It is shown that, particularly for terrestrial cellular telephony, the interference-suppression feature of CDMA (code division multiple access) can result in a many-fold increase in capacity over analog and even over competing digital techniques. A single-cell system, such as a hubbed satellite network, is addressed, and the basic expression for capacity is developed. The corresponding expressions for a multiple-cell system are derived. and the distribution on the number of users supportable per cell is determined. It is concluded that properly augmented and power-controlled multiple-cell CDMA promises a quantum increase in current cellular capacity. >

On the capacity of a cellular CDMA system

To study the operational behaviour of λ-terms, we will use the denotational (mathematical) approach. A denotational semantics for a language is based on the choice of a space of semantics values, or denotations, where terms are to be interpreted. Choosing a space with nice mathematical properties can help in proving the semantic properties of terms, since to this aim standard mathematical techniques can be used.

λ Δ -Models

RSSI is known to be a fickle indicator of whether a wireless link will work, for many reasons. This greatly complicates operation because it requires testing and adaptation to find the best rate, transmit power or other parameter that is tuned to boost performance. We show that, for the first time, wireless packet delivery can be accurately predicted for commodity 802.11 NICs from only the channel measurements that they provide. Our model uses 802.11n Channel State Information measurements as input to an OFDM receiver model we develop by using the concept of effective SNR. It is simple, easy to deploy, broadly useful, and accurate. It makes packet delivery predictions for 802.11a/g SISO rates and 802.11n MIMO rates, plus choices of transmit power and antennas. We report testbed experiments that show narrow transition regions (

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Predictable 802.11 packet delivery from wireless channel measurements

Space-Time Block Coding for Wireless Communications

In studying the performance of coded communications over memoryless channels (with or without fading), the results are given as upper bounds on the average bit error probability (BEP). In principle, there are three different approaches to arriving at these bounds, all of which employ obtaining the so-called pairwise error probability , or the probability of choosing one symbol sequence over another for a given pair of possible transmitted symbol sequences, followed by a weighted summation over all pairwise events. In this chapter, we will focus on the results obtained from the third approach since these provide the tightest upper bounds on the true performance. The first emphasis will be placed on evaluating the pairwise error probability with and without CSI, following which we shall discuss how the results of these evaluations can be used via the transfer bound approach to evaluate average BEP of coded modulation transmitted over the fading channel.

Coded Communication over Fading Channels

Network densification, massive multiple-input multiple-output (MIMO), and millimeter-wave (mmWave) bands have recently emerged as some of the physical layer enablers for the future generations of wireless communication networks (5G and beyond). Grounded on prior work on sub-6-GHz cell-free massive MIMO architectures, a novel framework for cell-free mmWave massive MIMO systems is introduced that considers the use of low-complexity hybrid precoders/decoders while factors in the impact of using capacity-constrained fronthaul links. A suboptimal pilot allocation strategy is proposed that is grounded on the idea of clustering by dissimilarity. Furthermore, based on mathematically tractable expressions for the per-user achievable rates and the fronthaul capacity consumption, max-min power allocation and fronthaul quantization optimization algorithms are proposed that, combining the use of block coordinate descent methods with sequential linear optimization programs, ensure a uniformly good quality of service over the whole coverage area of the network. The simulation results show that the proposed pilot allocation strategy eludes the computational burden of the optimal small-scale CSI-based scheme while clearly outperforming the classical random pilot allocation approaches. Moreover, they also reveal the various existing trade-offs among the achievable max-min per-user rate, the fronthaul requirements, and the optimal hardware complexity (i.e., the number of antennas and the number of RF chains).

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Cell-Free Millimeter-Wave Massive MIMO Systems With Limited Fronthaul Capacity

This paper presents the evaluation of the average bit error rate (BER) performance of linear space-time block codes (STBC) from orthogonal designs over correlated identically distributed Nakagami-m fading channels. Starting from the moment-generating function (MGF) of the multipath component signals at the antenna array elements, analytical expressions of the BER performance for both integral and nonintegral Nakagami-m fading parameters are derived. Closed-form expressions of the spatial cross-correlation function for mobile nonfrequency selective Nakagami-m fading multiple-input-multiple-output (MIMO) channels are obtained, which are valid for small angle-of-arrival (AOA) spread. In this expressions, various parameters of interest, such as the mean AOA of the signal, AOA spread, and array configurations, are all taken into account. The effects of antenna array configuration and the operating environment (mean AOA, AOA spread, Nakagami fading parameter) on the BER performance of the system are illustrated by several numerical examples.

BER performance of linear STBC from orthogonal designs over MIMO correlated Nakagami-m fading channels

To provide heterogeneous quality-of-service (QoS) guarantees to applications, most wireless communications standards combine the error-correcting capability of hybrid automatic repeat request (HARQ) protocols at the data link control layer with the adaptation ability of adaptive modulation and coding (AMC) strategies at the physical layer. In this paper, a novel cross-layer multidimensional discrete-time Markov chain (DTMC)-based queuing model is developed to jointly exploit the capabilities of HARQ and AMC. The analytical DTMC-based model, which generalizes and extends previous results on this topic, stems from a comprehensive consideration of packet multimedia traffic sources modeled as discrete-batch Markovian arrival processes, finite queue-length systems, truncated HARQ protocols, AMC strategies, and a wireless channel first-order 2-D Markov model that relies on the amplitude and rate of change of the fading envelope. Based on the stationary state probability distribution of this multidimensional DTMC, closed-form analytical expressions for performance metrics such as throughput, average packet delay, and packet loss rate, which were caused either by buffer overflow or by exceeding the maximum number of allowed retransmissions, are derived. Furthermore, the proposed analytical framework is used to formulate multidimensional and simplified 2-D constrained optimization problems aiming at maximizing the system throughput under prescribed QoS constraints. Computer simulation results are carried out to verify the validity of the proposed analytical model and to quantify the performance gain due to cross-layer optimization and the use of truncated HARQ protocols.

Cross-Layer Design of Adaptive Multirate Wireless Networks Using Truncated HARQ

Cell-free massive multiple-input multiple-output (MIMO) is a novel beyond 5G (B5G) and 6G paradigm that, through the use of a common central processing unit (CPU), coordinates a large number of distributed access points (APs) to coherently serve mobile stations (MSs) on the same time/frequency resource. By exploiting the characteristics of new less-congested millimeter wave (mmWave) frequency bands, these networks can improve the overall system spectral and energy efficiencies by using low-complexity hybrid precoders/decoders. For this purpose, the system must be correctly dimensioned to provide the required quality of service (QoS) to MSs under different traffic load conditions. However, only heavy traffic load conditions are usually taken into account when analysing these networks and, thus, many APs might be underutilized during low traffic load periods, leading to an inefficient use of resources and waste of energy. Aiming at the implementation of energy-efficient AP switch on/off strategies, several approaches have been proposed in the literature that only consider rather unrealistic uniform spatial traffic distribution in the whole coverage area. Unlike prior works, this paper proposes energy efficient AP sleep-mode techniques for cell-free mmWave massive MIMO networks that are able to capture the inhomogeneous nature of spatial traffic distribution in realistic wireless networks. The proposed framework considers, analyzes and compares different AP switch ON-OFF (ASO) strategies that, based on the use of goodness-of-fit (GoF) tests, are specifically designed to dynamically turn on/off APs to adapt to both the number and the statistical distribution of MSs in the network. Numerical results show that the use of properly designed GoF-based ASO strategies under a non-uniform spatial traffic distribution can serve to considerably improve the achievable energy efficiency.

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Energy-Efficient Access-Point Sleep-Mode Techniques for Cell-Free mmWave Massive MIMO Networks With Non-Uniform Spatial Traffic Density

The combination of user-centric network densification and distributed massive multiple-input multiple-output (MIMO) operation has recently brought along a new paradigm in the wireless communications arena, referred to as cell-free massive MIMO networking. In these networks, a large number of distributed access points (APs), coordinated by a central processing unit (CPU), cooperate to coherently serve a large number of mobile stations (MSs) in the same time/frequency resource. Similar to what has been traditionally done with conventional cellular networks, cell-free massive MIMO networks will be dimensioned to provide the required quality of service (QoS) to MSs under heavy traffic load conditions, and thus they might be underutilized during low traffic load periods, leading to an inefficient use of both spectral and energy resources. Aiming at the implementation of green cell-free massive MIMO networks, this paper proposes and analyzes the performance of different AP switch ON/OFF (ASO) strategies designed to dynamically turn ON/OFF some of the APs based on the number and/or location of the active MSs in the network. The proposed framework considers line-of-sight (LOS) and non-line-of-sight (NLOS) links between APs and MSs, the use of different antenna array architectures at the access points (APs), suitably characterized by array-dependent spatial correlation matrices, and specific power consumption models for APs, MSs and fronthaul links between the APs and the CPU. Numerical results show that the use of properly designed ASO strategies in cell-free massive MIMO networks clearly improve the achievable energy efficiency. Moreover, they also reveal the existing trade-offs among the achievable energy efficiency, the available network-state information, and the hardware configuration (i.e., number of APs, number of transmit antennas per AP, and number of MSs).

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Guillem Femenias

Papers

Cell-Free Millimeter-Wave Massive MIMO Systems With Limited Fronthaul Capacity

BER performance of linear STBC from orthogonal designs over MIMO correlated Nakagami-m fading channels

Cross-Layer Design of Adaptive Multirate Wireless Networks Using Truncated HARQ

Energy-Efficient Access-Point Sleep-Mode Techniques for Cell-Free mmWave Massive MIMO Networks With Non-Uniform Spatial Traffic Density

Access Point Switch ON/OFF Strategies for Green Cell-Free Massive MIMO Networking