The time-domain signal in orthogonal frequency division multiplexing (OFDM) has a large peak-to-average power ratio (PAPR). Most existing solutions for this problem are designed for OFDM systems operating with a fully-digital MIMO architecture. However, these solutions cannot be used for an OFDM system operating with a hybrid beamforming architecture. Therefore, in this work we address PAPR reduction in OFDM with hybrid beamforming. We propose to transmit a PAPR reduction signal along with the precoded information signal. For an efficient design of the PAPR reduction signal, we propose to use extra radio frequency (RF) chains. The design of the PAPR reduction signal and the analog beamformers corresponding to the extra RF chains, is written as a constrained optimization problem. An iterative algorithm based on successive convex approximation is proposed to solve the optimization problem. We show that the proposed technique achieves a considerable end-to-end performance gain in the presence of a non-linear power amplifier.

The single carrier modulation is a potential candidate at the sub-THz band, because of the channel sparsity and the necessity for an analog front-end friendly modulation. However, the peak-to-average-power ratio (PAPR) of the single carrier modulation in a multi-user MIMO downlink scenario is still a concern. In this work, we address this problem, by transmitting a PAPR reduction signal (PRS) together with the precoded data symbols. The goal of the PRS is to reduce the PAPR of the continuous-time signal entering the power amplifier attached to each antenna. We propose two different methods to design the PRS. In the first method, we restrict the PRS to the channel null space, so that it does not cause interference with the users’ information symbols at the receiver. As such, this method has limited degrees of freedom for the PAPR reduction. Considering this, we propose a second method for the PRS design, where the PRS can interfere with the users’ information symbols in a constrained manner. This relaxation enables an increased PAPR reduction without reducing the data detection performance. The design of the PRS is formulated as an optimization problem and the performance of the proposed schemes is studied semi-analytically. Our analysis shows that the proposed scheme is able to reduce the PAPR by about 9 dB at the cost of only 0.5 dB SINR. Consequently, the bit-error-rate performance of the proposed scheme is negligibly impacted by non-linear power amplifier distortion.

This paper investigates a dual-polarized intelligent reflecting surface (DP-IRS)-assisted multiuser multiple-input multiple-output (MIMO) wireless network with the possibility of multi-stream transmission per user. We aim to determine the number of data streams per user while simultaneously ensuring that each user achieves its specified target spectral efficiency performance with the minimum transmit power. To achieve this, we optimize the number of data streams, power allocations, transmit/receive digital filters, DP-IRS operations, and transmit/receive DP antennas phase shifters. Based on this generalized network setup, we formulate an optimization framework involving multiple coupled optimization variables. To tackle this complex optimization problem, we first derive low-complexity convex formulations for each variable. Subsequently, we propose a novel multi-step alternating optimization algorithm that effectively solves multiple subproblems sequentially and converges to a feasible solution. Motivated by further complexity reduction, we present a low-complexity suboptimal version of the main algorithm. Extensive numerical simulations demonstrate that, compared to a simple IRS, the DP-IRS achieves a 42.4% reduction in transmit power for a configuration with 50 reflecting elements and eight users. Additionally, the proposed low-complexity Algorithm 2 incurs a 62% decrease in computational complexity compared to Algorithm 1 while maintaining satisfactory performance.

Analog beamforming (ABF) is a key enabler for high-throughput mmWave communication to harvest sufficient beamforming gain from large antenna arrays. It relies on beam alignment and the radio frequency (RF) architecture. In multiuser scenarios, beam alignment becomes challenging because of the inter-beam-interference between different users. Motivated by the large number of available antennas at the base station, we propose a downlink sparse ABF architecture in which only a subset of antennas per RF chain can be scheduled for the beamforming. For this purpose, we model the RF chain-antenna association as a binary association matrix (BAM) and jointly optimize the transmit beams and the BAM subject to RF hardware constraints. To alleviate the complexity of the resulting mixed–integer programming problem, we propose an iterative beam alignment and BAM optimization where the beam alignment and BAM are successively optimized until convergence. The proposed sparse-connected RF architecture performs significantly better than the traditional fully and partially connected architectures in terms of signal-to-interference-plus-noise ratio and bit error rate. The simulation results indicate that optimizing the BAM profiles relaxes the need for optimized beam allocation beyond beamforming along the line-of-sight.

The channel sparsity and the necessity for an analog front-end friendly modulation have made single carrier a considerable candidate for sub-THz communication. However, the peak-to-average-power ratio (PAPR) of the single carrier modulation in a multi-user MIMO scenario is still a concern. In this work, we reduce the PAPR of the single carrier scheme, by transmitting an additional PAPR reduction signal (PRS). The PRS is constrained to lie in the null space of the channel so that it does not cause interference with the users’ information symbols at the receiver. Moreover, the additional transmit power consumed by the PRS is studied. An optimization problem is formulated to design the PRS, and the optimal power allocation for the PRS is analyzed. Our analysis shows that by trading off only 1 % of the total transmitted power, a PAPR reduction of about 3 dB can be achieved. Further, our simulations reveal that when an optimal power is allocated to the PRS, the proposed scheme achieves a significant performance gain compared to the classical single carrier system in the presence of power amplifier distortion.

In this paper we study analytically the sensitivity of analog-beamformed multiuser downlink MIMO systems to imperfect beamforming (BF) state information at the transmitter and the receiver. We consider different distributions of the transmit and receive BF errors and evaluate the end-to-end performance in terms of the statistical distribution of the minimum signal-to-interference plus noise ratio (SINR) and derive accordingly, for small fluctuation errors, analytical approximation of the average SINR and the corresponding symbol error probability (SEP). The analytical approximations of the SEPs are further benchmarked with the simulated error performance for both uncoded and coded transmission and for two BF architectures namely partially (PCA) and fully (FCA) connected architectures. Simulation results in line-of-sight propagation revealed that (i) tight estimates mainly of the transmit BF angles are required in the order of a fraction of one degree for moderate number of transmit antennas especially for FCA, and (ii) the BF accuracy requirement becomes stringent as the system load increases. We argue that with a moderate to high number of transmit antennas, multiuser beam alignment achieving sub-degree BF accuracy will be one of the main challenges of future mmWave communication systems that rely on analog BF.11This research received the support of the COREnext project, funded by the European Union's Horizon Europe Research and Innovation Actions, under Grant Agreement$N^{\circ}l$01092598.

Orthogonal Chirp Division Multiplexing (OCDM), a chirp based waveform, has gathered interest because of its robustness to time and frequency selective channels. In this work, we study the phase noise effect in OCDM, which has not been investigated in the literature yet. We analytically show that phase noise causes a common phase error (CPE) rotation of data symbols and inter-symbol interference (ISI) in OCDM. We investigate the influence of OCDM system parameters on the phase noise effect. For this purpose, a system parameter, chirp frequency offset is defined and its influence on the CPE and ISI is studied. Depending on the value of this chirp frequency offset, either CPE or ISI becomes the dominant phase noise effect. Our findings also show that an OCDM system can be made robust to phase noise at the cost of spectral efficiency by reducing the number of employed chirps. Our performance analysis demonstrates that OCDM has a gain over OFDM and Single Carrier (SC) in a fading channel with phase noise because of the frequency diversity and the different distortion caused by the phase noise generated ISI terms respectively. We also investigate the performance of OCDM in the presence of narrowband interference with phase noise and observe that OCDM has a benefit over OFDM and SC at medium and low interference power.

This paper considers the cell-free (CF) massive multiple-input multiple-output (MIMO) architecture with an added virtual uplink radar integration. We consider joint communications and radar (JCR) in the uplink payload of the time-division duplex (TDD) frame and formulate a set of linear interference constraints in order to limit the user equipment (UE) interference imposed on the radar system at each accesspoint (AP) through power control. The constraints are incorporated into the sum spectral efficiency (SSE) and the sum-log-SNR (SLS) policies. Furthermore, a largest large-scale fading (LLSF) heuristic is formulated as an approximate low-complexity solution. Numerical simulations indicate that all methods provide similar performance in terms of spectral efficiency (SE) and that power control allows the communication system to be controlled to satisfy a given worst case radar performance.

This paper considers the cell-free (CF) massive MIMO architecture from a joint communication and radar point of view. We propose a protocol for communication and sensing, where the network allocates a set of access-points (APs) to participate in the uplink together with the users (UEs) to serve the network with a radar signal. This realizes the radar system as a distributed bistatic radar system, where the objective is to recover the radar echoes from the multiuser interference. The imposed cost on the communication system is the loss of one AP and the need to schedule one additional virtual UE per allocated AP. We present two modes of radar sensing, occurring in either the uplink training segment or the data payload segment of the communication frame. A subspace signal model and its corresponding generalized likelihood ratio test is developed in order to evaluate the detection performance. We present expressions for the probably of detection and false alarm, and demonstrate the system numerically. Our main message is that coordinating the network to transmit in the uplink together with the UEs serves as an interesting approach in enabling radar sensing in CF massive MIMO systems.

In this paper, a novel hybrid architecture is proposed combining expert knowledge for optimal power allocation and deep artificial neural networks (ANN) to address the access-point scheduling problem in cell-free massive multiple-input multiple-output (MIMO) communication systems with a serial bandwidth-limited fronthaul architecture. The scheduling task is formulated as an image segmentation problem for which a supervised encoder-decoder like ANN is proposed. It consists of serially concatenated contraction and expansion layers to maximize the (regularized) cross-entropy, followed by a binary projection to undo the relaxation problem. Besides the robustness to scenarios with a time-varying system load and fronthaul bandwidth, the proposed architecture provides a complexity-efficient solution that fulfills the fronthaul bandwidth constraints and satisfies the real-time considerations. Our experimental results verify the competitive performance of the proposed solution with respect to both nonlinear solvers and state-of-art convex algorithms while the time efficiency of the ANN model outperforms the state of the art, especially, in scenarios with a large number of users.

This paper considers the problem of radar sensing by using a large number of antennas. We use the orthogonal frequency division multiplexing (OFDM) waveform, and show that the large arrays used in massive multiple-input multiple-output (MIMO) communications enable accurate localization in the array near-field, even at the narrow bandwidths typically encountered at low carrier frequencies. We validate our findings experimentally with a massive MIMO testbed operating at 3.5 GHz carrier frequency and 18 MHz OFDM bandwidth in an indoor environment. We consider a single moving cylinder, and demonstrate a median accuracy of (3.4, 5.6) cm in ($x$,$y$) in the near-field. We show that the accuracy is maintained with only a single subcarrier, and that the resolution increases with an order of magnitude when combining all antennas, effectively surpassing the 16.67 m bistatic range resolution set by the OFDM waveform. We use a radar symbol duration of$71.88~\mu $s at an effective transmission period of 2.5 ms, which indicates that the radar and communication systems can be implemented in time-division with a capacity loss of only 2.9%. Our results suggest that near-field radar sensing can be integrated into future massive MIMO systems operating at low carrier frequencies and narrow bandwidths.

Fronthauling the traffic from/to large number of distributed access points (AP)s in the cell-free (CF) massive Multiple-Input Multiple-Output (MIMO) is one of the main challenges hindering the deployment of CF massive MIMO systems. As the point-to-point fronthaul architecture is not cost-effective, there is a need to move towards shared fronthaul mediums or a point-to-multipoint architecture that requires the proper user-AP scheduling to improve the overall performance while a constraint on the fronthaul bandwidth must also be respected. In this paper, a low-bandwidth system with centralized digital beamforming is considered and a novel algorithm is proposed for the joint power and AP scheduling problem. The proposed optimization framework provides a scalable solution for CF massive MIMO under stringent fronthaul bandwidth constraints.

Cell-free (CF) massive Multiple-Input Multiple-Output (MIMO) with large number of distributed access points (APs) has emerged as a new paradigm allowing higher macro diversity for randomly distributed users. However, the fronthaul traffic bandwidth between central processing unit and the APs can explode in particular in the uplink, requiring expensive star-topology with point-to-point fronthaul links. To achieve a scalable CF massive MIMO architecture and a cost-effective fronthauling solution, we consider, in this paper, a point-to-multipoint fronthaul topology where (a subset of) the APs share a serial fronthaul link offering a per-user limited fronthaul bandwidth. We develop a novel unified optimization framework for iterative power control and AP scheduling that provides a systematic user-centric solution towards scalable uplink CF massive MIMO. Experimental results show that power control is not sufficient to guarantee the best objective and, therefore, the appropriate association of the users to the APs is required to improve the overall system signal-to-noise ratio. Under the stringent fronthaul bandwidth, the proposed joint optimization framework results in i) significant 5% outage data rate increase ii) near uniform distribution of the served users per APs and, hence, an increased diversity and iii) fast convergence of the algorithm within a few iterations.

One of the major bottlenecks that hinders the deployment of Cell-free (CF) massive Multiple-Input MultipleOutput (MIMO) in a cost-effective way is the limited capacity of back/front-haul connections. In this case, the traffic between the large number of distributed access points (APs) and the central processing unit can easily explode. Expensive pointto-point fronthauling technologies are certainly not desirable hence a shared fronthaul medium should be foreseen wherein (a subset of) APs share the same bandwidth-limited medium. However, the point-to-multipoint architectures require proper AP scheduling. In this paper, we propose a novel unified optimization framework for iterative power control and AP scheduling in the uplink of the cell-free massive MIMO system, that offers a systematic user-centric solution towards scalable CF massive MIMO. The experimental results show that power control is not sufficient to reach the best minimum throughput and, therefore, an appropriate association of the users to the APs is crucial to improve the overall system performance.

Due to the continuous demand for higher bit rates, the management of the spatio-temporal intersymbol interference in frequency-selective multiple-input multiple-output (MIMO) channels becomes increasingly important. For single-input single-output channels, equalized precoded partial-response signaling is capable of handling a large amount of intersymbol interference, but, to date, no equalization scheme with general partial-response signaling has been presented for the frequency-selective MIMO channel. Not only does this contribution extend partial-response signaling to the MIMO channel by proposing a general spatio-temporal partial-response precoder, but it also develops a minimum mean-squared-error optimization framework in which the equalization coefficients and the spatio-temporal target response are jointly optimized. Three iterative optimization algorithms are discussed, which update (part of) a row of the target impulse response matrix in each iteration. In particular, the third algorithm reformulates this row optimization as a lattice decoding problem. Numerical simulations confirm that the general partial-response signaling clearly outperforms the traditional full-response signaling in terms of the mean squared error and the bit error rate. The third optimization algorithm has a better performance but a higher complexity, compared to the first and the second algorithm.

Partial-response signaling is known to facilitate the equalizer design because a controlled amount of residual interference is permitted. The design of the target impulse response of the partial-response precoder often assumes perfect channel state information, which is unfortunately not available at the transmitter in most practical applications. Consequently, this contribution focuses instead on the robust and joint design of a spatio-temporal target impulse response and the equalization coefficients for a frequency-selective fading multiple-input multiple-output communication channel based on current and/or previous noisy channel estimates. More precisely, the error in the channel estimates is statistically modeled, and robustness is achieved by minimizing the mean-squared estimation error averaged over the joint distribution of the actual channel and the available channel estimates. Numerical results of the bit error rate confirm that the proposed robust partial-response signaling not only provides a significant performance gain compared to traditional full-response signaling, but also outperforms the naive approach, which ignores channel estimation errors.

It is claimed in the scientific community that vector perturbation (VP) typically outperforms Tomlinson-Harashima precoding (THP). Our aim in this contribution is to revisit these claims and provide more insights. In this comparison, we mainly focus on lattice reduction-aided VP, which significantly reduces the complexity of the optimal sphere encoding used as a benchmark. For the typical wireless THP precoding with a diagonalizing precoder and scalar-based power loading to enforce the sum power constraint, it is found that in well-conditioned channels, THP always outperforms LR while in ill-conditioned channels, LR is preferred. The stream ordering optimization allows the THP to win over a wider range of channel condition numbers with a further reduced gap towards LR, especially in large scale multiple input multiple output (MIMO) systems.11The author acknowledges the review of Dr. C. Nuzman.

High-speed communication over mutually coupled channels can be severely affected by intersymbol interference (ISI) and crosstalk (XT). Multiple-input multiple-output (MIMO) equalization is known to mitigate both ISI and XT, but requires accurate channel information at the receiver (RX) and/or transmitter (TX), when the channel is stochastic. However, since adjusting the equalization filters to the specific channel realization involves a considerable implementational and computational complexity, it is desirable to keep the equalization filters fixed irrespective of the specific channel realization, especially when the channel variability is relatively small. Therefore, we propose a general MIMO transceiver scheme where the equalization filters depend on the channel statistics rather than the actual channel. More specifically, by considering the time-domain equalization with the fixed linear MIMO pre-equalization and adjustable MIMO decision feedback equalization, the complexity associated with passing channel information from the RX to the TX is avoided, and the computationally intensive and iterative calculations of the fixed pre-equalizer can be performed offline rather than on-chip. The proposed equalization scheme is shown to yield only a small performance degradation compared to fully adjustable equalization schemes, thereby enabling multi-Gbit/s chip-to-chip communication over low-cost electrical interconnects which are prone to manufacturing tolerances.

While the requirements for delivering high throughputs increase exponentially with every generation of access node hardware, the device cost is of primary concern. As a result, multiple- input multiple-output (MIMO) equalization, which has been shown to facilitate multi-Gbit/s communication over low-cost parallel electrical interconnects, is emerging as an attractive high- speed interconnect solution for next-generation access nodes. Because of the high operating frequencies, however, the transfer functions of the on- and off-chip interconnects become highly susceptible to manufacturing tolerances (MTs); hence, the equalization filters must be adjusted to the specific channel realization to achieve optimal performance, which involves a high implementation and computational complexity. Considering that the MTs are usually limited, we propose a robust low-complexity transceiver consisting of a fixed MIMO linear pre-equalizer (which avoids the need for feeding back the channel state information to the transmitter), with either a fixed or adjustable MIMO decision- feedback equalizer (DFE). For a specific chip-to- chip interconnect operating at 75 Gbit/s per line and a 26 dB signal-to-noise ratio, we show that the resulting bit error rate does not exceed 10^(-12) for MTs up to 10.5% (fixed DFE) and 17.7% (adjustable DFE) of the nominal line width.

In this contribution, we present a linear multiple-input multiple-output (MIMO) equalization scheme at the receiver side for high-speed electrical chip-to-chip communication. As opposed to traditional single-input single-output (SISO) equalization per lane, this MIMO approach enables cooperating receivers to treat crosstalk (XT) between neighboring channels as an information-bearing signal instead of a disturbing signal, allowing to mitigate both inter symbol interference and XT. Given a simulated 4 × 4 MIMO electrical chip-to-chip interconnect channel, we point out that, for a given total number of equalizer taps, MIMO equalization can outperform SISO equalization. Moreover, by further increasing the total number of equalizer taps, MIMO equalization allows to obtain performance gains that are substantially larger than for SISO equalization.

Precoding is a technique that counteracts the crosstalk in downlink digital subscriber line (DSL) transmission. While linear precoding is adequate in the VDSL2 technology because of the moderate crosstalk environment, this might no longer be the case in the G.fast technology, which uses higher frequencies and therefore is affected by higher crosstalk levels. In this contribution we compare linear and nonlinear precoding for G.fast transmission protected by trellis-coded modulation, and present two bitloading algorithms that are suited for both precoding schemes. We show that for a set of measured broad-band channels, each representing a binder of eight twisted-pair cables, these bitloading algorithms have substantially different complexities but yield a similar information bitrate, which is about 10% higher for nonlinear precoding as compared to linear precoding.

We extend studies on power optimization in VDSL2 to G.fast, the technology under definition. In vectored G.fast the power of the signals before precoding needs to be optimized to meet power spectral density and maximum aggregate transmit power constraints per line. We formulate this interplay between vectoring and power optimization, with non-vectored transmission as a particular case. Three power allocation algorithms are devised that allow a tradeoff between optimality and computational complexity. Measured channel data from a European operator up to 106 MHz is considered. Numerical evaluation reveals that low complex heuristics for power optimization yield near optimal solutions both with perfect and imperfect channel state information. Similar conclusions hold for the 212 MHz profile.

There are two types of crosstalk in digital subscriber line (DSL) systems, namely near-end crosstalk (NEXT) and far-end crosstalk (FEXT). NEXT is usually much stronger than FEXT. Therefore, high-speed DSL systems transmit in preplanned disjoint downstream (DS) and upstream (US) frequency bands to avoid NEXT. Although easy for implementation, such a fixed bandplan can lead to inefficient bandwidth usage, depending on the DS and US bit rate requirements and the loop topology, particularly in so-called vectored DSL systems, which include signal coordination for FEXT cancellation. In dynamic bandplanning (DBP), each frequency band is allocated to either DS, US, or to both directions depending on the aforementioned parameters. In this paper, we consider optimal DBP for vectored DSL with linear as well as with nonlinear transmitter/receiver structures. We propose an optimal DBP algorithm for systems with disjoint DS and US bands. For systems with overlapping bands, the problem of finding the optimal transmitter/receiver filters is nonconvex and we propose two iterative algorithms based on recent optimum spectrum balancing schemes from the literature. We also study the effect of echo and US NEXT cancellation on the system performance. Finally, simulation results are provided to demonstrate that our algorithms can indeed significantly increase the achievable bit rates.

We present a measurement study of the energy consumption of an operator-side digital subscriber line (DSL) board under various conditions of data rate and power spectral density, with and without vectoring. The results highlight practical opportunities and challenges for optimizing rate-power-stability tradeoffs in DSL access systems, complementing simulation-based studies focused on energy reduction through spectral optimization. We validate models for line board consumption that can be tied with line driver consumption based on the aggregate transmit power of each line, and demonstrate that near-optimal rate-power-stability tradeoffs can be obtained through external line management of data rate, Signal-to-Noise-Ratio margin and power spectral density parameters.

Vectoring technology allows removing far-end crosstalk from coordinated digital subscriber lines. Challenges arise when vectored lines are mixed with legacy VDSL2 lines in the same binder. Using data rate targets from the European Union's Digital Agenda, we show that an automated line management technique based on scalar parameters that control the maximum transmit power spectral density, signal-to-noise-ratio margin and data rate allows the vectored lines to recover part of the performance loss due to the presence of the legacy lines when the data rate on these legacy lines is significantly capped. This is a practical solution when all lines are served by a single operator. When multiple operators serve lines in the same access network, this technique does not provide a fair competition between the operators without loss of vectoring gains, and virtual unbundling may be preferred.

We consider Discrete Multitone Transmission over short Digital Subscriber Lines using bandwidths applicable to G.fast, in the presence of impulsive noise. Various combinations of coding and retransmission schemes are compared in terms of bit error ratio performance and error-free information bitrate (goodput). Our study shows that, under an error performance constraint, retransmission schemes allow to achieve larger good-put with smaller latency as compared to the traditional combination of Reed-Solomon coding and Trellis Coded Modulation with a large interleaver in between.

Different precoder and equalizer structures have been proposed in literature for vectored digital subscriber lines (DSLs). In this paper, we assess the relative merit of advanced complex precoders and equalizers in practical DSL scenarios. Using extensive computer simulations, the achievable bit rates are investigated in the presence of alien crosstalkers, assuming a beta distribution model for crosstalk couplings. Vectoring in conventional as well as phantom mode (PM) VDSL2 transmission is considered. Vectoring techniques at the access-node (AN) are studied such as the zero-forcing equalizer (ZFE), ZF generalized decision feedback equalizer (ZF-GDFE), linear minimum mean squared error (MMSE), and MMSE-GDFE for upstream (US) scenarios and zero-forcing precoder (ZFP) for downstream (DS) scenarios. Vectoring is also considered at the customer premises (CP) in PM transmission. The results show that when there are no alien crosstalkers, the low-complexity ZFE allows reaching crosstalk-free rates in US direction. However using an MMSE-GDFE and if the noise spatial covariance information is assumed static, considerably higher bit rates can be achieved for long loops in the presence of alien crosstalkers. This rate increase comes at the expense of increased delay. In DS direction, the ZFP can achieve crosstalk-free rates in the absence of alien crosstalkers. The results also show that the use of vectoring techniques at the CP in PM transmission does not increase the achievable bit rates in US or DS direction when vectoring is already employed at the AN.

In this paper, we consider optimal dynamic spectrum management (DSM) for a downstream (DS) DSL scenario in which users are divided into a few separate groups, where vector encoding based signal coordination can be applied in each group and spectrum coordination is possible for all users. This can be seen as a mixed interference/broadcast channel (IF/BC) scenario. We investigate several candidates for vector encoding the signals inside the groups, including the linear zero-forcing (ZF) pre-compensator, ZF Tomlinson-Harashima pre-coder (THP), optimal linear pre-compensator (OLP), and THP with optimal transmit filters. The calculation of the optimal transmit filters (for both the linear pre-compensator and THP) is a non-convex problem. To resolve this problem, we develop a generalized duality between the IF/BC and IF/multiple-access channel (MAC). In order to achieve the highest data rates, optimal spectrum balancing (OSB) is applied to all users on top of the vector encoding inside the groups. Simulation results show that the grouped THP with optimal transmit filters achieves considerably higher bit rates than the other schemes. The resulting algorithm is referred to as the IF/BC-OSB algorithm, and encompasses the OSB (i.e., IF-OSB) and the earlier developed BC-OSB algorithm as special cases.

The ever growing demand for higher data rate is pushing existing electrical broadband communication systems, using coax or twisted pair cabling, to the limit. While optical access systems inherently have a much higher transmission capacity, upgrading the access network entirely to fiber remains a costly and time-consuming effort. Therefore, many operators deploy fiber gradually closer to the end user, while bridging the remaining distance through copper technologies such as VDSL2. In the next step of this evolutionary path, fiber is brought to distribution points that are in the range of no more than 200 m from the end user, with a copper access technology called G. fast delivering data rates of 500 Mb/s to 1 Gb/s over the remaining copper stretch. In this paper, we give an overview of the G. fast technology that is currently being standardized in ITU. We show the feasibility of its main technical requirements, namely i) powering of the access equipment through the customer premises modem, ii) high transmission efficiency for orthogonal frequency division multiplexing over short copper loops and iii) offering high net data rates to end users.

The continued growth of multimedia traffic pushes access network operators to further boost performance over their copper infrastructure network. As a result, digital subscriber line technology has evolved substantially. Field and lab trials have proven that recent innovations, such as crosstalk cancellation and phantom mode transmission, can push data rates of VDSL2 higher than 100 Mb/s on a single twisted pair and 300 Mb/s on two pairs. In ITU-T Q4, a new access technology to provide aggregate data rates in the range of 500 Mb/s to 1 Gb/s per copper loop of up to a few hundred meters is being defined under the G.fast project. G.fast enables the continued cost-effective deployment of fiber in the access network. In this paper, we give an overview of some key challenges this new access technology needs to overcome. By taking into account the expected access network topology, we give guidelines for the node architecture and deployment of G.fast.

In this paper, we investigate joint level 2 and 3 dynamic spectrum management (joint DSM 2/3) for downstream (DS) DSL. We consider a DS scenario in which users are divided into a few separate groups, where vector encoding based signal coordination can be applied in each group and spectrum coordination is possible for all users. This can be seen as a mixed interference/broadcast channel (IF/BC) scenario. In order to obtain the optimal transmitter structure, we develop a generalized duality between the vector broadcast and multiple-access channel (MAC) for scenarios in which partial signal coordination is available among users. This theory together with optimal spectrum balancing (OSB) is exploited to calculate the jointly optimal filters and transmit powers for non-linear vector dirty paper coding structures (in the form of Tomlinson-Harashima precoder (THP)) in the groups. The proposed scheme is compared to several other joint DSM 2/3 algorithms for DS DSL. Simulation results show that the proposed scheme (referred to as the IF/BC-OSB algorithm) achieves considerably higher bit rates than the other schemes. IF/BC-OSB encompasses the earlier developed BC-OSB algorithm as a special case. A simplified version of IF/BC-OSB avoiding exhaustive search with near-optimal performance is also proposed.

Crosstalk cancellation, also known as vectoring, is a promising technique that significantly increases the capacity of digital subscriber line access networks. In this paper, the potential of vectoring to boost the capacity in a realistic copper access network is demonstrated. Deployment of vectoring becomes challenging when not all crosstalk can be eliminated due to the presence of uncontrolled lines or due to limited cancellation resources. Lines can be outside of the vectoring group because of technological constraints or regulation. As a result, the performance of vectoring degrades as compared to full cancellation. Based on representative simulations and lab measurements, different deployment guidelines are proposed along with a discussion on their practicality.

The Packet Processor (PP) or Network Processor is one of the main building blocks found in Ethernet based access nodes. The PP is typically implemented on line-boards of access nodes such as Digital Subscriber Line Access Multiplexers (DSLAMs) for copper and Optical Line Terminals (OLTs) for fiber. It mainly deals with L2 functions such as VLAN tagging, forwarding and QoS at the packet level. Other functions which can be implemented in the packet processor are multicast, protocol adaptation functions and L2 security features such as MAC address spoofing. In this paper we present the different paths towards energy efficient PPs for different traffic mixes. For this purpose, we elaborate on a simplified block diagram of the PP and show the relationship between the incoming data and packet rates. After revisiting the dynamic nature of the data usage by the typical broadband consumers, we propose an empirical model relating the energy consumption of the PP versus the packet rate and other design technology parameters. The energy efficiency of the PP reveals different cost/power trade-offs. Additionally we show that potential energy saving can be realized when designing a PP that is optimized for the expected peak load and scales-up with the actual traffic load. Two use cases in the numerical result section, one for copper and one for fiber based access networks, show that up to 25% energy saving in the PP can be realized.

Dynamic spectrum management (DSM) refers to a wide range of techniques for counteracting crosstalk in digital subscriber line (DSL) networks. DSM is categorized into three levels based on the degree of coordination among users. In this article, we investigate optimal joint level 2 and 3 DSM for upstream DSL. We will discuss the difficulties of finding the universally optimal solution and we propose an optimal algorithm, referred to as IF/MAC-OSB, under some practical and implementation assumptions for this problem. Using computer simulations, we show that IF/MAC-OSB is capable of increasing the user bit rates considerably compared to several other DSM techniques. The proposed algorithm involves using the minimum mean squared error (MMSE)-generalized decision feedback equalizer (GDFE) together with Lagrange dual optimization. We address several aspects of the problem including the optimal decoding order in the GDFE receiver, GDFE error propagation, and the computational complexity of the algorithm. We also study effects of channel model randomness and upstream power back-off utilization on the performance of the algorithm.

The design of crosstalk mitigation techniques for DSL broadband access systems has mainly focused on physical layer transmit rate maximization. However, for certain applications, upper-layer performance metrics like network throughput, stability and delay performance may be more relevant. In this paper, we present a number of dynamic resource allocation based algorithms for partial crosstalk cancellation (PCC) that focus on these upper-layer metrics. A first algorithm focuses on preserving transmission queueing stability while maximizing the transmit rate. This is then extended towards budget adaptive algorithms, which dynamically adapt the PCC so as to improve the resource efficiency and to obtain a desirable trade-off between delay performance and resource consumption. Simulation results demonstrate the improved stability of the proposed algorithms and the obtained trade-off between delay performance and resource consumption.

To gradually expand their networks, operators deploy new xDSL technologies from remote terminals (RT's) closer to the customer. However, since xDSL lines deployed from an RT can share a binder with lines deployed from the central office (CO), a near-far problem is introduced and crosstalk may cause a severe performance degradation for the CO-deployed lines. RT lines have to be careful about how to allocate transmit power to the transmission frequencies, such that the impact on the CO lines is acceptable. Noise impact (NI) methods have been proposed based on a target noise shape generated by the disturbers (RT lines). In this paper new methods based on the actual impact on the bit rate of the victims (CO lines) are proposed. These bit impact (BI) methods closely approximate the optimal power allocation.

In this paper we investigate the tracking performance of the downstream (DS) crosstalk (XT) channel estimation based on the reported signal to noise ratio (SNR), in particular for digital subscriber line (DSL) systems. Aiming to its simplicity, the SNR-assisted XT estimation, has been recognized in ITU as a backward compatible method that does not require any change in the very high speed digital subscriber line 2 (VDSL2) standard. This low complex algorithm can be used for XT channel estimation in dynamic spectrum management (DSM) techniques today. The algorithm as proposed, relies on sending perturbing signals on the victim lines (VLs) and reporting the SNRs by those lines to acquire the crosstalk channel from some disturber line (DL) to the VLs. We generalize this concept to include full startup, tracking and joining scenarios as well as the impact of different perturbation signal choices. Simulation results reveal that starting from no crosstalk precompensation, and updating a precoder matrix based on the DS crosstalk channel estimates, the far-end crosstalk (FEXT) free SNR can be reached in few iterations (36 SNR measurements for the four lines case).

In this paper, we present a new method to estimate the crosstalk channels in VDSL systems, allowing to implement well-known pre-compensation schemes. As opposed to previously presented methods, this estimation only requires minimal changes to the current standard and equipments. It is based on the concept of adding small, controlled, perturbations to the transmitted signal and observing the related changes to the SNR at the receiver. It is shown in this paper that, based on a limited amount of SNR measurements from the receivers, it is possible to accurately estimate the crosstalk channels, both in amplitude and phase.

A statistical model has been constructed that extends the phenomenological 99% cumulant model to a full cumulative distribution function for amplitude and phase of the far end crosstalk between twisted pair telephone wires. The offset of the crosstalk amplitude relative to the 99% level is described by a frequency independent beta distribution. Inter-binder crosstalk is modeled by an additional parameter that reflects the distance between the two binders. The multi-line behavior of the beta model is shown to be close to the currently agreed scaling factor without additional forcing.

In xDSL systems, crosstalk can be separated into two categories, namely in-domain crosstalk and out-of-domain crosstalk. In-domain crosstalk is also referred to as self crosstalk. Out-of-domain crosstalk is crosstalk originating from outside the multi-pair system and is also denoted as external noise (alien crosstalk, radio frequency interference,...). While self crosstalk in itself can easily be canceled by a linear detector like the ZF detector, the presence of external noise requires a more advanced processing. Coordination between transmitters and receivers enables the self crosstalk and the external noise to be mitigated using MIMO signal processing, usually by means of a whitening filter and SVD. In this paper, we investigate the problem of finding the optimal power allocation in MIMO xDSL systems in the presence of self crosstalk and external noise. Optimal Tx/Rx structures and power allocation algorithms will be devised under practical limitations from xDSL systems, namely per-modem total power constraints and/or spectral mask constraints, leading to a generalized SVD-based transmission. Simulation results are given for bonded VDSL2 systems with external noise coming from ADSL2+ or VDSL2 disturbing lines, along with a comparison between algorithms with one-sided signal coordination either only at the transmit side or the receive side.

Rapid acquisition of accurate crosstalk estimates is a core requirement for effective preceding in digital subscriber line (DSL) systems. It is shown that signal-to-noise ratio (SNR) reports provided by customer premises equipment (CPE) can be used to perform this task by "tuning" the precoder, i.e., iterating alternate steps of estimation and precoder adaptation. Such an approach has the advantage that it can be applied to legacy CPEs. Estimation algorithms are designed using techniques from stochastic control.

Spectrum-overlay scenarios for wide-band multi-carrier (MC) systems bring new technical challenges along that must be considered during the system design. In such scenarios, the receiver has to perform actions, such as channel estimation and synchronization, in the presence of possibly strong in- band interference. In this paper, we investigate the impact of digitally modulated narrowband interference (NBI) on the iterative algorithm for joint channel estimation and frame synchronization as proposed in (Guenach et al., 2008) for uplink MC-CDMA. Moreover, we modify the algorithm to have better performance in the presence of NBI. The performance of the modified algorithm taking into account the statistics of NBI is verified through computer simulations and compared with the results from (Guenach et al., 2008).

The estimation and tracking of the fractional carrier frequency offset (CFO) is a crucial issue in the implementation of orthogonal frequency division multiplexing (OFDM) systems. In this contribution, we present a novel code-aided fractional CFO estimation algorithm based on the expectation-maximization (EM) algorithm. The proposed algorithm exchanges soft information from the channel decoder, in the form of a posteriori probabilities of the coded symbols, between the demapper, the decoder, and the CFO estimator in an iterative way. The proposed estimation scheme can work with any detector as long as the detector is able to compute the a posteriori probabilities (APPs) of the data symbols.

In this contribution, we propose a novel code-aided channel tracking and carrier frequency offset (CFO) and/or phase noise (PN) estimation algorithm for orthogonal frequency-division multiplexing (OFDM) systems. Starting from the maximum-likelihood (ML) principle, we derive a low complexity estimator based on the expectation-maximization (EM) algorithm. It turns out that the estimator receives soft information from the channel decoder to refine the CFO, PN, and channel estimates. Simulation results revealed that the proposed algorithm outperforms the conventional techniques in terms of bit-error rate (BER).

In this contribution, we propose a new code-aided synchronization and channel estimation algorithm for uplink MC-CDMA. The space alternating generalized expectation- maximization (SAGE) algorithm is used to estimate the channel impulse responses, propagation delays and carrier frequency offsets of the different users. The estimator, multi-user detector, equalizer, demapper and channel decoder exchange soft information in an iterative way. The performance of the proposed algorithm is evaluated through Monte Carlo simulations. Impressive performance gains are visible as compared to a conventional data-aided estimation scheme.

Spectrum-overlay scenarios for wideband multi-carrier (MC) systems bring new technical challenges that must be considered during the system design. In such a scenario, the receiver has to perform actions, such as channel estimation and synchronization, in the presence of possibly strong in-band interference. In this paper, we modify the iterative maximum likelihood joint frame synchronization and channel estimation algorithm for downlink MC-CDMA presented in (M. Guenach et al., 2006) to have better performance in the presence of narrowband interference. The performance of the modified algorithm is verified through computer simulations and compared with the original one.

This paper deals with joint data detection, synchronization and channel parameter estimation for direct-sequence code-division multiple-access systems over frequency-selective channels. In low-signal-to-noise ratio environments, conventional data-aided (DA) estimation algorithms may require an unacceptably large number of pilot symbols in order to obtain sufficiently accurate estimates of the channel and synchronization parameters. Especially, frequency offset estimation results in a significant loss in spectral efficiency. In this contribution, we consider several code-aided estimation schemes which can be incorporated in an iterative turbo detection scheme. We consider the expectation maximization algorithm, as well as the space alternating generalized expectation maximization algorithm as tools to develop code-aided estimation algorithms for a variety of scenarios. We pay special attention to the issue of computational complexity, and propose some complexity-reducing approximations. We show through computer simulations that the proposed code-aided estimation techniques considerably outperform their conventional DA counterparts.

In this paper, we present a novel code-aided joint synchronization and channel estimation algorithm for downlink multicarrier code-division multiple access. The expectation-maximization algorithm is used to locate the maximum-likelihood estimate of the channel impulse response, propagation delay, and carrier frequency offset. The estimator accepts soft information from the decoder in the form of a posteriori probabilities of the coded symbols, and can be interpreted as performing joint estimation and data detection. The performance of the proposed algorithm is verified through computer simulations. Impressive performance gains are visible as compared with a conventional data-aided estimation scheme.

We describe a class of low-complexity channel parameter and frequency offset estimation algorithms, applied to a space-time bit-interleaved coded modulation (ST-BICM) scheme for burst-mode asynchronous DS-CDMA uplink transmission over frequency selective channels. Conventional estimation algorithms rely mainly on the presence of training symbols within the data stream, reducing both the energy- and bandwidth efficiency. Our main goal is to remove the need for long training sequences by exploiting the presence of an underlying error-correcting code. We derive an iterative estimation technique, based on the space alternating generalized expectation maximization (SAGE) algorithm, which iterates between detection and estimation stages. Performance results are illustrated through computer simulations

This paper deals with space-time detection and channel parameter estimation in a bit-interleaved coded modulation (BICM) scheme for asynchronous direct-sequence code division multiple access (DS-CDMA) transmission over frequency selective channels. Using a pilot sequence to obtain sufficiently accurate channel estimates for this system requires an unacceptably large number of pilot symbols. In this contribution, we consider several code-aided estimation schemes which can be incorporated in an iterative space-time (ST) turbo detection scheme. We point out that the EM algorithm, which has recently been addressed as a convenient tool for code-aided estimation, has some serious drawbacks because of the large number of parameters to be estimated. These can be resolved using the space alternating generalized expectation maximization (SAGE) algorithm. We show through computer simulations that the proposed low complexity ST receiver with SAGE estimation considerably outperforms conventional estimation schemes.

The performance of multi-user direct-sequence code division multiple access (DS-CDMA) transmission over frequency selective, slowly fading channels strongly depends on the reliability of the channel parameter estimates: state-of-the-art detection algorithms that exploit multiple-access-interference and inter-symbol-interference require very powerful estimation algorithms. In this contribution we consider a system with bit-interleaved coded modulation (BICM) with an iterative detector consisting of minimum mean squared error (MMSE) interference cancellation, followed by a soft demapper and a MAP decoder. We derive an estimator that makes use of the a posteriori probabilities computed by the detector. This multi-user estimator is based on the iterative space alternating generalized expectation maximization (SAGE) algorithm. We show through computer simulation that the proposed receiver considerably outperforms conventional channel estimation schemes. Finally, the impact of different mappings in the BICM scheme is evaluated.

We investigate the performance of three multiuser tap weight estimators for multipath channels in data aided (DA) and decision directed (DD) modes for a BPSK DS-CDMA reverse link. The tap weights are estimated using different algorithms working separately or jointly in order to obtain good estimates as required for coherent detection or synchronization purposes. The performance of these algorithms and their sensitivity to the observation window, to the delay estimation error and to the difference between successive delays are investigated. A comparison between Hadamard and Gold codes is also included. The mean squared estimation error (MSEE) is computed and compared to the Cramer-Rao lower bound (CRLB).

We investigate timing recovery structures for a DS-CDMA multiuser uplink using codes with a period of several symbols named long codes and operating over frequency selective multipath and slowly Rayleigh fading channels. In order to implement RAKE reception the delays of the different paths have to be estimated and the estimates have to be updated. We extend interference mitigation to this estimation problem and design timing recovery schemes accounting for the intersymbol interference (ISI) and the multiple access interference (MAI) present in the signal. We first propose a multirate description of the long code DS-CDMA uplink. Then based on this formalism we revisit the optimum data-aided (DA) maximum likelihood (ML) delay estimation structure and the suboptimum early-late implementation. The sensitivity of the synchronizers to imperfect knowledge of path gains to the period of the long codes and to near-far situations is also investigated.

We consider a direct sequence code division multiple access (DS-CDMA) system operating over frequency selective multipath and slowly Rayleigh fading channels. In order to implement RAKE reception the delays of the different paths have to be estimated and the estimates have to be updated. We extend interference mitigation to this estimation problem and design timing recovery schemes accounting for the intersymbol interference (ISI) and the multiple access interference (MAI) present in the signal. Starting from the maximum likelihood (ML) approach we derive a decision-directed (DD) early-late synchronizer and its tracking performance is studied. The advantage of the interference mitigating synchronizer is illustrated. The sensitivity of the synchronizer to near-far situations is also investigated.

We consider the downlink of a Universal Mobile Telecommunication System terrestrial radio access-wideband code division multiple access (UTRA-WCDMA) system and we investigate the performance of the conventional RAKE receiver. A multipath slowly Rayleigh fading channel is assumed. For the purpose of channel tap weight estimation, a common control physical channel, that is either serial or parallel multiplexed with the dedicated physical channels, is used. The receiver sensitivity to imperfect knowledge of the path delays, to the number of pilot symbols, and to the power ratio of pilot to data channels is also investigated. The system performance is evaluated by means of bit-error rates (BERs) derived using quadratic forms and characteristic functions for a BPSK modulation. The mean-squared estimation error (MSEE) of the channel tap weights is also computed and compared to the classical Cramer-Rao lower bound (CRLB). The mutual interference between pilot and data symbols is taken into account.

We consider a direct-sequence code-division multiple-access system operating over frequency-selective multipath and slowly Rayleigh fading channels. In order to implement RAKE reception, the delays of the different paths have to be estimated and the estimates have to be updated. We extend interference mitigation to this estimation problem and design timing recovery schemes accounting for the intersymbol interference and the multiple-access interference present in the signal. Starting from the maximum likelihood approach, we derive data-aided and decision-directed early-late synchronizers and study their tracking performance. The advantage of the interference mitigating synchronizer is illustrated. The sensitivity of the synchronizer to imperfect knowledge of path gains and to near-far situations is also investigated.

This paper deals with the performance evaluation of an asynchronous UTRA-WCDMA uplink using a sequential algorithm for channel estimation and multiuser detection. A multipath slowly Rayleigh fading channel is considered. Both perfect and non-perfect channel estimations are studied with the pilot-to-data amplitude ratio as a parameter, when pilot symbols are transmitted in parallel with data. For channel estimation we use expectation maximization (EM) and spaced alternating generalized expectation maximization (SAGE) algorithms; for symbol detection we use interference cancellation. Bit Error Probabilities (BER) are derived using Monte Carlo simulations for binary phase shift keying (BPSK). The users may have different bit rates. In addition the mean squared estimation error (MSEE) of channel gains is computed and compared to the classical Cramer-Rao lower bound (CRLB).

This paper deals with the synthesis and the performance analysis of multiuser delay estimators of multipath channels according to the maximum likelihood (ML) criterion in data aided (DA) mode for a BPSK DS-CDMA uplink. We suppose the channel tap weights are known perfectly, and we are interested in the estimation of the path delays. We perform open-loop (S-curve) and closed loop mean squared estimated error (MSEE) analysis in tracking mode and we compare the results to the classical Cramer-Rao lower bound (CRLB).