in DS/CDMA systems, based on the minimization of a modified MMSE-like cost function, and which may possibly entail an independent processing of the data and of their complex conjugate. The proposed detection structure is then specialized to the relevant case that the interference consists of a secondary CDMA network whose bit-rate is slower than that of the primary network: interestingly, interference suppression entails a periodically time-varying (PTV) detection rule. We also address the issue of adaptive detection, and present a new RLS algorithm suited for the tracking of the PTV solution. As to the performance assessment, we give a closed-form formula for the system error probability, while numerical results show that the new detection structure, and its adaptive version, outperform previously known receivers.

In this paper, we handle the problem of joint suppression of multiple-access interference (MAI) and narrowband interference (NBI) in fading, dispersive channels. The detectors we consider are linear, one-shot structures, which allow for possible window enlargement and signal-space oversampling to improve performance. We focus on both zero-forcing and minimum-mean square-error design strategies, showing that the presence of NBI generally requires a time-varying processing of the observables, no matter what the optimization criterion. A thorough performance assessment of the proposed detectors is also presented, either through analytical formulas or through computer simulations. We finally deal with the problem of blind suppression of both MAI and NBI, introducing batch-estimation procedures to be implemented offline, which require very little and sometimes no prior knowledge as to the interference structure.

The authors consider an asynchronous DS/CDMA system wherein users are allowed to transmit their symbols at one out of two available data-rates. Besides the variable spreading length (VSL) access technique, described in the literature, two other types of access methods are considered, namely the variable chip-rate (VCR) and the variable chip-rate frequency shifted (VCRFS), wherein users with different data-rates are accommodated by means of signature waveforms with different chip-rates. The authors derive, through an unified approach valid for each of the above access techniques, an MMSE-based multiuser detector, and show that detection of the users transmitting at the higher data-rate requires a periodically time varying processing. As to the performance analysis, results show that the VCRFS access technique presents the best performance, as well as that enlarging the processing window length and sampling at rates larger than the chip-rate yield beneficial effects on the system performance.

The authors present a new MMSE-based multiuser detector for asynchronous DS/CDMA communications over frequency-selective fading channels. The proposed detector is able to simultaneously suppress both the multiaccess interference and a narrowband interference with known second-order statistics. It is shown that narrowband interference suppression requires in general a time-varying processing of the observables. As to the performance assessment, we give formulas for the system bit error rate for Rayleigh fading and we show that the detector is near-far resistant. Results demonstrate that the proposed system is effective in combating the overall interference. Moreover, enlarging the processing window and oversampling the signal space yield a remarkable improvement in the system performance, especially for large number of users.

The paper discusses the problem of detecting one out of M Gaussian correlated signals in impulsive noise, modeled as a compound-Gaussian, possibly correlated process. We first show that, for uncorrelated noise, the detection problem admits one and the same optimum-in the sense of attaining minimum error probability-solution, independent of the noise statistics: the optimum detector, in fact, amounts to an estimation block, aimed at measuring the short-time noise power spectral density (PSD), whose output is fed to a bank of estimators-correlators, each keyed to one of the M admissible waveforms and to the estimated noise PSD. We also give suggestions for realizing a suboptimum receiver, with reduced complexity, which again is canonical in its structure. As for the performance analysis, we focus on binary frequency-shift keying (BFSK) signaling: we provide numerical results for two particular channel correlations and for Cauchy-distributed noise. These results indicate that, like for the general Gauss-Gauss case, the performance depends on the energy contrast, as well as on the "time-bandwidth" product of the useful signal. Moreover, noise spikiness seems to negatively affect the performance, in the sense that heavier and heavier high-amplitude tails of the noise marginal distribution give rise to higher and higher error probabilities for fixed energy contrast and time-bandwidth signal product.