This paper proposes a radio simultaneous location and mapping (radio-SLAM) scheme based on sparse multipath channel estimation. By leveraging sparse channel estimation schemes at millimeter wave bands, namely high resolution estimates of the multi-path angle of arrival (AoA), time difference of arrival (TDoA), and angle of departure (AoD), we develop a radio-SLAM algorithm that operates without any requirements of clock synchronization, receiver orientation knowledge, multiple anchor points, or two-way protocols. Thanks to the AoD information obtained via compressed sensing (CS) of the channel, the proposed scheme can estimate the receiver clock offset and orientation from a single anchor transmission, achieving sub-meter accuracy in a realistic typical channel simulation.

Rate Splitting (RS) has emerged as a flexible multiple-access scheme for Multi-User Multiple-Input Multiple-Output (MU-MIMO) systems, generalizing more conventional approaches such as linear precoding or Non-Orthogonal Multiple Access (NOMA), and providing additional robustness against imperfect channel state information at the transmitter. Actual achievable rates cannot be pre-calculated when facing imperfect and/or outdated channel state information at the transmitter (CSIT), so practical real-time mechanisms in the form of link adaptation (LA) are required. The available CSIT is used to design the RS precoders, which can accommodate some degree of robustness, whereas the physical layer feedback reports the outcome of the decoding of the codewords, in the form of acknowledgement (ACK) or negative ACK (NACK), providing the additional meta-robustness needed when the statistical model of CSIT errors is not accurate, and/or the precoders cannot fully track the channel dynamics. We characterize the outage rate region of RS and analyze the convergence of the complete LA-RS system under partial CSIT (non-accurate and non-permanent), providing relevant insights for addressing the adaptation of private and common rates, designing robust precoders with throughput as relevant metric, and handling the time-variant CSIT quality.

This paper studies the cross-layer challenges and performance of Hybrid Beamforming (HBF) and Multi-User Multiple-Input Multiple-Output (MU-MIMO) in 5G millimeter wave (mmWave) cellular networks with full-stack TCP/IP traffic and MAC scheduling. While previous research on HBF and MU-MIMO has focused on link-level analysis of full-buffer transmissions, this work reveals the interplay between HBF techniques and the higher layers of the protocol stack. To this aim, prior work on the full-stack evaluation of mmWave cellular networks has been extended by including the modeling of MU-MIMO and HBF. Our results reveal novel relations between the networking layers and the HBF MU-MIMO performance at the physical layer. Particularly, throughput can be increased in 5G networks by means of Space Division Multiple Access (SDMA). However, in order to achieve such benefits it is necessary to take into account certain trade-offs and the implementation complexity of a full-stack HBF solution.

This paper introduces a Compressed Sensing (CS) estimation scheme for Orthogonal Time Frequency Space (OTFS) channels with sparse multipath. The OTFS waveform represents signals in a two dimensional Delay-Doppler (DD) orthonormal basis. The proposed model does not require the assumption that the delays are integer multiples of the sampling period. The analysis shows that non-integer delay and Doppler shifts in the channel cannot be accurately modelled by integer approximations. An Orthogonal Matching Pursuit with Binary-division Refinement (OMPBR) estimation algorithm is proposed. The proposed estimator finds the best channel approximation over a continuous DD dictionary without integer approximations. This results in a significant reduction of the estimation normalized mean squared error with reasonable computational complexity.

This paper proposes link scheduling and power allocation algorithms for mmWave picocellular integrated access and backhaul networks. The proposed algorithm does not assume that interference is negligible and takes it into account in the solution. The algorithm supports any state of the art multi-user MIMO and hybrid beamforming schemes at the physical layer. The link scheduling and power allocation subproblems are solved using two separate simulated annealing (SA) algorithms which can also be individually combined with other pre-existing suboptimal algorithms for the other subproblem. Particularly, mixed-integer linear programming for fixed power link scheduling, which is optimal in a special interference-free case, is shown to perform much worse than the proposed algorithm. SA link scheduling with water-filling power allocation performs close to the optimal, while reducing power allocation complexity.

This paper analyzes the impact of non-Gaussian multipath component (MPC) amplitude distributions on the performance of Compressed Sensing (CS) channel estimators for OFDM systems. The number of dominant MPCs that any CS algorithm needs to estimate in order to accurately represent the channel is characterized. This number relates to a Compressibility Index (CI) of the channel that depends on the fourth moment of the MPC amplitude distribution. A connection between the Mean Squared Error (MSE) of any CS estimation algorithm and the MPC amplitude distribution fourth moment is revealed that shows a smaller number of MPCs is needed to well-estimate channels when these components have large fourth moment amplitude gains. The analytical results are validated via simulations for channels with lognormal MPCs such as the NYU mmWave channel model. These simulations show that when the MPC amplitude distribution has a high fourth moment, the well known CS algorithm of Orthogonal Matching Pursuit performs almost identically to the Basis Pursuit De-Noising algorithm with a much lower computational cost.

This paper studies the maximum throughput achievable with optimal scheduling in multi-hop mmWave picocellular networks with Multi-user Multiple-Input Multiple-Output (MU-MIMO) radios. MU-MIMO enables simultaneous transmission to multiple receivers (Space Division Multiplexing) and simultaneous reception from multiple transmitters (Space Division Multiple Access). The main contribution is the extension to MU-MIMO of the Network Utility Maximization (NUM) scheduling framework for multi-hop networks. We generalize to MU-MIMO the classic proof that Maximum Back Pressure (MBP) scheduling is NUM optimal. MBP requires the solution of an optimization that becomes harder with MU-MIMO radios. In prior models with one-to-one transmission and reception, each valid schedule was a matching over a graph. However, with MU-MIMO each valid schedule is, instead, a Directed Bipartite SubGraph (DBSG). In the general case this prevents finding efficient algorithms to solve the scheduler. We make MU-MIMO MBP scheduling tractable by assuming fixed power allocation, so the optimal scheduler is the Maximum Weighted DBSG. The MWDBSG problem can be solved using standard Mixed Integer Linear Programing. We simulate multi-hop mmWave picocellular networks and show that a MU-MIMO MBP scheduler enables a 160% increase in network throughput versus the classic one-to-one MBP scheduler, while fair rate allocation mechanisms are used in both cases.

This paper proposes and analyzes a mmWave sparse channel estimation technique for OFDM systems that uses the Orthogonal Matching Pursuit (OMP) algorithm. This greedy algorithm retrieves one additional multipath component (MPC) per iteration until a stop condition is met. We obtain an analytical approximation for the OMP estimation error variance that grows with the number of retrieved MPCs (iterations). The OMP channel estimator error variance outperforms a classic maximum-likelihood (ML) non-sparse channel estimator by a factor of approximately 2L̂/M where L̂ is the number of retrieved MPCs (iterations) and M the number of taps of the Discrete Equivalent Channel. When the MPC amplitude distribution is heavy-tailed, the channel power is concentrated in a subset of dominant MPCs. In this case OMP performs fewer iterations as it retrieves only these dominant large MPCs. Hence for this MPC amplitude distribution the estimation error advantage of OMP over ML is improved. In particular, for channels with MPCs that have lognormally-distributed amplitudes, the OMP estimator recovers approximately 5-15 dominant MPCs in typical mmWave channels, with 15-45 weak MPCs that remain undetected.

The scaling of coherent and non-coherent channel capacity is studied in a single-input multiple-output (SIMO) block Rayleigh fading channel as both the bandwidth and the number of receiver antennas go to infinity jointly with the transmit power fixed. The transmitter has no channel state information (CSI), while the receiver may have genie-provided CSI (coherent receiver), or the channel statistics only (non-coherent receiver). Our results show that if the available bandwidth is smaller than a threshold bandwidth which is proportional (up to leading order terms) to the square root of the number of antennas, there is no gap between the coherent capacity and the non-coherent capacity in terms of capacity scaling behavior. On the other hand, when the bandwidth is larger than this threshold, there is a capacity scaling gap. Since achievable rates using pilot symbols for channel estimation are subject to the non-coherent capacity bound, this work reveals that pilot-assisted coherent receivers in systems with a large number of receive antennas are unable to exploit excess spectrum above a given threshold for capacity gain.

The availability of very wide spectrum in millimeter wave bands combined with large antenna arrays and ultra-dense networks raises two basic questions: What is the true value of overly abundant degrees of freedom and how can networks be designed to fully exploit them? This paper determines the capacity scaling of large cellular networks as a function of bandwidth, area, number of antennas, and base station density. It is found that the network capacity has a fundamental bandwidth scaling limit, beyond which the network becomes power-limited. An infrastructure multi-hop protocol achieves the optimal network capacity scaling for all network parameters. In contrast, current protocols that use only single-hop direct transmissions cannot achieve the capacity scaling in wideband regimes except in the special case when the density of base stations is taken to impractical extremes. This finding suggests that multi-hop communication will be important to fully realize the potential of next-generation cellular networks. Dedicated relays, if sufficiently dense, can also perform this task, relieving user nodes from the battery drain of cooperation. On the other hand, more sophisticated strategies such as hierarchical cooperation, that are essential for achieving capacity scaling in ad hoc networks, are unnecessary in the cellular context.

In this paper, we study the achievable rate and the energy efficiency of analog, hybrid, and digital combining (AC, HC, and DC) for millimeter wave (mmW) receivers. We take into account the power consumption of all receiver components, not just analog-to-digital converters (ADCs), determine some practical limitations of beamforming in each architecture, and develop performance analysis charts that enable comparison of different receivers simultaneously in terms of two metrics, namely, spectral efficiency (SE) and energy efficiency (EE). We present a multi-objective utility optimization interpretation to find the best SE-EE weighted tradeoff among AC, DC, and HC schemes. We consider an additive quantization noise model to evaluate the achievable rates with low resolution ADCs. Our analysis shows that AC is only advantageous if the channel rank is strictly one, the link has very low SNR, or there is a very stringent low power constraint at the receiver. Otherwise, we show that the usual claim that DC requires the highest power is not universally valid. Rather, either DC or HC alternatively results in the better SE versus EE tradeoff depending strongly on the considered power consumption characteristic values for each component of the mmW receiver.

In non-coherent wideband fading channels, where energy rather than spectrum is the limiting resource, peaky and non-peaky signaling schemes have long been considered species apart, as the first approaches asymptotically the capacity of a wideband AWGN channel with the same average SNR, whereas the second reaches a peak rate at some finite critical bandwidth and then falls to zero as bandwidth grows to infinity. In this paper, it is shown that this distinction is in fact an artifact of the limited attention paid in the past to the product between the bandwidth and the fraction of time it is in use. This fundamental quantity, called bandwidth occupancy, measures average bandwidth usage over time. For all signaling schemes with the same bandwidth occupancy, achievable rates approach to the wideband AWGN capacity within the same gap as the bandwidth occupancy approaches its critical value, and decrease to zero as the occupancy goes to infinity. This unified analysis produces quantitative closed-form expressions for the ideal bandwidth occupancy, recovers the existing capacity results for (non-) peaky signaling schemes, and unveils a tradeoff between the accuracy of approximating capacity with a generalized Taylor polynomial and the accuracy with which the optimal bandwidth occupancy can be bounded.

Peaky and non-peaky signaling schemes have long been considered species apart in non-coherent wideband fading channels, as the first approaches asymptotically the linear-in-power capacity of a wideband AWGN channel with the same SNR, whereas the second reaches a nearly power-limited peak rate at some finite critical bandwidth and then falls to zero as bandwidth grows to infinity. In this paper it is shown that this distinction is in fact an artifact of the limited attention paid in the past to the product between the bandwidth and the fraction of time it is in use. This fundamental quantity, that is termed bandwidth occupancy, measures average bandwidth usage over time. The two types of signaling in the literature are harmonized to show that, for any type of signals, there is a fundamental limit-a critical bandwidth occupancy. All signaling schemes with the same bandwidth occupancy approach the capacity of wideband AWGN channels with the same asymptotic behavior as the bandwidth occupancy grows to its critical value. For a bandwidth occupancy above the critical, rate decreases to zero as the bandwidth occupancy goes to infinity.

This paper studies noncoherent wideband systems with a single antenna transmitter and a multiple antenna receiver with many elements, under signaling with peak-to-average power ratio constraints. The analysis considers the scaling behavior of capacity and achievable rates by letting both the number of antennas and the bandwidth go to infinity jointly. In contrast to prior work on wideband single input single output (SISO) channels without a-priori channel state information, it is shown that a sufficiently large number of receive antennas can make up for the vanishingly small SNR at each antenna. In particular, it is shown that when bandwidth grows sufficiently slowly with the number of antennas, the capacity scaling with an increasing number of receive antennas is the same as the optimal coherent capacity scaling. If the bandwidth grows faster than a certain threshold, however, the additional bandwidth does not help because a finite transmit power is spread over an excessively large bandwidth.

With the shortage of spectrum in conventional cellular frequencies, millimeter-wave (mmWave) bands are being widely considered for use in next-generation networks. Multihop relaying is likely to play a significant role in mmWave cellular systems for self backhauling, range extension and improved robustness from path diversity. However, designing scheduling policies for these systems is challenging due to the need to account for both adaptive directional transmissions and dynamic time-division duplexing schedules, which are key enabling features of mmWave systems. This paper considers the problem of joint scheduling and congestion control in a multihop mmWave network using a Network Utility Maximization (NUM) framework. Interference is modeled with an exact model and two auxiliar simplified models: actual interference (AI), with a graph-based calculation of the Signal to Interference plus Noise Ratio (SINR) depending on dynamic link activity and directivity, as well as upper and lower bounds computed from worst-case interference (WI) and interference free (IF) approximations. Throughput and utility optimal policies are derived for all interference models (AI, WI and IF) with both deterministic Maximum Weighted and randomized Pick and Compare scheduling algorithms, jointly with decentralized Dual Congestion Control. Results are evaluated with numerical simulations, using accurate mmWave channel and beamforming gain approximations based on measurement campaigns.

In this article we propose solutions to diverse conflicts that result from the deployment of the (still immature) relay node (RN) technology in LTE-A networks. These conflicts and their possible solutions have been observed by implementing standard-compliant relay functionalities on the Vienna simulator. As an original experimental approach, we model realistic RN operation, taking into account that transmitters are not active all the time due to half-duplex RN operation. We have rearranged existing elements in the simulator in a manner that emulates RN behavior, rather than implementing a standalone brand-new component for the simulator. We also study analytically some of the issues observed in the interaction between the network and the RNs, to draw conclusions beyond simulation observation. The main observations of this paper are that: i) Additional time-varying interference management steps are needed, because the LTE-A standard employs a fixed time division between eNB-RN and RN-UE transmissions (typical relay capacity or throughput research models balance them optimally, which is unrealistic nowadays); ii) There is a trade-off between the time-division constraints of relaying and multi-user diversity; the stricter the constraints on relay scheduling are, the less flexibility schedulers have to exploit channel variation; and iii) Thee standard contains a variety of parameters for relaying configuration, but not all cases of interest are covered.

With millimeter wave bands emerging as a strong candidate for 5G cellular networks, next-generation systems may be in a unique position where spectrum is plentiful. To assess the potential value of this spectrum, this paper derives scaling laws on the per mobile downlink feasible rate with large bandwidth and number of nodes, for both Infrastructure Single Hop (ISH) and Infrastructure Multi-Hop (IMH) architectures. It is shown that, for both cases, there exist critical bandwidth scalings above which increasing the bandwidth no longer increases the feasible rate per node. These critical thresholds coincide exactly with the bandwidths where, for each architecture, the network transitions from being degrees-of-freedom-limited to power-limited. For ISH, this critical bandwidth threshold is lower than IMH when the number of users per base station grows with network size. This result suggests that multi-hop transmissions may be necessary to fully exploit large bandwidth degrees of freedom in deployments with growing number of users per cell.

This paper studies mutual information in a novel scenario combining cooperative diversity and cognitive radio based on spectrum leasing. In the scenario there is a primary transmitter subject to random channel fading, with full spectrum rights available, and a secondary transmitter without any spectrum rights, which offers its cooperation to the primary transmitter in exchange for a share of the resulting resource gains. Two decision-making schemes, based on different levels of channel knowledge, are considered in the primary transmitter. These are knowledge of the statistics of random fading (averages) and full knowledge of instantaneous channel state. The contributions of this paper are the radio leasing scenario itself, which, unlike previous approaches in cognitive radio, is not based on game theory, and the statistical characterization of the resource gains achieved in this scenario using cooperative diversity for spectrum leasing under diverse channel conditions and the aforementioned decision-making schemes. Analytical expressions are obtained for the probability of cooperation, the mutual information probability density function and its average, and the proportion of resource gains achieved for the statistical and instantaneous channel knowledge schemes. We identify the conditions for resource gains: for statistical channel knowledge to suffice, the primary link must be of low quality, whereas for instantaneous channel knowledge, although resource gains are achieved in any situation, they increase as the primary channel gets worse.