Joint optimization of power and data transfer in multiuser MIMO systems

We present an approach to solve the nonconvex optimization problem that arises when designing the transmit covariance matrices in multiuser multiple-input multiple-output (MIMO) broadcast networks implementing simultaneous wireless information and power transfer (SWIPT). The MIMO SWIPT problem is formulated as a general multiobjective optimization problem, in which data rates and harvested powers are optimized simultaneously. Two different approaches are applied to reformulate the (nonconvex) multiobjective problem. In the first approach, the transmitter can control the specific amount of power to be harvested by power transfer whereas in the second approach the transmitter can only control the proportion of power to be harvested among the different harvesting users. We solve the resulting formulations using the majorization-minimization (MM) approach. The solution obtained from the MM approach is compared to the classical block-diagonalization (BD) strategy, typically used to solve the nonconvex multiuser MIMO network by forcing no interference among users. Simulation results show that the proposed approach improves over the BD approach both the system sum rate and the power harvested by users. Additionally, the computational times needed for convergence of the proposed methods are much lower than the ones required for classical gradient-based approaches.Peer ReviewedPostprint (author's final draft

Scheduler Algorithms for MU-MIMO

In multi-user multiple input multiple output (MU-MIMO), the complexity of the base-station scheduler has increased further compared to single-user multiple input multiple output (SU-MIMO). The scheduler must understand if several users can be spatially multiplexed in the same time-frequency resource. One way to spatially separate users is through beamforming with sufficiently many antennas. In this thesis work, two downlink beamforming algorithms for MU-MIMO are studied: The first algorithm implements precoding without considering inter-cell interference (ICI). The second one considers it and attempts to mitigate or null transmissions in the direction of user equipments (UEs) in other cells. The two algorithms are evaluated in SU-MIMO and MU-MIMO setups operating in time division duplex (TDD) mode and serving with single and dual-antenna terminals. Full-Buffer (FB) and file transfer protocol (FTP) data traffic profiles are studied. Additionally, various UE mobility patterns, UE transmit antenna topologies, sounding reference signal (SRS) periodicity configurations, and uniform linear array (ULA) topologies are considered. Simulations have been performed using a system level simulation framework developed by Ericsson AB. Another important part of this thesis work is the functional verification of this simulation framework, which at the time of writing is still undergoing development. Our simulation results show that in SU-MIMO, the second algorithm, which considers ICI, outperforms the first one for FB traffic profile and all UE speeds, but not for FTP traffic profile and medium (30 km/h) or high (60 km/h) UE speeds. In this case, the first algorithm, which does not consider ICI, can be used with advantage. In MU-MIMO, cell downlink throughput gains are observed for the second algorithm over the first one for low and medium system loads (number of users). For both algorithms, the cell throughput is observed to decrease with increasing UE speed and sounding periodicity.Scheduling in modern wireless standards, e.g., 3G, 4G and future 5G, can be defined as the task of allocating time and frequency resources by the base station (BS) to each user equipment (UE) that wants to engage in communication. Resources are allocated every transmission time interval (TTI), which is typically one millisecond. There exist both uplink (from the UEs to the BS) and downlink (from the BS to the UEs) resource schedulers implemented in the e-Node B, i.e., the base station (BS) in Long Term Evolution (LTE). The aim of this thesis work is to study how various communication techniques proposed for 5G can increase the overall system throughput of the downlink (DL) when a realistic resource scheduler is used. In particular, we consider: (i) Beamforming, (ii) Multi-user multiple input multiple output (MU-MIMO), and (iii) Inter-cell interference (ICI) mitigation. Beamforming can be achieved by deploying a large number of antenna elements at the BS with the aim of increasing the signal to interference noise ratio (SINR) towards the UE. Contrary to single-user multiple input multiple output (SU-MIMO), in MU-MIMO more than one UE are scheduled for transmissions in the same time-frequency resource; this is possible by judiciously pairing various UEs which are spatially sufficiently separated (according to some metric that we will define later). ICI mitigation can be achieved by means of proper precoding at BS where the precoder attempts to mitigate the interfering signal from BS towards UEs belonging to neighboring cells. In this thesis work, we investigate the performance of two scheduler algorithms for MU-MIMO, using SU-MIMO as baseline. The first algorithm does not consider ICI while the second one does. Dual layer beamforming (that is, two independent data streams are transmitted to each UE) and time division duplex (TDD) are assumed. In TDD mode the BS acquires the channel information from sounding reference signals (SRS) transmitted in the uplink (UL) and, by virtue of channel reciprocity, reuses the so-obtained channel information in the downlink. The performance evaluation of the two algorithms is based on the following parameters: UE Traffic profile, UE speed, SRS UL antenna configuration, SRS parameters, and BS antenna topology. - UE speed includes 3,30, and 60 km/h. - UE traffic profile includes full-buffer (FB) and file transfer protocol (FTP). With FB traffic profile, UEs send/receive data to/from the BS all the time, while this is not the case in the FTP traffic profile case. Some examples of FTP traffic profiles may include chatty, video, VoIP, web, etc. - SRS UL antenna configuration includes: (i) Two SRS, in which each UE sends two SRS to the BS from two antennas, (ii) one SRS with antenna selection, in which each UE alternately sends one SRS to the BS from each of two antennas, and (iii) one SRS without antenna selection, in which each UE sends one SRS to the BS from only one antenna. For two SRS UE case (note that in the downlink two layers, and hence two UE antennas, are always used). - SRS parameters include SRS bandwidth and SRS periodicity. In this thesis work, full-bandwidth SRS (20 MHz) with various SRS periodicities such as 5 ms, 10 ms, 20 ms are considered. - BS antenna topology includes 8 and 64 antenna elements at the BS. The main result of this thesis work is that in both SU-MIMO and MU-MIMO with FB traffic profile, it is better to use the second algorithm which considers ICI rather than the first one which does not. However, with FTP traffic profile, this is not always the case

User grouping and resource allocation in multiuser MIMO systems under SWIPT

This paper considers a broadcast multiple-input multiple-output (MIMO) network with multiple users and simultaneous wireless information and power transfer (SWIPT). In this scenario, it is assumed that some users are able to harvest power from radio frequency (RF) signals to recharge batteries through wireless power transfer from the transmitter, while others are served simultaneously with data transmission. The criterion driving the optimization and design of the system is based on the weighted sum rate for the users being served with data. At the same time, constraints stating minimum per-user harvested powers are included in the optimization problem. This paper derives the structure of the optimal transmit covariance matrices in the case where both types of users are present simultaneously in the network, particularizing the results to the cases where either only harvesting nodes or only information users are to be served. The trade-off between the achieved weighted sum rate and the powers harvested by the user terminals is analyzed and evaluated using the rate-power (R-P) region. Finally, we propose a two-stage user grouping mechanism that decides which users should be scheduled to receive information and which users should be configured to harvest energy from the RF signals in each particular scheduling period, this being one of the main contributions of this paper.Peer ReviewedPostprint (published version

Resource management techniques for sustainable networks with energy harvesting nodes

Premi extraordinari doctorat UPC curs 2015-2016, àmbit Enginyeria de les TICThis dissertation proposes novel techniques for assigning resources of wireless networks by considering that the coverage radii are small, implying that some power consumption sinks not considered so far shouldnow be introduced, and by considering that the devices are battery-powered terminals provided with energy harvesting capabilities. In this framework, two different configurations in terms of harvesting capabilities are considered. First, we assume that the energy source is external and not controllable, e.g. solar energy. In this context, the proposed design should adapt to the energy that is currently being harvested. We also study the effect of having a finite backhaul connection that links the wireless access network with the core network. On the other hand, we propose a design in which the transmitter feeds actively the receivers with energy by transmitting signals that receivers use for recharging their batteries. In this case, the power transfer design should be carried out jointly with the power control strategy for users that receive information as both procedures, transfer of information and transfer of power, are implemented at the transmitter and make use of a common resource, i.e., power. Apart from techniques for assigning the radio resources, this dissertation develops a procedure for switching on and off base stations. Concerning this, it is important to notice that the traffic profile is not constant throughout the day. This is precisely the feature that can be exploited to define a strategy based on a dynamic selection of the base stations to be switched off when the traffic load is low, without affecting the quality experienced by the users. Thanks to this procedure, we are able to deploy smaller energy harvesting sources and smaller batteries and, thus, to reduce the cost of the network deployment. Finally, we derive some procedures to optimize high level decisions of the network operation in which variables from several layers of the protocol stack are involved. In this context, admission control procedures for deciding which user should be connected to which base station are studied, taking into account information of the average channel information, the current battery levels, etc. A multi-tier multi-cell scenario is assumed in which base stations belonging to different tiers have different capabilities, e.g., transmission power, battery size, end energy harvesting source size. A set of strategies that require different computational complexity are derived for scenarios with different user mobility requirements.Aquesta tesis doctoral proposa tècniques per assignar els recursos disponibles a les xarxes wireless considerant que els radis de cobertura són petits, el que implica que altres fonts de consum d’energia no considerades fins al moment s’hagin d’introduir dins els dissenys, i considerant que els dispositius estan alimentats amb bateries finites i que tenen a la seva disposició fonts de energy harvesting. En aquest context, es consideren dues configuracions diferents en funció de les capacitats de l’energia harvesting. En primer lloc, s’assumirà que la font d’energia és externa i incontrolable com, per exemple, l’energia solar. Els dissenys proposats han d’adaptar-se a l’energia que s’està recol·lectant en un precís moment. En segon lloc, es proposa un disseny en el qual el transmissor és capaç d’enviar energia als receptors mitjançant senyals de radiofreqüència dissenyats per aquest fi, energia que és utilitzada per recarregar les bateries. A part de tècniques d’assignació de recursos radio, en aquesta tesis doctoral es desenvolupa un procediment dinàmic per apagar i encendre estacions base. És important notar que el perfil de tràfic no és constant al llarg del dia. Aquest és precisament el patró que es pot explotar per definir una estratègia dinàmica per poder decidir quines estaciones base han de ser apagades, tot això sense afectar la qualitat experimentada pels usuaris. Gràcies a aquest procediment, es possible desplegar fonts d'energy harvesting més petites i bateries més petites. Finalment, aquesta tesis doctoral presenta procediments per optimitzar decisions de nivell més alt que afecten directament al funcionament global de la xarxa d’accés. Per prendre aquestes decisions, es fa ús de diverses variables que pertanyen a diferents capes de la pila de protocols. En aquest context, aquesta tesis aborda el disseny de tècniques de control d’admissió d’usuaris a estacions base en entorns amb múltiples estacions base, basant-se amb la informació estadística dels canals, i el nivell actual de les bateries, entre altres. L'escenari considerat està format per múltiples estacions base, on cada estació base pertany a una família amb diferents capacitats, per exemple, potència de transmissió o mida de la bateria. Es deriven un conjunt de tècniques amb diferents costos computacionals que són d'utilitat per a poder aplicar a escenaris amb diferents mobilitats d’usuaris.Award-winningPostprint (published version