Optimal Channel Training in Uplink Network MIMO Systems

We consider a multi-cell frequency-selective fading uplink channel (network MIMO) from K single-antenna user terminals (UTs) to B cooperative base stations (BSs) with M antennas each. The BSs, assumed to be oblivious of the applied codebooks, forward compressed versions of their observations to a central station (CS) via capacity limited backhaul links. The CS jointly decodes the messages from all UTs. Since the BSs and the CS are assumed to have no prior channel state information (CSI), the channel needs to be estimated during its coherence time. Based on a lower bound of the ergodic mutual information, we determine the optimal fraction of the coherence time used for channel training, taking different path losses between the UTs and the BSs into account. We then study how the optimal training length is impacted by the backhaul capacity. Although our analytical results are based on a large system limit, we show by simulations that they provide very accurate approximations for even small system dimensions.Comment: 15 pages, 7 figures. To appear in the IEEE Transactions on Signal Processin

Optimal Power Allocation in MIMO wire-tap channels

Projecte Finl de Carrera fet en col.laboració amb Università La Sapienza di Roma.English: Study of a methodology that, without the use of cryptography, limits the possible "intelligence" present at the eavesdropper and increases the level of secrecy on a wireless environment using MIMO systems.Castellano: Estudio de una metodologia que, sin hacer uso de la criptografia, permite limitar la posible "inteligencia" del espia, con la finalidad de aumentar la confidencialidad en comunicacines wireless con sistemas MIMOCatalà: Estudi d'una metodologia que, sense fer ús de la criptografia, permet limitar la possible "intel.ligència" de l'espia per tal d'augmentar la confidencialitat en comunicacions wireless amb sistemes MIMO

Robust Symbol Level Precoding for Overlay Cognitive Radio Networks

This paper focuses on designing robust symbol-level precoding (SLP) in the downlink of an overlay cognitive radio (CR) network, where a primary base station (PBS) serving primary users (PUs) and a cognitive base station (CBS) serving cognitive users (CUs) share the same frequency band. When the PBS shares data and perfect channel state information (CSI) with the CBS, an SLP approach which minimizes the CR transmission power and satisfies symbol-wise Safety Margin (SM) constraints of both PUs and CUs, is obtained in a low-complexity quadratic formulation. Then for the case of imperfect CSI from the PBS to CBS, we propose robust SLP schemes. First, with a norm-bounded CSI error model to approximate uncertain channels at the PBS, we adopt the max-min philosophy to conservatively achieve robust SLP constraints. Second, we use the additive quantization noise model (AQNM) to describe the statistics of the quantized PBS CSI, and we employ a stochastic constraint to formulate the problem, where the SM constraints are converted to be deterministic. Simulation results show that the proposed robust SLP schemes help enable PUs to mitigate negative effect of the quantization noise and simultaneously offer CR transmission with significant improvements in energy efficiency compared to non-robust methods.Comment: 30 pages, 13 figures, journa

Matrix-Monotonic Optimization for MIMO Systems

For MIMO systems, due to the deployment of multiple antennas at both the transmitter and the receiver, the design variables e.g., precoders, equalizers, training sequences, etc. are usually matrices. It is well known that matrix operations are usually more complicated compared to their vector counterparts. In order to overcome the high complexity resulting from matrix variables, in this paper we investigate a class of elegant multi-objective optimization problems, namely matrix-monotonic optimization problems (MMOPs). In our work, various representative MIMO optimization problems are unified into a framework of matrix-monotonic optimization, which includes linear transceiver design, nonlinear transceiver design, training sequence design, radar waveform optimization, the corresponding robust design and so on as its special cases. Then exploiting the framework of matrix-monotonic optimization the optimal structures of the considered matrix variables can be derived first. Based on the optimal structure, the matrix-variate optimization problems can be greatly simplified into the ones with only vector variables. In particular, the dimension of the new vector variable is equal to the minimum number of columns and rows of the original matrix variable. Finally, we also extend our work to some more general cases with multiple matrix variables.Comment: 37 Pages, 5 figures, IEEE Transactions on Signal Processing, Final Versio

Achievable rates of full-duplex MIMO radios in fast fading channels with imperfect channel estimation

We study the theoretical performance of two full-duplex multiple-input multiple-output (MIMO) radio systems: a full-duplex bi-directional communication system and a full-duplex relay system. We focus on the effect of a (digitally manageable) residual self-interference due to imperfect channel estimation (with independent and identically distributed (i.i.d.) Gaussian channel estimation error) and transmitter noise. We assume that the instantaneous channel state information (CSI) is not available the transmitters. To maximize the system ergodic mutual information, which is a non-convex function of power allocation vectors at the nodes, a gradient projection algorithm is developed to optimize the power allocation vectors. This algorithm exploits both spatial and temporal freedoms of the source covariance matrices of the MIMO links between transmitters and receivers to achieve higher sum ergodic mutual information. It is observed through simulations that the full-duplex mode is optimal when the nominal self-interference is low, and the half-duplex mode is optimal when the nominal self-interference is high. In addition to an exact closed-form ergodic mutual information expression, we introduce a much simpler asymptotic closed-form ergodic mutual information expression, which in turn simplifies the computation of the power allocation vectors

D 3. 3 Final performance results and consolidated view on the most promising multi -node/multi -antenna transmission technologies

This document provides the most recent updates on the technical contributions and research challenges focused in WP3. Each Technology Component (TeC) has been evaluated under possible uniform assessment framework of WP3 which is based on the simulation guidelines of WP6. The performance assessment is supported by the simulation results which are in their mature and stable state. An update on the Most Promising Technology Approaches (MPTAs) and their associated TeCs is the main focus of this document. Based on the input of all the TeCs in WP3, a consolidated view of WP3 on the role of multinode/multi-antenna transmission technologies in 5G systems has also been provided. This consolidated view is further supported in this document by the presentation of the impact of MPTAs on METIS scenarios and the addressed METIS goals.Aziz, D.; Baracca, P.; De Carvalho, E.; Fantini, R.; Rajatheva, N.; Popovski, P.; Sørensen, JH.... (2015). D 3. 3 Final performance results and consolidated view on the most promising multi -node/multi -antenna transmission technologies. http://hdl.handle.net/10251/7675

Full-duplex MU-MIMO systems under the effects of non-ideal transceivers: performance analysis and power allocation optimization

Modern Technologies, particularly connectivity, increasingly support many facets of everyday life. The next generation of wireless communication systems aims to provide new advanced services and support new demands. These services are required to serve a massive number of devices and achieve higher spectral and energy efficiency, ultra-low latency, and reliable communication. The research community around the globe is still working on finding novel technologies to meet these requirements. Full duplex (FD) communications have been recognized as one of the promising wireless transmission candidates and gamechangers for the future of wireless communication and networking technologies, thanks to their ability to greatly improve spectral efficiency (SE) and dramatically enhance energy efficiency (EE). In this thesis, first, the influence of hardware impairment (HWI) on singleinput single-output (SISO) FD access point (AP) is studied. More precisely, the SE and EE when the system’s terminals have impaired transceivers are analyzed. Optimization problem for EE maximization is formulated to fulfill quality of service (QoS) and power budget constraints. An algorithm to solve the optimization problem by using the fractional programming theory and Karush–Kuhn–Tucker (KKT) conditions technique is proposed. [...