In this paper, we design a 5 G -compliant semipersistent scheduling algorithm that guarantees determinism (i.e., bounded delay and zero jitter) over the wireless link for delayconstrained traffic. This is especially important for industrial remote control applications handling time-sensitive traffic. To this end, we adapt the window reservation mechanism for wired networks introduced in IEEE 802.1Qbv to also ensure determinism over 5G wireless links. Based on the statistical characterization of the radio channel, we develop a rigorous method to determine the number of time-frequency resources that must be reserved in each 5 G subframe to accommodate all time-sensitive traffic traversing the wireless link. Numerical simulations are conducted in representative industrial scenarios, showing that neighboring base stations have to coordinate their transmissions to avoid interference and mitigate channel fading. Numerical results demonstrate that window design for timesensitive traffic benefits from coordination in two key ways: by extending coverage and significantly increasing the number of time-critical flows that a 5G network can support in industrial deployments.

This paper presents a novel radio frame design for wireless links that allows efficient scheduling of multiple time-sensitive flows with bounded delay and arbitrarily small packet jitter requirements. The proposed design is compatible with the IEEE 802.1 standards for Time Sensitive Networks (TSN) and permits the efficient integration of wireless links into newly arrived wired TSN infrastructure. With this aim, we have reformulated the window reservation mechanism introduced in standard 802.1Qbv to deal with the variable transmission rate of wireless links. The new radio frame is organized in a sequence of partially-overlapped windows. If the intended flow does not use its window completely, the unconsumed time can be scheduled to other flows in overlapped windows. The benefits of this approach are evaluated numerically in an illustrative industrial scenario showing substantial gain in terms of both reduced control cycle (flows’ periodicity) and enhanced transmission throughput (number of admitted flows).

In this paper, we consider a reconfigurable intelligent surface (RIS)-based transmitter operating in a high-frequency band that sends more symbols per channel use than the number of antennas at the receiver. For such a system, we present a comprehensive study on the design and performance of a neural network (NN)-based receiver. We evaluate the performance of the minimum mean squared error (MMSE) receiver, which is a linear receiver, the optimum maximum likelihood (ML) detector, and the NN-based receiver for recovering the transmitted symbols. The numerical simulations carried out for all the detectors considered prove that the classical far-field simplification leads to a performance underestimation in scenarios involving wide transmitters and high-frequency bands, as the one considered in this paper. Moreover, the results show that the NN-based receiver achieves a favorable trade-off between complexity and performance, outperforming the MMSE receiver while maintaining a lower complexity than the ML detector.

In this paper, we propose a reconfigurable intelligence surface (RIS)-aided location system. Through such a system, we exploit that near-field (NF) effects are still significant at long distances in mm-wave bands (i.e., up to the Fraunhofer distance) for large RISs. Specifically, we leverage the wavefront curvature, which depends on the impinging direction of arrival and the distance to the RIS, to locate emitting sources. As the location procedure cannot directly access the signals at a passive RIS, our method uses the signals reflected by the RIS that impinge on an antenna array located close to the RIS. By processing the signals the array collects, we estimate the spatial power density in a given region using a minimum variance distortionless response (MVDR) estimator. As shown in the paper, this technique can precisely estimate the positions of a set of sources within the NF region of the RIS. Even though the signals that are processed are those collected by the antenna array and not the signals at the RIS, the proposed system can provide a much higher location accuracy than a system with only the antenna array without RIS. We also extend the approach to scenarios with multiple RIS-array pairs.

Receive spatial modulation (RSM) has been proposed as an effective transmission technology for next-generation wireless communications systems because of its reduced complexity and low energy consumption at the receiver end. Compared to conventional multiple-input multiple-output (MIMO) transceivers, which require one radio-frequency (RF) chain and analog-to-digital converter (ADC) per receive antenna, RSM can be implemented with one amplitude detector per antenna and a single RF chain, with mild performance degradation in terms of spectral efficiency (SE). However, its implementation using zero-forcing precoders is inadequate in mmWave channels due to the lack of propagation scattering and, hence, rank deficiency in the channel matrix. This has been only partially solved in the past using receiver antenna selection (RAS), which requires additional receive antennas. On the other hand, using reconfigurable intelligent surfaces (RIS), which can effectively create scatter and enhance the channel matrix rank, is an affordable solution that can also cope with shadowing situations and the higher path losses associated with mmWave bands. We propose using a RIS in a single-user MIMO communication with RSM to improve the downlink transmission. This paper shows that RIS-assisted RSM communication is more than a good option in mm Wave channels in terms of bit error rate due to the multipath induced in the channel and the link budget boosting.

Within the framework of 5G, blockage effects occurring in the mmWave band are critical. Previous works describe the effects of blockages in isolated and multiple links for simple blocking objects, modeled with mathematical tools such as stochastic geometry and random shape theory. Our study uses these tools to characterize a scenario with $N$ links, including the possible correlation among them in terms of blocking for several models of blocking objects. We include numerical evaluations highlighting that assuming independence among the links' blocking elements is a too-brief simplification and does not accurately describe the real scenario. This paper also applies the formulation developed for the case of $N$ links to optimize the relay positioning in mmWave cells for coverage enhancement, that is, to minimize the communication failure probability. We also show that both link budget and blockages affect the optimum positioning of the relays as they are both essential for successful transmission.

This paper presents an estimation approach within the framework of uplink massive machine-type-communications (mMTC) that considers the energy limitations of the devices. We focus on a scenario where a group of sensors observe a set of parameters and send the measured information to a collector node (CN). The CN is responsible for estimating the original observations, which are spatially correlated and corrupted by measurement and quantization noise. Given the use of Gaussian sources, the minimum mean squared error (MSE) estimation is employed and, when considering temporal evolution, the use of Kalman filters is studied. Based on that, we propose a device selection strategy to reduce the number of active sensors and a quantization scheme with adjustable number of bits to minimize the overall payload. The set of selected sensors and quantization levels are, thus, designed to minimize the MSE. For a more realistic analysis, communication errors are also included by averaging the MSE over the error decoding probabilities. We evaluate the performance of our strategy in a practical mMTC system with synthetic and real databases. Simulation results show that the optimization of the payload and the set of active devices can reduce the power consumption without compromising the estimation accuracy.

Ultra dense networks (UDNs) allow for efficient spatial reuse of the spectrum, giving rise to substantial capacity and power gains. However, recent findings have demonstrated that the reduction of inter-site distances after a certain threshold, has a detrimental effect on the network performance. In such cases, interference mitigation strategies to counteract the effect of primarily the line of sight (LOS) interference are imperative. In this course, the present paper investigates a minimum coordination strategy among immediate neighbors. The adopted scheme realizes the interference mitigation objective, enhancing system capacity, while being implementable in practice. Building upon this scheme, the present paper provides tractable closed form expressions for the downlink (DL) ergodic capacity of a reference user under the examined coordination scheme. The analysis is performed for a scenario consisting of base stations (BSs) whose positions follow a Poisson point process of a given spatial density. The tractability and accuracy of the derived expressions renders them ideal for quantifying the performance of additional coordination strategies and for revealing trends in complex optimization problems. Thus, constituting a valuable tool for network operators, toward assessing different interference mitigation techniques and coordination schemes in UDNs.

This paper develops and evaluates precoding techniques for coordinated joint transmission in visible light communications (VLC). A multi-user multiple-input single-output (MISO) setup is adopted. Transmitters are equipped with light emitting diode (LED) arrays, while receivers incorporate a single photodetector (PD). We design zero forcing (ZF) linear precoders considering, as figure of merit, the weighted sumrate for multilevel pulse amplitude modulation (PAM) and take into account the optical power constraints. We present two approaches. First, we formulate the design as a convex optimization problem and find its exact solution. Second, by considering certain approximations, we find an alternative precoder that despite being suboptimal can be computed in an almost closed-form, achieving a good trade-off between performance and complexity. Finally, we demonstrate that the proposed approaches largely outperform the conventional pseudo-inverse precoding and single-user TDMA approaches.

This paper presents long-term resource provisioning schemes for dense multi-cell OFDMA-based networks, where multiple cells with possibly overlapping coverage areas compete for the same set of resources. The optimization is done over the long term, being independent of the specific users connected to each cell but dynamic enough to follow significant variations of the traffic load. In this sense, we focus on the average resource utilization (RU) and propose schemes to minimize the maximum RU of all cells. Firstly, we consider orthogonal resource usage among cells. Optimal closed-form expressions for the long-term resource provisioning are derived for this case. Secondly, we assume that resources can be reused at non-overlapping cells. In this case, the resource provisioning is solved in two steps: i) the number of resources required per cell is obtained by discretizing the optimal solution of a convex problem, and then ii) the specific resources to be utilized by each cell are determined by using graph coloring. In contrast to previous works, graph coloring can be applied to get an implementable solution for any condition of the cell loads. Simulation results show a significant reduction of the maximum RU, which translates into an increase of the served traffic and a reduction of the packet delay, as compared to static resource provisioning schemes.

We propose a novel stochastic radio resource allocation strategy for the uplink that achieves long-term fairness in terms of similar bitrates considering backhaul and air-interface capacity limitations. We focus on a single cell scenario based on WCDMA technology. We propose to use a maximin criteria to introduce fairness among the different users' throughputs. An stochastic approximation is implemented to obtain an online algorithm where the Lagrange multipliers are estimated at each scheduling period. Our results show that the proposed scheme achieves higher fairness among the users and, in some cases, a higher sum-rate compared with the well-known proportional fair scheduler.

We consider a system where multiple users are connected to a small cell base station enhanced with computational capabilities. Instead of doing the computation locally at the handset, the users offload the computation of full applications or pieces of code to the small cell base station. In this scenario, this paper provides a strategy to allocate the uplink, downlink, and remote computational resources. The goal is to improve the quality of experience of the users, while achieving energy savings with respect to the case in which the applications run locally at the mobile terminals. More specifically, we focus on minimizing a cost function that depends on the latencies experienced by the users and provide an algorithm to minimize the latency experienced by the worst case user, under a target energy saving constraint per user.

The degrees of freedom (DoF) of the 3-user multiple-input multiple-output (MIMO) interference channel (IC) with full channel state information and constant channel coefficients are investigated when (p,p+1) antennas are deployed at the transmitters and receivers, respectively. The point of departure of this paper is the work of Wang et al., which conjectured but did not prove the DoF for the antenna settings with p>1. Here the achievability of the DoF outer bound is formally proved using linear methods, thereby avoiding the use of the rational dimensions framework. The proposed transmission scheme exploits asymmetric complex signaling together with symbol extensions in time and space interference alignment concepts. While the paper deals with the p=2,3,\ldots,6 cases, providing the specific transmit and receive filters, there are also provided the tools needed for proving the achievability of the optimal DoF for p>6, whose DoF characterization is conjectured.

This paper proposes a decentralized algorithm for interference coordination in LTE-A networks, based on the exchange of information (pricing) at control plane level. In our approach, every user equipment (UE) report the maximum modulation and coding scheme (MCS) that can be used within several sets (sub-bands) of available resource blocks, along with a parameter (cost) that measures the MCS degradation due to the transmission from an interfering neighbor. Through the exchange of pricing messages, the higher costs are distributed to the dominant interferers; and the selection of the MCS and operational sub-band is based on the current link conditions along with the received pricing messages. We evaluate the algorithm in a cellular area covered by a macro base station (MBS) and multiple active femtocells. We also measure the degradation due to the quantization of the exchanged cost values. The results demonstrate significantly enhanced performance as compared to the non-coordinated case.

A relay station (RS)-based cellular system deployment is considered, where multiple base stations (BS) cooperate in the BS-RS in-band transmission for the downlink. With the joint optimization of the resources allocated to the wireless backhaul and to the RS-MS access, it is possible to exploit the benefits of networked-MIMO along with combating the pathloss and shadowing effects, and thus obtain significantly enhanced spectral efficiency and coverage homogeneity. The problem is shown to be convex under conventional QoS objective functions. Suboptimal low complexity solutions are also proposed and evaluated.

This work looks into the extension of the proportional fair (PF) scheduler to the multi-user case, where the source is transmitting several messages under the superposition coding (SC) strategy in a Gaussian Broadcast channel. Jointly with the weighted sum-rate (WSR) scheduling criterion, we derive guidelines for 2-user pairing, based both on SNR and user priority. We compare superposition coding access with frequency division multiple access, while time division is obtained naturally as a result of the user pairing. Results elucidate that the 2-user SC PF always improves the single-user PF in terms of average throughput and delay reduction, and we compare its performance with the 3-user SC PF. Finally, the WSR shows throughput gains similar to the 2-user SC PF for certain configuration of the scheduler.

The two-way relay channel (TWRC) describes the communication between two terminals sharing a common relay. In this work we compare different protocols for the TWRC with a half-duplex relay (forwarding and protocol I) and transmission schemes (network coding relaying with random binning and XOR precoding), when the relay works in decode-and-forward and without channel state information at the transmitters. We provide the optimal resource allocation (in terms of phase duration, data rate and power allocation) when there is an individual or sum-average power constraint over the terminals. Closed-form solutions are derived whenever it is possible, while for others cases we show that the resource allocation can be formulated as a convex problem, which means that the solution can be obtained by low-complexity interior point methods.

Automatic repeat request (ARQ) protocols deal with the situations where the selected data rate is not supported by the current channel realization. The inappropriate selection is motivated by the limited channel state information at the transmitter (CSIT). This work looks into how the ARQ protocols are applied to the half-duplex relay-assisted transmission with decode-and-forward relays by exploiting the ACK feedback channel of the terminals. Two implementations are tackled: 1) only the source or 2) source and relay manage the retransmissions under the pure-ARQ protocol. This work presents an analytical framework for the comparison of both options. The study allows the optimization of the bitrate and amount of resource allocated for the relay transmission phases.

Under limited channel state information at the transmitter the communication suffers from the outage events produced by a data rate selection not supported by the current channel realization. Automatic repeat request (ARQ) protocols are a useful tool to deal with those outage events in delay-tolerant services. This work looks into how automatic repeat request (ARQ) protocols are applied to the half-duplex relay-assisted transmission with a decode-and-forward (DF) relay. The exploitation of ACK feedback channels from destination and relay leads to two possible implementations: 1) only-source manages the retransmission procedure or 2) both source and relay control the retransmissions. We analyze both options under a chase-combining ARQ protocol with limited number of transmission rounds, providing integral expressions for the throughput. This study allows the optimization transmission rate and the amount of resources allocated for the relay transmission.

This paper addresses the design of joint multi-cell resource allocation and scheduling with coordination among neighboring base stations (BS). Considering Nsneighboring sectors, the solution that maximizes the sum-rate in the covered area is found for TDMA and TDMA/OFDMA access. The optimum solution exhibits low complexity as it presents the useful property that its computation admits a decomposition such that each BS is responsible for the selection of the users to be scheduled in its own sector. This result is proved analytically.

The compress-and-forward (C&F) cooperative relaying strategy is known to outperform decode-and-forward (D&F) when the relay is close to the destination. In this paper, we derive achievable rates on Gaussian vector channels with cooperative C&F relaying. In order to extend previous information-theoretic results from the scalar to the vector Gaussian channel, we exploit recent results in distributed source coding. Like in source coding with side information at the decoder, the relay applies a conditional Karhunen Loeve transform (CKLT) to its observed signal, followed by a separate Wyner-Ziv encoding of each output stream with a different rate and under a sum-rate constraint. However, these Wyner-Ziv coding rates are such that the total mutual information between the source and destination is maximized. This differs from the conventional source coding approach in which the rates are selected to minimize the total squared distortion, leading to the well-known reverse-waterfilling algorithm. We show that the maximization of the C&F mutual information is also a convex problem. The optimum Wyner-Ziv coding rates have a simple analytical expression, and can be obtained by a waterfilling algorithm. Finally, we illustrate these results by simulations of MIMO-OFDM relaying in a system similar to IEEE802.16.

This paper deals with the design of non-regenerative relays in cooperative transmission schemes. The conventional nonregenerative approach is the amplify and forward (AF) approach, where the signal received at the relay is simply amplified and retransmitted. In this paper, we propose an alternative design which maximizes the capacity for nonregenerative cooperative transmission, when channel state information is available at the relay station. Therefore, the relay units are not simple amplify and forward units, but still they are not required to demodulate or remodulate the symbols transmitted by the base station as in regenerative relaying schemes. We compare the performance so obtained with the performance for the conventional AF approach, and also with the performance of regenerative relays and direct noncooperative transmission.

An iterative game theory based algorithm is proposed to allocate the resources in cooperative schemes for the downlink. Both amplify-and-forward (AF) and decode-and-forward (DF) cooperative schemes are considered with cellular reuse of the relay slot. Multiple antennas can be used at the involved stations. Using the algorithm proposed, the simultaneous relay powers are decided in a decentralized way using mean channel level measures and mean values of noise and interference power. The cell capacity gain for the cooperative schemes using the decentralized algorithm is evaluated by means of simulation for both the AF and DF approaches.

The performance of downlink coded cooperative transmission in mobile communication systems is evaluated. Cooperative transmission is seen as a "virtual" MIMO system where multiple transmit antennas are provided by a relay station and the base station, and different space-time block coding schemes are considered. Regenerative and non-regenerative systems are considered for the cooperative schemes. The use of rate compatible puncture turbo codes as forward error correction codes allow the system to be tested under the hybrid-type II automatic repeat request protocol. Results in terms of throughput show the benefits of coded cooperation over direct transmission.

A new time variant wideband propagation channel model is presented for user location applications in third generation mobile environments. The model considers evolutionary angle of arrival (AOA) and evolutionary time of arrival (TOA), based on the real instantaneous relative user equipment and base station position. The channel model proposed is used also in a link level simulator (LLS) to estimate realistic delay and angle of arrival coherence time, that is, the time in which position and time delay and angle of arrival for the received signal remain almost constant. In order to increase the time integration period and consequently reduce the error in geographical positioning, the maximum coherence time has to be known in the time delay and angle estimating process. The new wideband propagation channel model will provide the delay and angle estimating process with realistic coherence time and Doppler spread. The model also provides spatial correlation matrices for different diversity base station (BS) antenna schemes and compares them with experimental results.

Multiuser detection has been investigated to mitigate the near-far effect in CDMA systems. Antenna arrays have been shown to provide spatial diversity and cancel undesired signals. In this paper we consider the synergy of both multiuser detection and antenna arrays for the base station of a CDMA system. The receiver we proposed consists of the known multiuser decorrelator, which cancels multiple-access interferences followed by a beamformer for each user, which cancels the external interferences. This receiver adds an extra branch to the decorrelator. This additional branch, corresponding to a fictitious user with an unused code and zero power, allows to estimate the external interference signal subspace and compute a suitable beamforming weight-vector that cancels the external interferences. The receiver is also extended to the asynchronous case and all of this without any training signal or any a priori spatial information.

This paper studies the potential benefits of antenna arrays in cellular CDMA communications and proposes a powerful scheme to undertake the array processing at the base station in CDMA mobile systems. The proposed technique exploits the temporal structure of CDMA signals. The necessary information is extracted directly from the received signals, thus no training signal or "a priori" spatial information is required. Making use of the overall information present at the receiver after the despreading, the technique presented, jointly with singular value decomposition, estimates the generalized steering vector for each user. Then, an optimal combining of the signal received at each antenna is undertaken, achieving substantial robustness against fading and near-far problems.