This work addresses the problem of precoding optimization for a multi-user and multi-target ISAC system from a communication-centric perspective. Specifically, the paper considers a scenario where a multiple-antenna base station (BS) serves several single-antenna communication user equipments (UE) while also steering beams for target detection. The objective is to maximize the signal-to-interference plus noise ratio (SINR) subject to power and radio-sensing constraints. The problem is challenging due to its non-convexity. To address this, we propose a sub-optimal solution by zero-forcing (ZF) multi-user interference. A closed-form solution is derived, which efficiently computes the precoder with low computational cost. Simulation results validate the effectiveness of our proposed precoder design which outperforms previous precoder design methods for ISAC.

Ultra-dense networks (UDNs) have been proposed to achieve high data rates and energy efficiency, but their performance is limited by the increase of inter-user interference. To overcome this problem, interference alignment (IA) algorithms have been widely researched. However, reported IA techniques neglect the nonlinear distortion (NLD) induced by power amplifiers. Thus, their performance is severely degraded in power-efficient transmissions operating close to the saturation point. Distortion-aware precoding techniques have been studied to reduce NLD in single transmitter scenarios either single-user or multi-user. Nevertheless, its extension to UDNs with multiple transmitters and users is not straightforward. In this work, a novel IA algorithm, named NLD-IA, is proposed to alternatively design the precoding and combining vectors to reduce the interference and NLD by maximizing the sum-rate through the signal-to-interference-plus-noise ratio (SINR). Precoding vectors are obtained via a non-convex optimization problem that models the NLD correlation. An analytical solution based on the Newton method over the complex field is developed to solve this problem with low computational complexity. Simulation results show that the proposed NLD-IA significantly reduces interference and NLD outperforming previous IA algorithms. The proposed method is an attractive solution for UDNs commonly found in the context of Internet of Things applications.

User-centric cell-free massive multiple-input multiple-output (UC CF mMIMO) is a key technology for 6G. In UC CF mMIMO each user equipment (UE) is jointly served by a small subset of a large set of cooperating access points (APs). The APs are connected through the fronthaul to a central unit (CU) for joint processing. The key to efficiency is the UE-APs association procedure together with the APs/CU cooperative signal decoding. The first is essential for reducing fronthaul signaling and the latter for removing interference. In this work, we design an algorithm to jointly perform UE-APs association and decoding. The aim is to maximize the mean squared error (MSE) between transmitted and CU decoded data, considering the fronthaul data rate limitations. In our approach, the two aspects are jointly considered, allowing improved performance while keeping the amount of fronthaul signaling low. Furthermore, the proposed method has low-complexity, requiring only the knowledge of a signal quality indicator of each UE at the CU to perform joint decoding and UE-APs association. The numerical results have shown that there is a tradeoff between performance and fronthaul requirements, where the proposed method with fewer APs may achieve the same bit error rate (BER) performance in comparison to conventional CF systems where each AP serves all UEs.

In this paper, we propose a distributed hybrid analog-digital multi-user equalizer combined with an analog precoder for a wideband millimeter-wave (mmWave) cell-free massive multiple-input multiple-output (CF mMIMO) systems. A low complexity angle of departure (AoD) analog-based precoder is applied at the transmitter, while a distributed architecture is considered at the receiver side, i.e., the hybrid analog/digital beamforming processing is executed at the access points (APs), while the final data fusion is performed at the central processing unit (CPU) combiner. Herein, the average mean square error (MSE) between the transmitted and received signals is used as a metric to optimize the APs hybrid equalizer. Then, the noise variance is included for optimal data combination. The results show that the performance of the proposed hybrid scheme with the AoD analog precoder achieves a close result to the fully digital counterpart and fully centralized approach.

This paper considers a cooperative bistatic scenario for integrated sensing and communication (ISAC) paradigm, where transmitter and receiver base stations (BS) are connected through the front-haul to a central unit (CU), enabling cooperation. A multiple-input multiple-output (MIMO) configuration is considered in combination with orthogonal frequency division multiplexing (OFDM). The communication and radio-sensing functions are performed in orthogonal sets of sub-carriers, where the sub-carriers allocated to radio-sensing are distributed among antennas in an interleaved way. The interleaved frame structure is exploited in the design of a new parameter estimation method. The proposed method is a two-stage algorithm to estimate the delay/Doppler shift and angular position of objects (paths) in the channel. First, the multiple signal classification (MUSIC) algorithm estimates the angle-of-arrival (AoA) of the paths. Then, the delay, Doppler shift and angle-of-departure (AoD) are jointly estimated for each AoA combining an extended search over the AoD domain and a two-dimensional periodogram. The simulations show that the delay, Doppler shift and AoA are estimated correctly, while the estimation of the AoD may report error, although it can be compensated.

The current cellular systems are conventional cell-centric based architectures, and thus the inter-cell interference greatly affects the quality of service (QoS) of users located at the border of those service areas. For that reason, future wireless systems will rely on a cell-less deployment by using an alternative promising network infrastructure known as cell-free (CF) technology. Here, in contrast to the current networks, there are no concepts of cells or cell boundaries since it is a disruptive paradigm where a large number of geographically distributed access points (APs) simultaneously and jointly serve a much smaller number of user terminals (UTs) to fulfill the exponentially increasing number of users. Therefore, this paper aims to contribute on this field and considers the design of hybrid analog/digital multi-user equalizer for broadband millimeter wave (mmWave) CF massive multiple-input multiple-output (mMIMO) systems, using a distributed beamforming approach (processing is distributed by APs and central unit (CU)) to reduce the fronthaul requirements. First, only a low complexity analog precoder is applied to the transmitter, while a joint design of APs hybrid equalizer and CU combiner are considered by minimizing the average mean square error (MSE) between the transmitted and CU estimated signals. To achieve this joint design, a cyclic minimization method is used to iterate between APs hybrid equalizer and CU combiner, where the information is exchanged between APs and CU based on a set of error variances to improve detection performance. The simulation results show that the proposed precoder and the hybrid linear equalizer can achieve performance results very close to those of the fully digital system. Moreover, just two iterations of the proposed algorithm are already enough to match the full centralized approach performance.

The use of efficient high-power amplifiers (HPAs) is critical for future millimeter-wave (mmWave) systems. HPAs can become highly nonlinear when operated near saturation, distorting the transmission signal. Therefore, the design of efficient solutions to mitigate nonlinear distortion (NLD) is of paramount importance. This article proposes a hybrid multiuser equalizer for the uplink of wideband mmWave massive MIMO systems. The equalizer is designed to mitigate both the multiuser interference (MUI) and inter-symbol interference (ISI), introduced by the multiple access channel, and the NLD, introduced by the user terminals HPA. The digital part of the hybrid equalizer is iterative and computed on a per subcarrier basis, to minimize the mean squared error between the transmitted and detected data. In the iterative processing, a feedback loop estimates and removes the distortion. The analog part is frequency-flat and its design assumes that the digital part efficiently removes the MUI, ISI and NLD. Performance results show a huge gain of the proposed hybrid nonlinear equalizer, when compared with linear ones. The nonlinear effects are almost completely removed, without significant error propagation effects, allowing a more efficient operation of the HPAs.

In this paper we consider a multipath channel subject to variations in time due to the presence of a Doppler drift which imposes a phase rotation on the original channel impulse response. Accordingly, a decision-directed state-space approach based on the extended Kalman filter (EKF) is proposed to track the channel variation. This approach is particularly efficient since we are able to reduce the number of training symbols used for channel tracking to be as few as two times the number of transmitters. These training symbols are required to initialize the EKF. Furthermore, using a decision-directed approach we are able to provide the EKF with state-observations without additional training symbols. Our approach is specially designed to work with hybrid analog/digital multiple-input multiple-output (MIMO) architectures.

In this paper we consider a multi-input multi-output (MIMO) channel subject to time variations. These channel variations are due to the presence of a Doppler term which imposes a phase rotation on the original channel impulse response (CIR). On one hand, modern equalization schemes require the knowledge of the CIR or, equivalently, the channel frequency response (CFR). On the other hand, channel estimation procedures consume significant resources, particularly when transmitting training sequences. Therefore, we propose the use of a statespace approach, namely the extended Kalman filter (EKF), to interpolate the channel estimates obtained during the training stage onto the data transmission stage. Our approach is validated considering single-carrier frequency-domain equalization (SCFDE) transmissions.

In this paper we consider a multipath channel subject to variations in time due to the presence of a Doppler term which imposes a phase rotation on the original channel impulse response. Accordingly, a decision-directed state-space approach based on the extended Kalman filter (EKF) is proposed to track the channel variation. This approach is particularly efficient since we are able to reduce the number of pilot symbols used for channel tracking by using a decision-directed approach. In fact, only two training symbols are required to initialize the EKF. Our approach is validated considering orthogonal frequency-division multiplexing (OFDM) schemes.

The secrecy challenge of protecting a power domain non-orthogonal multiple access (NOMA) system is associated with the intrinsic superposition structure of the transmitted information. Because of this superposition operation, the interference generated by the other user's information must be first decoded by the receiver in order to allow the intended information to be acquired. Therefore, a robust secrecy solution for this type of channel access techniques must consider not only the existence of attacks coming from undetectable passive eavesdroppers located outside of the network, but also attacks carried out by eavesdroppers registered as legitimate users inside the system. In this work, a cooperative jamming technique is combined with a secure channel training solution in order to protect a two user power domain NOMA system against eavesdropping attacks coming simultaneously from inside and outside of the network. The proposed secrecy solution is evaluated numerically and the evaluation demonstrates that weak secrecy is achieved against the inside and outside eavesdroppers.

This paper considers a hybrid two-step space-frequency receiver structure for multiuser uplink millimeter-wave (mmWave) massive MIMO based systems. We adopt constant envelope OFDM (CE-OFDM) since it is a promising modulation technique for future systems, which allows very efficient power amplification. We consider low-complexity user terminals employing a single RF chain and using an analog precoding based only on the average angles of departure of the channel. At the base station a non-linear multi-user equalizer, based on the iterative block decision feedback equalization (IB-DFE) principle, and using a hybrid analog-digital structure, is designed to efficiently remove the inter-user and inter-carrier interferences. This equalizer is designed to minimize the sum of the mean square errors of all subcarriers. Numerical results have shown that the proposed scheme outperforms the linear equalizers. Moreover, performance is already close to the full digital counterpart after only a few iterations.

In this paper we consider the use of a single- carrier with frequency-domain equalization (SC-FDE) scheme for the uplink in a cellular radio system. To cope with the doubly-selective nature of the channel we propose a receiver structure for the joint channel equalization and tracking. We use a low-complexity iterative frequency-domain equalizer based on the iterative block decision-feedback equalization (IB-DFE) concept for the channel equalization and an extended Kalman filter (EKF) for the channel tracking procedure. The tracking procedure works by, first, observing the channel through channel estimation based on training blocks and, then, by predicting the channel during data transmission. Alternatively, decision-directed channel estimation can be used also, resulting in an improved performance.

Accommodating the coverage and capacity requirements of wireless cellular communication systems evolved contemporary cellular architectures to comprise two tiers: A macro-cell overlay coverage tier encompassing a small-cell tier offloading user traffic in high traffic demand areas. While two-tier cellular architectures can effectively meet coverage and capacity requirements when operating on independent frequency bands, radio spectrum scarcity entails sharing spectrum by both tiers which substantially complicates interference management for such architectures. In order to address uplink interference in two-tier cellular architectures, this paper considers the joint application of dual space-frequency block codes (SFBC) and signal alignment (SA) enabled physical network coding (PNC). When compared to designs adopting interference alignment (IA) or PNC, the proposed joint dual-SFBC with SA-PNC design substantially reduces interference and enables connecting a larger number of users. Numerical results also verify that the proposed method outperforms the SA-PNC static method without any information exchange requirement between the two tiers while achieving close to optimal performance for macro-cells.

In this paper, we consider the application of signal alignment (SA) enabled physical network coding (PNC) for the uplink of heterogeneous networks. The joint design of SA and PNC has the potential of fully exploiting the precoding space and can achieve better spatial diversity of a multi-input multi-output (MIMO) networks that provides higher system degrees of freedom (DoF), than the case where only PNC or interference alignment (IA) is employed individually. We consider a scenario where a set of small-cells coexist under the same spectrum with the macro- cell. For this scenario, we design new joint SA and PNC based schemes under different levels of inter-tier coordination. We compare the proposed joint SA-PNC schemes with the IA based techniques, recently designed for uplink heterogeneous systems. Simulation results show that the proposed SA-PNC is quite efficient to remove the inter- tier/system interference while allowing to increase the overall data rate, by serving more users, as compared with the IA based methods.

The aim of this manuscript is to propose a new hybrid nonlinear block space-time receiver structure for millimeter wave (mmW) systems, to efficiently separate the spatial streams. We consider a fully connected analog-digital architecture. We assume that both the transmitter and the receiver are equipped with a large antenna array and the number of radio frequency (RF) chains is lower than the number of antennas. The analog and digital parts of the equalizer are jointly optimized using as a metric the mean square error (MSE) between the transmitted data vector and its estimate after the digital equalizer. The specificities of the analog domain impose several constraints in the joint optimization. To efficiently deal with the constraints the analog part is selected from a dic-tionary based on the array response vectors. The performance results have shown that the performance of our hybrid nonlinear space-time equalizer is close to the fully digital counterpart after only a few iterations. Moreover, it clearly outperforms the linear receivers recently proposed for hybrid mmW massive MIMO architectures.

The combination of millimeter wave (mmW) with massive MIMO is a promising approach to achieve the multi Gb/s required by future wireless systems. Fully digital architectures are not feasible due to hardware limitations, and thus, the design of signal processing techniques for hybrid analog-digital architectures is of paramount importance. In this paper, we propose a new hybrid iterative block space-time receiver structure for multiuser mmW massive MIMO systems. We consider low-complexity user terminals employing analog-only random precoding and a single RF chain. At the base station, a hybrid analog-digital equalizer/detector is designed to efficiently remove the multiuser interference. The analog and digital parts of the equalizer are jointly optimized using as a metric the average bit-error-rate. The specificities of the analog domain impose several constraints in the joint optimization. To efficiently handle these constraints, the analog part is selected from a dictionary based on the array response vectors. We also propose a simple, yet an accurate semi-analytical approach for obtaining the performance of the proposed hybrid receiver structure. The results show that the performance of the hybrid iterative equalizer is close to the fully digital counterpart after only a few iterations. Moreover, it clearly outperforms the linear receivers recently considered for hybrid mmW massive MIMO architectures.

In this paper, we consider the K-user singleinput single-output interference channel with delayed channel state information at the transmitters (CSIT). Our main contribution is to show that even with delayed CSIT and distributed transmitters, the achievable degrees of freedom (DoFs) still scale with the number of users. More specifically, we propose a method that achieves K/(2√K -1) ≥ √K/2 DoF. The main idea behind the proposed method is to use interference alignment (IA) at the receiver side in conjunction with repetition coding at the transmitters. Repetition coding repeats the data R times while IA makes the interference generated by a given transmitter identical: 1) at all non-intended receivers and 2) all transmission repetitions. Therefore, one retransmission per transmitter is sufficient to cancel all the interference. This reduces significantly the overhead required for interference removal since the number of interference terms is reduced from RK(K - 1) to K.

In this paper, we consider the downlink communication of an arbitrary number of transmitters over broadcast interference channels. In order to suppress interference, we investigate a network-level linear precoding scheme dubbed precoding reuse. Such a technique is leveraged on the interference alignment (IA) principle, where the undesired signals overlap in a reduced-dimension subspace at the receivers. Precoding reuse relies on two cascaded precoders to suppress intra- and inter-cell interference and requires feedback only within a cell. We designed precoding reuse schemes for which interference suppression can be attained in a coordinated or uncoordinated fashion over a fixed number of quasi-static channel uses. We provide expressions for the parametrization of the precoders and investigate the advantages, limitations, suitable scenarios, and applications of the proposed IA scheme. Finally, we pointed out the open problems, where the proposed IA scheme and parametrization can be implemented with little effort, demanding minimum changes to an existing cellular system supporting multi-user MIMO.

The exploration of the physical layer characteristics of the wireless channel is currently the object of intensive research in order to develop advanced secrecy schemes that can protect information against eavesdropping attacks. Following this line of work, in this manuscript we consider a massive MIMO system and jointly design the channel precoder and security scheme. By doing that we ensure that the precoding operation does not reduce the degree of secrecy provided by the security scheme. The fundamental working principle of the proposed technique is to apply selective random rotations in the transmitted signal at the antenna level in order to achieve a compromise between legitimate and eavesdropper channel capacities. These rotations use the phase of the reciprocal wireless channel as a common random source between the transmitter and the intended receiver. To assess the security performance, the proposed joint scheme is compared with a recently proposed approach for massive MIMO systems. The results show that, with the proposed joint design, the number of antenna elements does not influence the eavesdropper channel capacity, which is proved to be equal to zero, in contrast to previous approaches.

Millimeter waves and massive MIMO are a promising combination to achieve the multi-Gb/s required by future 5G wireless systems. However, fully digital architectures are not feasible due to hardware limitations, which means that there is a need to design signal processing techniques for hybrid analog-digital architectures. In this manuscript, we propose a hybrid iterative block multiuser equalizer for subconnected millimeter wave massive MIMO systems. The low complexity user-terminals employ pure-analog random precoders, each with a single RF chain. For the base station, a subconnected hybrid analog-digital equalizer is designed to remove multiuser interference. The hybrid equalizer is optimized using the average bit-error-rate as a metric. Due to the coupling between the RF chains in the optimization problem, the computation of the optimal solutions is too complex. To address this problem, we compute the analog part of the equalizer sequentially over the RF chains using a dictionary built from the array response vectors. The proposed subconnected hybrid iterative multiuser equalizer is compared with a recently proposed fully connected approach. The results show that the performance of the proposed scheme is close to the fully connected hybrid approach counterpart after just a few iterations.

In this paper we design a new iterative space-frequency equalizer, based on iterative block decision feedback equalization (IB-DFE) principle, for multiplexing MIMO CE-OFDM millimeter wave (mmW) based systems. Linear frequency domain equalizers are not the most efficient to separate the spatial streams due to inter-carrier interference. Therefore, we design a non-linear equalizer that takes into account both inter-block and residual inter-carrier interferences by efficiently exploit the high space-frequency diversity order inherent to these systems. The feedforward and feedback matrices for the proposed iterative space-frequency equalizer are obtained by minimizing the overall mean square error (MSE) of all data streams at each subcarrier. Our iterative scheme significantly outperforms the linear frequency domain equalizers, recently considered for CE-OFDM, with only a few iterations.

In this paper, we consider a K-user M × N MIMO interference channel, with outdated channel state information at the transmitters (CSIT). Based on the technique introduced by Cadambe and Jafar, for the IC with perfect and up-to-date CSIT, we propose and analyze a scheme that guarantees interference alignment with outdated CSIT. The interference is aligned by the transmitters, and removed by the receivers using zero-forcing by Cadambe and Jafar. However, this is not feasible for the IC with outdated CSIT, since there is no up-to-date CSIT to compute the interference alignment precoders. To overcome this limitation, we propose that the interference should be aligned by the receivers instead. With this approach, the interference caused by a transmitter spans the same subspace at all receivers, i.e., the interference at receiver k ≠ m may be obtained through a linear map from the interference at receiver m. Therefore, one interference retransmission per transmitter is enough to cancel all the interference. This reduces the overhead required for interference removal from K(K -1) to K interference terms.

In this manuscript, we consider the uplink of a single carrier frequency division multiple access (SC-FDMA) based system, where a set of small-cells coexist with a macro-cell using the same spectrum. To deal with both the inter-carrier interference (ICI) and inter-system interference, we combine interference alignment (IA) precoding at the small-cell transmitters with iterative decision feedback equalization at the macro-receiver. The transmitter and receiver design is performed jointly by considering both full-coordination and limited inter-system information exchange between macro- and small-cells. At the small cells side, we assume that the access points are connected through a limited capacity backhaul network to a central unit, where the separation of a quantized version of the small-cell signals is performed. For this case, the iterative feedback equalizer is designed by explicitly taking into account the impact of signal quantization. Moreover, a semi-analytical approach for the performance of the proposed schemes is provided. The results show that the proposed schemes are robust to both inter-system and inter-carrier interferences and thus are able to efficiently separate the macro- and small-cells spatial streams under limited information exchange.

Small‐cells are considered as an effective solution to increase capacity and offload traffic from, the current macro‐cell cellular system. Owing to the difficulty and costs involved in acquiring new spectrum licenses, small‐cells are expected to coexist with their respective macro‐cells, in the same spectrum. This leads to considerable interference between the two systems. Optimum performance, at the macro‐cell, is achieved when the small‐cell terminals transmit their information over the null‐space of the macro‐cell link. However, availability, at the small‐cell terminals, of the macro‐cell channel null‐space information requires full‐cooperation and thus a high overhead of information exchange. In this study, the cognitive precoding schemes are designed under a limited inter‐system information exchange and the constraint that the performance of the macro‐cell link is kept close to the case where no small‐cell network does exist. Two techniques are considered: a two‐bit quantisation precoded and a dual space‐frequency coding precoded approach. It is demonstrated that the first achieves a performance close to the full cooperation approach recently proposed, but with very low information exchange requirements. For the second, it is show that both the systems are able to coexist without any inter‐system cooperation and with a performance close to the non‐coexistence scenario.

To increase capacity and offload traffic from the current macro-cell cellular system, operators are considering the deployment of small cells. It is expected that both the small and macro-cells will coexist in the same spectrum, resulting in unsustainable levels of interference. Interference alignment is considered as an effective method to deal with such interference. By using interference alignment, the small cells align their transmission along a common direction to allow the macro-cell receiver to completely remove it. It is clear that, if the two systems have no limitations on the information that may be exchanged between them to perform the signal design, then the performance may be improved in comparison to the case of no or partial cooperation. However, this full-cooperation strategy requires a high-rate connection between the macro and small cells, which may not be available. To overcome this problem, we consider that the alignment direction is selected from a finite set, known to both macro- and small-cell terminals. We provide sufficient conditions for this set that guarantee full diversity, at the macro-cell, and propose an efficient method to optimize the set elements. Results show that an alignment set with a description length of 1 bit is enough to achieve the same diversity as in the case where an infinite amount of information is exchanged between both systems. The proposed set optimization method achieves better performance than random vector quantization and similar performance to Grassmannian quantization.

To increase capacity and offload traffic from the current macro cell cellular system, small cells have been deployed extensively. In the current deployments small cells coexist with their respective macro cells in the same spectrum, due to the difficulty and costs involved in acquiring new spectrum licenses. This leads to considerable interference between the two systems. In this context, we propose an underlay cognitive interference alignment technique to remove the interference from the small cell to the macro cell system. In the proposed scheme the small cells sense the unused resources in the space dimension of the macro cell, i.e. its null space, and precode their signals such that they lie in the sensed null space. We demonstrate that only the sign of the null space components is necessary to obtain close to full null space information performance. This results in less overhead in the sensing process making the system more efficient and practically feasible.

This paper focus on the lossy compression of a binary symmetric source. We propose a new algorithm for binary quantization over low density generator matrix (LDGM) codes. The proposed algorithm is a modified version of the belief propagation (BP) algorithm used in the channel coding framework and has linear complexity in the code block length. We also provide a common framework under which the proposed algorithm and some previously proposed algorithms fit. Simulation results show that our scheme achieves close to state-of-the-art performance with reduced complexity.

For a distributed multiple input single output (DMISO) system a terminal can be connected to all system antennas, but this leads, obviously, to a high processing capacity requirement, which is not practical. Since capacity increases only slightly with the terminal connection to more antennas, it is important to evaluate the number of antennas that a terminal must be connected to. Thus in this paper we study the ergodic capacity, for the single-user case, and the respective capacity increase by the user connection to K new antennas, over a Rayleigh flat fading channel. For each case we provide an exact closed-form expression and simple to compute upper/lower bounds. Results show that symmetry in the antenna configuration is good since maintains the capacity increase curve approximately flat. They also show that the maximum capacity increase by the connection to K new antennas is obtained when we have all mean SNRpsilas equal, which happens when all antennas are co-located, and not distributed.