This work analyzes the joint influence of channel fading and the data outsourcing process in the QoS metrics of a wireless system. As a first contribution, expressions of the channel effective bandwidth function (also known as effective capacity) for time-correlated Rayleigh fading under different adaptive rate policies are obtained. This result allows us to analytically evaluate the maximum constant information rate that can be transmitted over the channel under a probabilistic delay constraint. Later, this Capacity with Probabilistic Delay Constraint C_D^t, _ε is generalized for systems with non-constant sources and simple closed-form expressions able to capture the influence of source processes in the probability of over-delay are given. Figures on how much the maximum allowable rate decreases for shorter allowable delays or for more changing rate sources are shown and the expected delay violation is compared to simulations in order to validate our results.

LTE V2X is the response of the 3GPP standardization body to the high market expectations related to vehicular communications for safety and infotainment services. To fulfill the stringent requirements in terms of reliability associated with safety applications, geo-location based access (GLOC) has been proposed for direct Vehicle-to-Vehicle (V2V) communication. Such a scheme aims at maximizing the distance of co-channel transmitters (i.e. transmitter that use the same resources) while preserving a low latency when accessing the resources and a low overhead. In this paper we analyze, with the aid of stochastic geometry, the delivery of periodic and non-periodic broadcast messages with GLOC, taking into account path loss and fading as well as the random locations of transmitting vehicles. Analytical results include the average interference, average Binary Rate (BR), capture probability, i.e., the probability of successful message transmission, and Energy Efficiency (EE). Mathematical analysis reveals interesting insights about the system performance, which are validated thought extensive Monte Carlo simulations. In particular, it is shown that the capture probability is an increasing function with exponential dependence with respect to the transmit power and it is demonstrated that an arbitrary high capture probability can be achieved, as long as the number of access resources is high enough. Finally, to facilitate the system-level design of GLOC, it is obtained the optimum transmit power, which fulfill a given minimum capture probability constraint while maximizing the EE of the system.

With the speeding up of the fifth generation (5G) new radio (NR) worldwide commercialization, one of the paramount questions for operators and vendors is how to optimize the radio links, considering the widely diverse scenarios envisioned. One of the key pillars of 5G has been an unprecedented flexibility on the configuration of the radio access network (RAN) on scenarios that include cellular, vehicular, and industrial networks among others. This flexibility has its main exponent on link adaptation (LA), which has evolved into a multi-domain technique where a plethora of parameters, like numerology, bandwidth part, radio frequency beam, power, modulation and coding scheme (MCS) or multiple antenna precoding can be adapted to the instantaneous link conditions. Although such enhancements open the door to a significant performance improvement, they also pose many challenges to LA optimization. In this article, we first present the signaling aspects of NR technology for multi-domain LA and the challenges that need to be faced. Then, we explore the latest advances on LA for wireless networks. We envision a combination of machine learning (ML) tools with multi-domain LA as a key enabler for 5G and beyond networks. Finally, we investigate emerging ML approaches for LA and present a promising application of ML for LA that is assessed with simulations. With this scheme, the training is performed at the network side to relieve the user equipment (UE) to do such a complex task. It is shown with simulations that our ML approach outperforms the well-known outer loop link adaptation (OLLA) algorithm in terms of instantaneous block error rate (BLER), while reaching the same average spectral efficiency (SE). Interestingly, it is shown that the proposed scheme only requires 4 bits to represent the features used to train the model, which makes it suitable for implementation in real systems with limited feedback.

In this paper, we present an analytical study of the bit error rate (BER) for single-carrier frequency-division multiple access (SC-FDMA) transmission over frequency-selective fading channels when zero-forcing frequency-domain equalization is applied. SC-FDMA, which can be described as a precoded version of orthogonal frequency-division multiple access (OFDMA), is regarded as a promising candidate for next mobile communication systems due its favorable envelope characteristics and low peak-to-average-power ratio (PAPR), compared with that of OFDMA. We focus on Nakagami-m fading channels and provide a method to calculate BER values with a single numerical computation. We provide a closed-form expression for the BER with binary phase-shift keying (BPSK) and square M-ary quadrature amplitude modulation (M-QAM) under the assumption of independence among channel frequency responses for allocated subcarriers.