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A key distinction between today's and future networks is the appetite for reliable communication to support emerging critical-communication services. In this paper, we study multi-operator connectivity as a form of redundancy to support the design of reliable networks and investigate its trade-offs. This approach is motivated by 3GPP standardisation initiatives of dual-connectivity and similar techniques in industrial wired networks. We deploy a risk awareness performance metric to assess reliability: this superquantile metric accounts for periods of connectivity shortfalls. Our analysis shows that multi-operator connectivity brings significant reliability gains, in particular when network deployments by different operators exhibit high complementarity in coverage. We also explore the effects of multi-connectivity on spectral efficiency in times of high demand for bandwidth. Our study is based on a real-world dataset comprising signal strength indicators of three mobile operators in Dublin, Ireland.

The next generation of mobile networks will bring an appetite for reliable communication, which enables emerging critical-communication services. In this paper, we present network sharing between operators as a way to provide increased reliability while using the already existing mobile network infrastructure. Our results indicate that network sharing significantly improves network performance during periods of connectivity shortfalls, benefiting the design of reliable networks. Our conclusions are drawn from a real-world dataset of signal quality indicators for three mobile operators in Dublin, Ireland.

Next generation wireless communication systems such as 5G will feature a step increase in the speed of wireless data transmission. This requires using RF signals of wider bandwidths along with higher order modulation schemes. Such signals are subjected to frequency and power dependent impairments such as gain compression, amplitude ripple and tilt, group-delay and AM-PM conversion as they traverse through the transmitter’s hardware blocks. This paper introduces a novel calibration scheme that applies a specially designed wideband 64- QAM modulated stimulus and uses the captured response to evaluate the impairments within the transmitter’s RF chain. The needed pre-compensation is applied in a single iteration. This technique is intended for use with Doherty, Outphasing and MIMO type applications. Presented technique was experimentally validated using signal bandwidths up to 100 MHz for both weakly and strongly nonlinear systems.

In this paper, we study the sum rate maximization for a multiple-input multiple-output (MIMO) system with successive zero-forcing dirty-paper coding (SZFDPC) and per-antenna power constraint (PAPC). Although SZFDPC is a low-complexity alternative to the optimal dirty paper coding, efficient algorithms to compute its sum rate are still open problems especially under practical PAPC. The existing solution to the considered problem is computationally inefficient due to employing high-complexity interior-point method. In this study, we propose two novel low-complexity approaches to this important problem. More specifically, the first algorithm achieves the optimal solution by transforming the original problem in the broadcast channel into an equivalent problem in the multiple access channel, then the resulting problem is solved by alternating optimization together with successive convex approximation. We also derive a suboptimal solution based on machine learning to which simple linear regressions are applicable. The approaches are analyzed and validated extensively to demonstrate their superiors over the existing approach.

As the physical makeup of cellular basestations evolve into systems with multiple parallel transmission paths the effort involved in modelling these complex systems increases considerably. One task in particular which contributes to signal distortion on each signal path, is the power amplifier. In power amplifier (PA) modelling, Recursive Least Squares (RLS) has been used in the past to train Volterra models with memory terms. The Volterra model is widely used for modelling of PAs. In this paper we present a comparison of the stability performance for a PA model during training for various model memory lengths, model orders of non linearity and signal sample rates. This examination provides a technique to avoid instability occurring during the adaptive training of dynamic nonlinear behavioural models.

A new technique for the estimation of coupling between array elements in MIMO transceivers is presented. The estimation method is founded on subsequent transmission and over-the-air (OTA) reception between the array elements, when the transmitter’s characteristics are unknown. The method enables accurate on-line characterization of the behavior of the array in terms of coupling for a complete system with PAs and antennas connected. The method is validated via OTA measurements on a four-element array in a MIMO transmitter configuration. The results demonstrate that the estimated couplings with the proposed technique are similar to the ones obtained from S-parameter measurements with deviations reflecting the operation with antennas and PAs connected. The proposed intra-array coupling estimation facilitates practical OTA measurement-based modeling and linearization of MIMO transmitters.

In this paper, we present a novel and effective linearization technique for nonlinear phased array antennas. For large phased arrays, linearization of the array using a single digital predistortion (DPD) is inevitable since one digital path is upconverted and feeds several RF transmission paths, each of which is connected to a power amplifier (PA) and an antenna element. However, a critical issue is that the PA characteristics can vary considerably within an array. Thus, linearizing individual PAs with one DPD is rather challenging. We formulate and solve an optimization problem that corresponds to jointly minimizing the maximum residuals between the input to the array and the output of individual PAs. We demonstrate that the proposed technique outperforms state-of-the-art linearization solutions while retaining the linear gain of the array.

In modern radio frequency (RF) transceivers the power amplifier (PA) is a central component in terms of power consumption. Achieving efficient performance in this component results in the PA output signal becoming distorted. Linearisation can be performed using techniques such as Digital Pre-Distortion (DPD). The pre-distorter operation of a DPD system involves the constant computation of a distorted signal to ensure linear operation of the nonlinear power amplifier. In this work a novel polynomial evaluation scheme is proposed to optimise the pre-distorter operation within a DPD system. Improvements to latency and hardware requirements are possible with new techniques. Validation of the proposed design was conducted using FPGA implementations and compared to incumbent pipelined solutions for both low latency and hardware efficiency. The proposed method indicated hardware savings of 67.8%, while operating 58.7% faster, compared to an existing implementation.

This work proposes a concise standalone model for Chireix power combiner. The model is based on the analysis of the nonlinear behaviour of a Chireix power combiner under amplitude imbalance. The generalised equations for input impedance of Chireix combiner branches excited by signals with different amplitudes have been derived. The results predicted by the model were validated using both commercial high frequency circuit simulations and experimentally measured results. As a result the proposed model serves two purposes. For one it can be used directly in a larger circuit simulation to predict the performance of an outphasing power amplifier. It can also be used as the basis for a linearization strategy for outphasing power amplifiers.

Power amplifiers are widely employed electronic devices in various fields such as mobile networks and radio frequency (RF) transceivers. To achieve efficient operations, power amplifiers can often suffer from nonlinearity problems. This problem can be mitigated through the use of linearization techniques, such as digital predistortion, regarded as the most promising solution to power amplifier linearization. Behavioural modeling is a substantial part of the digital predistortion, responsible for acquiring the coefficients that are necessary to linearize the power amplifier. A Complex Reduced Non-Uniform Generalized Memory Polynomial model was proposed to reach comparable performance of accuracy as Memory Polynomial Model with reduced complexities. The proposed model was tested with a 5MHz LTE signal measured at the input and output of a Doherty PA under different conditions of nonlinearities, memory effects and attenuations as well as PA working powers. It can be observed that the proposed model shows superior accuracy at low complexities, when the PA has higher levels of nonlinearity and memory depth while still maintaining low complexities. Over 60% of coefficients reduction could be reached at the same level of accuracy compared to the MP model.

In this paper, we propose a novel wideband wireless transmission scheme with spatially combined frequency interleaved transmitters of narrower bandwidths. The proposed technique enables development of seamless scalable bandwidth transmitters for next generation wireless and satellite communications with potential to reuse legacy hardware. The scheme is experimentally validated at Ka Band with instantaneous modulation bandwidths up to 400 MHz achieving transmission bit rates up to 2.039Gbps.

Modern wireless communication systems employ wideband modulated RF carriers to communicate the data of interest between the nodes in the network. The security of communications has been conventionally addressed in the data link layers through scrambling and data encryption schemes. These schemes however do not secure the air interface parameters such as modulation scheme and leave them susceptible to eavesdropping and interception by man-in-the-middle platforms. Physical layer security schemes such as directional modulation, DFT S OFDM and RF fingerprinting have been proposed. In this paper, we propose a novel physical layer encryption scheme based on the spectral profile of the intended modulated signal through deliberately introduced constellation distortion to conceal the modulation scheme. The scheme uses a dispersive filter in the modulator with unique group delay profiles unknown to the eavesdropper. The appropriate inverse filter is employed in the authorized receivers to recover the original modulated basebands for demodulation.

Next generation wireless communication systems such as fifth generation mobile communications and high throughput satellites have promised a step increase in the rate at which digital data can be transmitted. This requires wideband modulators consisting of high speed digital to analogue converters and RF upconverters to generate the wideband signal of interest. In this paper we demonstrate a scheme to generate a wide bandwidth modulated signal by bandwidth interleaving multiple modulators of narrower bandwidths. The proposed scheme is experimentally validated with measured results on an 8PSK signals of symbol rate 80 MSPS with modulation characteristics in accordance with DVB-S2 standard.

Modern wireless communication equipment such as outphasing power amplifiers or systems like massive-MIMO rely heavily on transmission of complex wideband modulated radio frequency signals on parallel signal paths. As these signal bandwidths increase, wireless transmitters are more susceptible to amplitude and phase distortions across frequency. We propose a novel method to quantify the complex signal distortions in each transmit path and a technique to pre-compensate the transmitter over a wide bandwidth of interest. This work has been experimentally validated with measured results on two separate RF test benches using signal bandwidths up to 100 MHz. An outphasing power amplifier bench for WCDMA at S band requiring 4 signal paths and a satellite uplink modulator using 8- PSK at Ku band requiring two signal paths were tested in the experimental validation. Further, it is also validated that this method requires only one iteration to calibrate a set of parallel RF signal paths.

Peak to Average Power Ratio (PAR or PAPR) is one of the most challenging issues in the operation of Orthogonal Frequency Division Multiplexing (OFDM) for multicarrier signals used in Fourth and Fifth Generation of broadband cellular network technology (4G and 5G). There are numerous PAPR reduction or also recognized as Crest Factor Reduction (CFR) techniques, for instance Clipping, Coding, Dummy Sequence Insertion (DSI), Tone Reservation, Active Constellation Sequence (ACE), Partial Transmit Sequence (PTS), and Selective Mapping (SLM) schemes. Among these methods, SLM-based techniques are very attractive solutions due to their good performance without additional out-of-band radiations or in-band distortions. This study demonstrates a performance analysis of an SLM-based method combined with adding randomly generated dummy sequences to power-free subcarriers. Simulation results show that the PAPR of the OFDM based signal can be reduced efficiently by using adequate number of dummies and tolerable number of iterations, and that is a potential scheme for 4G and 5G

New wireless technologies have been developed in recent years which enable applications that require the transmission of small amounts of data over long distances in an energy efficient manner. One of these technologies, LoRaWAN, includes a server-initiated communication mode named Class B which provides a deterministic latency for downlink communications. In this paper, we model Class B of LoRaWAN in ns-3 to explore the limits of scale at which this form of bi-directional communication remains feasible in large networks. The simulation results show that the principle restriction on scalability is caused by the duty cycle limits that the gateway must adhere to. In addition, we identify a limitation in the protocol which in certain configurations allows a gateway node to block the future transmission of its own beacon frames. Our contributions are the development of the first implementation and simulation of LoRaWAN Class B in ns-3, and an evaluation of the scalability limits of Class B.

LPWAN technologies are defined by their focus on extended coverage while maintaining energy efficiency, at the expense of data throughput. In this research we enable the analysis of LoRa, a key LPWAN technology, in terms of energy efficiency. We perform real-world measurements of a standard LoRa chip and use the results to develop an energy consumption module in ns-3. Our contributions are an analysis of the energy consumption of different states in a LoRa transmission by the SX1272, the LoRa transceiver that is used in most common LoRaWAN devices, beyond what is provided in the datasheet, and an energy consumption module for use in three of the LoRaWAN ns-3 modules described in research, enabling more accurate energy consumption analysis of LoRa-based systems.

In this paper, we revisit the fundamental problem of computing MIMO capacity under per-antenna power constraint (PAPC). Unlike the sum power constraint counterpart which likely admits water-filling-like solutions, MIMO capacity with PAPC has been largely studied under the framework of generic convex optimization. The two main shortcomings of these approaches are (i) their complexity scales quickly with the problem size, which is not appealing for large-scale antenna systems, and/or (ii) their convergence properties are sensitive to the problem data. As a starting point, we first consider a single user MIMO scenario and propose two provably-convergent iterative algorithms to find its capacity, the first method based on fixedpoint iteration and the other based on alternating optimization and minimax duality. In particular, the two proposed methods can leverage the water-filling algorithm in each iteration and converge faster, compared to current methods. We then extend the proposed solutions to multiuser MIMO systems with dirty paper coding (DPC) based transmission strategies. In this regard, capacity regions of Gaussian broadcast channels with PAPC are also computed using closed-form expressions. Numerical results are provided to demonstrate the outperformance of the proposed solutions over existing approaches.

This paper presents an efficient approach to computing the capacity of multiple-input multiple-output (MIMO) channels under multiple linear transmit covariance constraints (LTCCs). LTCCs are general enough to include several special types of power constraints as special cases such as the sum power constraint (SPC), per-antenna power constraint (PAPC), or a combination thereof. Despite its importance and generality, most of the existing literature considers either SPC or PAPC independently. Efficient solutions to the computation of the MIMO capacity with a combination of SPC and PAPC have been recently reported, but were only dedicated to multipleinput single-output (MISO) systems. For the general case of LTCCs, we propose a low-complexity semi-closed-form approach tothecomputationoftheMIMOcapacity.Specifically,amodified minimax duality is first invoked to transform the considered problem in the broadcast channel into an equivalent minimax problem in the dual multiple access channel. Then alternating optimization and concave-convex procedure are utilized to derive water-filling-based algorithms to find a saddle point of the minimax problem. This is different from the state-of-the-art solutions to the considered problem, which are based on interiorpoint or subgradient methods. Analytical and numerical results are provided to demonstrate the effectiveness of the proposed low-complexity solution under various MIMO scenarios.