In this article, we study the problem of latency and reliability trade-off in ultra-reliable low-latency communication (URLLC) in the presence of decoding complexity constraints. We consider linear block encoded codewords transmitted over a binary-input AWGN channel and decoded with order-statistic (OS) decoder. We first investigate the performance of OS decoders as a function of decoding complexity and propose an empirical model that accurately quantifies the corresponding trade-off. Next, a consistent way to compute the aggregate latency for complexity constrained receivers is presented, where the latency due to decoding is also included. It is shown that, with strict latency requirements, decoding latency cannot be neglected in complexity constrained receivers. Next, based on the proposed model, several optimization problems, relevant to the design of URLLC systems, are introduced and solved. It is shown that the decoding time has a drastic effect on the design of URLLC systems when constraints on decoding complexity are considered. Finally, it is also illustrated that the proposed model can closely describe the performance versus complexity trade-off for other candidate coding solutions for URLLC such as tail-biting convolutional codes, polar codes, and low-density parity-check codes.

The problem of communication in Rayleigh fading channels with estimated channel state information at the receiver (CSIR) is investigated. Based on a related hypothesis testing problem in the Neyman-Pearson formulation, a non-asymptotic- in the codeword block-length-converse on the maximal coding rate is derived. The bound summarizes succinctly the effect of various system parameters that include the length of channel coherence interval, the length of the training and data intervals and the power allocated to training and data transmission. The bound is also studied in the asymptotic-in the codeword blocklength-regime and a particularly simple, non-trivial upper bound on the ergodic capacity of Raleigh fading channels with estimated CSIR is obtained. Finally, a second-order asymptotic expansion of the non-asymptotic converse is provided, which can be very useful in the study of latency-constrained communication systems.

The phenomenon of pilot contamination (PC) in multi-cell Massive MIMO systems is investigated in the presence of imperfect timing synchronization (TS). In particular, a basic setup is considered, where a base station (BS) is perfectly synchronized with the user of its cell, but there is imperfect TS between the BS and the user in another cell, possibly due to different propagation distances. A discrete-time system model is derived based on the continuous-time system model. The discrete-time system model accurately captures the phenomenon of imperfect TS in terms of the timing mismatch and the pulse shaping filter impulse responses. The derived discrete-time system model is used to study the achievable rates of a two-cell Massive MIMO uplink. It is shown that the structure imposed to the pilot contaminating signal due to the imperfect TS can be leveraged to mitigate the effect of PC. The level of PC suppression is quantified as a function of the timing mismatch and the characteristics of the transmit/receive pulse shaping filters.

The problem of maximum likelihood (ML) detection in training-assisted single-input multiple-output (SIMO) systems with phase noise impairments is studied for two different scenarios, i.e., the case when the channel is deterministic and known (constant channel) and the case when the channel is stochastic and unknown (fading channel). Furthermore, two different operations with respect to the phase noise sources are considered, namely, the case of identical phase noise sources and the case of independent phase noise sources over the antennas. In all scenarios, the optimal detector is derived for a very general parameterization of the phase noise distribution. Furthermore, a high signal-to-noise-ratio (SNR) analysis is performed to show that symbol-error-rate (SER) floors appear in all cases. The SER floor in the case of identical phase noise sources (for both constant and fading channels) is independent of the number of antenna elements. In contrast, the SER floor in the case of independent phase noise sources is reduced when increasing the number of antenna elements (for both constant and fading channels). Finally, the system model is extended to multiple data channel uses and it is shown that the conclusion is valid for these setups, as well.

In this paper, the problem of optimal maximum likelihood detection in a single user single-input multiple-output (SIMO) channel with phase noise at the receiver is considered. The optimal detection rules under training are derived for two operation modes, namely when the phase increments are fully correlated among the M receiver antennas (synchronous operation) and when they are independent (non-synchronous operation). The phase noise increments are parameterized by a very general distribution, which includes the Wiener phase noise model as a special case. It is proven that phase noise creates a symbol-error-rate (SER) floor for both operation modes. In the synchronous operation this error floor is independent of M, while it goes to zero exponentially with M in the non-synchronous operation.

Multiuser multiple-input-multiple-output (MIMO) cellular systems with an excess of base station (BS) antennas (Massive MIMO) offer unprecedented multiplexing gains and radiated energy efficiency. Oscillator phase noise is introduced in the transmitter and receiver radio frequency chains and severely degrades the performance of communication systems. We study the effect of oscillator phase noise in frequency-selective Massive MIMO systems with imperfect channel state information. In particular, we consider two distinct operation modes, namely, when the phase noise processes at the M BS antennas are identical (synchronous operation) and when they are independent (nonsynchronous operation) . We analyze a linear and low-complexity time-reversal maximum-ratio combining reception strategy. For both operation modes, we derive a lower bound on the sum-capacity, and we compare their performance. Based on the derived achievable sum-rates, we show that with the proposed receive processing, an O(√M) array gain is achievable. Due to the phase noise drift, the estimated effective channel becomes progressively outdated. Therefore, phase noise effectively limits the length of the interval used for data transmission and the number of scheduled users. The derived achievable rates provide insights into the optimum choice of the data interval length and the number of scheduled users.

The presence of line-of-sight (LoS) components is typically considered as a hindrance for multiple-input multiple-output (MIMO) communications due to the limited amount of multipath scattering which, in turn, results in low spatial multiplexing gains. However, some recent investigations have questioned this common belief and demonstrated that by employing specifically designed antenna arrays at both the transmitter (Tx) and receiver (Rx), the mean channel matrix can become full-rank and, consequently, we can obtain high channel capacities even at high Ricean K-factors. In this paper, using the joint ordered eigenvalue probability density function (PDF) as a starting point, we derive analytical exact and asymptotic expressions for the mutual information (MI) statistics of these optimized LoS MIMO configurations. The proposed analytical formulae are given in a tractable determinant form and thus can be easily evaluated and efficiently programmed. The implications of the model parameters on MI statistics are also assessed with the match between the analytical curves and Monte-Carlo simulations being excellent.