Ultra-Reliable Short-Packet Communications: Fundamental Limits and Enabling Technologies

The paradigm shift from 4G to 5G communications, anticipated to enable ultra-reliable low-latency communications (URLLC), will enforce a radical change in the design of wireless communication systems. Unlike in 4G systems, where the main objective is to provide a large transmission rate, in URLLC, as implied by its name, the objective is to enable transmissions with low latency and, simultaneously, very high reliability. Since low latency implies the use of short data packets, the tension between blocklength and reliability is studied in URLLC.Several key enablers for URLLC communications have been designated in the literature. Of special importance are diversity-enabling technologies such as multiantenna systems and feedback protocols. Furthermore, it is not only important to introduce additional diversity by means of the above examples, one must also guarantee that thescarce number of channel uses are used in an optimal way. Therefore, it is imperative to develop design guidelines for how to enable reliable detection of incoming data, how to acquire channel-state information, and how to construct efficient short-packet channel codes. The development of such guidelines is at the heart of this thesis. This thesis focuses on the fundamental performance of URLLC-enabling technologies. Specifically, we provide converse (upper) bounds and achievability (lower) bounds on the maximum coding rate, based on finite-blocklength information theory, for systems that employ the key enablers outlined above. With focus on the wireless channel, modeled via a block-fading assumption, we are able to provide answers to questions like: howto optimally utilize spatial and frequency diversity, how far from optimal short-packet channel codes perform, how multiantenna systems should be designed to serve a given number of users, and how to design feedback schemes when the feedback link is noisy. In particular, this thesis is comprised out of four papers. In Paper A, we study the short-packet performance over the Rician block-fading channel. In particular, we present achievability bounds for pilot-assisted transmission with several different decoders that allow us to quantify the impact, on the achievable performance, of imposed pilots and mismatched decoding. Furthermore, we design short-packet channel codes that perform within 1 dB of our achievability bounds. Paper B studies multiuser massive multiple-input multiple-output systems with short packets. We provide an achievability bound on the average error probability over quasistatic spatially correlated Rayleigh-fading channels. The bound applies to arbitrary multiuser settings, pilot-assisted transmission, and mismatched decoding. This makes it suitable to assess the performance in the uplink/downlink for arbitrary linear signal processing. We show that several lessons learned from infinite-blocklength analyses carry over to the finite-blocklength regime. Furthermore, for the multicell setting with randomly placed users, pilot contamination should be avoided at all cost and minimum mean-squared error signal processing should be used to comply with the stringent requirements of URLLC.In Paper C, we consider sporadic transmissions where the task of the receiver is to both detect and decode an incoming packet. Two novel achievability bounds, and a novel converse bound are presented for joint detection-decoding strategies. It is shown that errors associated with detection deteriorates performance significantly for very short packet sizes. Numerical results also indicate that separate detection-decoding strategies are strictly suboptimal over block-fading channels.Finally, in Paper D, variable-length codes with noisy stop-feedback are studied via a novel achievability bound on the average service time and the average error probability. We use the bound to shed light on the resource allocation problem between the forward and the feedback channel. For URLLC applications, it is shown that enough resources must be assigned to the feedback link such that a NACK-to-ACK error becomes rarer than the target error probability. Furthermore, we illustrate that the variable-length stop-feedback scheme outperforms state-of-the-art fixed-length no-feedback bounds even when the stop-feedback bit is noisy

Joint Pilot and Payload Power Allocation for Massive-MIMO-enabled URLLC IIoT Networks

The Fourth Industrial Revolution (Industrial 4.0) is coming, and this revolution will fundamentally enhance the way the factories manufacture products. The conventional wired lines connecting central controller to robots or actuators will be replaced by wireless communication networks due to its low cost of maintenance and high deployment flexibility. However, some critical industrial applications require ultra-high reliability and low latency communication (URLLC). In this paper, we advocate the adoption of massive multiple-input multiple output (MIMO) to support the wireless transmission for industrial applications as it can provide deterministic communications similar as wired lines thanks to its channel hardening effects. To reduce the latency, the channel blocklength for packet transmission is finite, and suffers from transmission rate degradation and decoding error probability. Thus, conventional resource allocation for massive MIMO transmission based on Shannon capacity assuming the infinite channel blocklength is no longer optimal. We first derive the closed-form expression of lower bound (LB) of achievable uplink data rate for massive MIMO system with imperfect channel state information (CSI) for both maximum-ratio combining (MRC) and zero-forcing (ZF) receivers. Then, we propose novel low-complexity algorithms to solve the achievable data rate maximization problems by jointly optimizing the pilot and payload transmission power for both MRC and ZF. Simulation results confirm the rapid convergence speed and performance advantage over the existing benchmark algorithms.Comment: Accepted in IEEE JSAC with special issue on Industry 4.0. Keywords: URLLC, Industrial 4.0, Industrial Internet-of-Things (IIoT), Massive MIM

URLLC with Massive MIMO: Analysis and Design at Finite Blocklength

The fast adoption of Massive MIMO for high-throughput communications was enabled by many research contributions mostly relying on infinite-blocklength information-theoretic bounds. This makes it hard to assess the suitability of Massive MIMO for ultra-reliable low-latency communications (URLLC) operating with short blocklength codes. This paper provides a rigorous framework for the characterization and numerical evaluation (using the saddlepoint approximation) of the error probability achievable in the uplink and downlink of Massive MIMO at finite blocklength. The framework encompasses imperfect channel state information, pilot contamination, spatially correlated channels, and arbitrary linear spatial processing. In line with previous results based on infinite-blocklength bounds, we prove that, with minimum mean-square error (MMSE) processing and spatially correlated channels, the error probability at finite blocklength goes to zero as the number $M$ of antennas grows to infinity, even under pilot contamination. On the other hand, numerical results for a practical URLLC network setup involving a base station with $M=100$ antennas, show that a target error probability of $10^{-5}$ can be achieved with MMSE processing, uniformly over each cell, only if orthogonal pilot sequences are assigned to all the users in the network. Maximum ratio processing does not suffice.Comment: 30 pages, 5 figure

Resource Allocation for Uplink Cell-Free Massive MIMO enabled URLLC in a Smart Factory

Smart factories need to support the simultaneous communication of multiple industrial Internet-of-Things (IIoT) devices with ultra-reliability and low-latency communication (URLLC). Meanwhile, short packet transmission for IIoT applications incurs performance loss compared to traditional long packet transmission for human-to-human communications. On the other hand, cell-free massive multiple-input and multiple-output (CF mMIMO) technology can provide uniform services for all devices by deploying distributed access points (APs). In this paper, we adopt CF mMIMO to support URLLC in a smart factory. Specifically, we first derive the lower bound (LB) on achievable uplink data rate under the finite blocklength (FBL) with imperfect channel state information (CSI) for both maximum-ratio combining (MRC) and full-pilot zero-forcing (FZF) decoders. \textcolor{black}{The derived LB rates based on the MRC case have the same trends as the ergodic rate, while LB rates using the FZF decoder tightly match the ergodic rates}, which means that resource allocation can be performed based on the LB data rate rather the exact ergodic data rate under FBL. The \textcolor{black}{log-function method} and successive convex approximation (SCA) are then used to approximately transform the non-convex weighted sum rate problem into a series of geometric program (GP) problems, and an iterative algorithm is proposed to jointly optimize the pilot and payload power allocation. Simulation results demonstrate that CF mMIMO significantly improves the average weighted sum rate (AWSR) compared to centralized mMIMO. An interesting observation is that increasing the number of devices improves the AWSR for CF mMIMO whilst the AWSR remains relatively constant for centralized mMIMO.Comment: Accepted by Transactions on Communication

URLLC with Massive MIMO: Analysis and Design at Finite Blocklength

The fast adoption of Massive MIMO for high-throughput communications was enabled by many research contributions mostly relying on infinite-blocklength information-theoretic bounds. This makes it hard to assess the suitability of Massive MIMO for ultra-reliable low-latency communications (URLLC) operating with short-blocklength codes. This paper provides a rigorous framework for the characterization and numerical evaluation (using the saddlepoint approximation) of the error probability achievable in the uplink and downlink of Massive MIMO at finite blocklength. The framework encompasses imperfect channel state information, pilot contamination, spatially correlated channels, and arbitrary linear spatial processing. In line with previous results based on infinite-blocklength bounds, we prove that, with minimum mean-square error (MMSE) processing and spatially correlated channels, the error probability at finite blocklength goes to zero as the number M of antennas grows to infinity, even under pilot contamination. However, numerical results for a practical URLLC network setup involving a base station with M-100 antennas, show that a target error probability of 10^¿5 can be achieved with MMSE processing, uniformly over each cell, only if orthogonal pilot sequences are assigned to all the users in the network. Maximum ratio processing does not suffice.The work of Johan Östman, Alejandro Lancho, and Giuseppe Durisi was supported in part by the Swedish Research Council under grant 2016-03293 and in part by the Wallenberg AI, Autonomous Systems, and Software Program. The work of Luca Sanguinetti was supported in part by the Italian Ministry of Education and Research (MIUR) in the framework of the CrossLab Project (Departments of Excellence)

High reliability downlink MU-MIMO with new encoded OSTBC approach and superposition modulated side information

Abstract. The promise of Fifth Generation Mobile Network (5G) heralded 5G-era with apparently unlimited potential outcomes. It resulted in the emergence of new paradigms of thought, better approaches to lead business, new innovative solutions, services and products, and is expected to transform the world as we know it. With the advent of some of those new technologies and use cases which deviate from the traditional human-centric, delay tolerant applications, the need for Ultra-Reliable Low-Latency Communications (URLLC) in the 5G wireless network has become indispensable. In this thesis we investigate how to improve the reliability of a downlink multiuser (MU) MIMO transmission scheme with the use of a new approach of orthogonal space time block codes (OSTBC) and network coding with superposition modulated system and side information. The main advantage here is that we show multiple users can be accommodated with the same resource. This is quite useful in a wireless system where resources are always restricted. This therefore is a combination of two techniques to further enhance reliability. Orthogonality is useful in terms of resolving different signals from multiple antennas in a reduced complexity configuration. Superposition modulation with side information is important as it facilitates the recovery of symbols while still keeping the energy normalized. Thus we carried out a detailed analysis with the new OSTBC approach. It is shown that the performance of a multiuser (MU) MIMO system can be improved significantly in terms of bit, block and frame error rates (BER, BLER and FER) as reliability measures. By accommodating a reasonable number of multiple users, high reliability is achieved at the expense of bringing down the rate. To compensate for the low rate, conventional OSTBC is considered as well, where, as a penalty to pay, multiple orthogonal resources are required

Robust MIMO Detection With Imperfect CSI: A Neural Network Solution

In this paper, we investigate the design of statistically robust detectors for multi-input multi-output (MIMO) systems subject to imperfect channel state information (CSI). A robust maximum likelihood (ML) detection problem is formulated by taking into consideration the CSI uncertainties caused by both the channel estimation error and the channel variation. To address the challenging discrete optimization problem, we propose an efficient alternating direction method of multipliers (ADMM)-based algorithm, which only requires calculating closed-form solutions in each iteration. Furthermore, a robust detection network RADMMNet is constructed by unfolding the ADMM iterations and employing both model-driven and data-driven philosophies. Moreover, in order to relieve the computational burden, a low-complexity ADMM-based robust detector is developed using the Gaussian approximation, and the corresponding deep unfolding network LCRADMMNet is further established. On the other hand, we also provide a novel robust data-aided Kalman filter (RDAKF)-based channel tracking method, which can effectively refine the CSI accuracy and improve the performance of the proposed robust detectors. Simulation results validate the significant performance advantages of the proposed robust detection networks over the non-robust detectors with different CSI acquisition methods.Comment: 15 pages, 8 figures, 2 tables; Accepted by IEEE TCO

Reliability performance analysis of half-duplex and full-duplex schemes with self-energy recycling

Abstract. Radio frequency energy harvesting (EH) has emerged as a promising option for improving the energy efficiency of current and future networks. Self-energy recycling (sER), as a variant of EH, has also appeared as a suitable alternative that allows to reuse part of the transmitted energy via an energy loop. In this work we study the benefits of using sER in terms of reliability improvements and compare the performance of full-duplex (FD) and half-duplex (HD) schemes when using multi-antenna techniques at the base station side. We also assume a model for the hardware energy consumption, making the analysis more realistic since most works only consider the energy spent on transmission. In addition to spectral efficiency enhancements, results show that FD performs better than HD in terms of reliability. We maximize the outage probability of the worst link in the network using a dynamic FD scheme where a small base station (SBS) determines the optimal number of antennas for transmission and reception. This scheme proves to be more efficient than classical HD and FD modes. Results show that the use of sER at the SBS introduces changes on the distribution of antennas for maximum fairness when compared to the setup without sER. Moreover, we determine the minimum number of active radio frequency chains required at the SBS in order to achieve a given reliability target