Resource Allocation in Multi-user MIMO Networks: Interference Management and Cooperative Communications

Nowadays, wireless communications are becoming so tightly integrated in our daily lives, especially with the global spread of laptops, tablets and smartphones. This has paved the way to dramatically increasing wireless network dimensions in terms of subscribers and amount of flowing data. Therefore, the two important fundamental requirements for the future 5G wireless networks are abilities to support high data traffic and exceedingly low latency. A likely candidate to fulfill these requirements is multicell multi-user multi-input multiple-output (MU-MIMO); also termed as coordinated multi-point (CoMP) transmission and reception. To achieve the highest possible performance in MU-MIMO networks, a properly designed resource allocation algorithm is needed. Moreover, with the rapidly growing data traffic, interference has become a major limitation in wireless networks. Interference alignment (IA) has been shown to significantly manage the interference and improve the network performance. However, how practically use IA to mitigate interference in a downlink MU-MIMO network still remains an open problem. In this dissertation, we improve the performance of MU-MIMO networks in terms of spectral efficiency, by designing and developing new beamforming algorithms that can efficiently mitigate the interference and allocate the resources. Then we mathematically analyze the performance improvement of MUMIMO networks employing proposed techniques. Fundamental relationships between network parameters and the network performance is revealed, which provide guidance on the wireless networks design. Finally, system level simulations are conducted to investigate the performance of the proposed strategies

Dynamic Location Modelling in 3D Beamforming for 5G Mobile Communications

Mobile communication system is designed to provide reliable communication with more number of services and with low cost among multiple users. Due to limited frequency spectrum and resources, mobile communication requires more development in case of both establishing communication and maintenance in service quality. To fulfill these requirements, 5G mobile communication is being developed to provide high quality reliable communication and quality of service, by using beamforming model. As the trend of next generation mobile communication, 3D directional transmission is considered to give enhanced coverage model and reusability of frequency. Phase arrayed antenna is used in this beamforming model to give orthogonal communication among users. In this paper, a new modeling of beamforming is applied to give a new dimension by considering altitude with potential field strategy. Here phase arrayed antenna is replaced by 3-D smart antenna to improve the performance of 5G mobile communications. Performance evaluation outcomes 3D beamforming leads 2D beamforming in terms of communication delay, and uplink downlink throughput

Coordinated Beamforming with Relaxed Zero Forcing: The Sequential Orthogonal Projection Combining Method and Rate Control

In this paper, coordinated beamforming based on relaxed zero forcing (RZF) for K transmitter-receiver pair multiple-input single-output (MISO) and multiple-input multiple-output (MIMO) interference channels is considered. In the RZF coordinated beamforming, conventional zero-forcing interference leakage constraints are relaxed so that some predetermined interference leakage to undesired receivers is allowed in order to increase the beam design space for larger rates than those of the zero-forcing (ZF) scheme or to make beam design feasible when ZF is impossible. In the MISO case, it is shown that the rate-maximizing beam vector under the RZF framework for a given set of interference leakage levels can be obtained by sequential orthogonal projection combining (SOPC). Based on this, exact and approximate closed-form solutions are provided in two-user and three-user cases, respectively, and an efficient beam design algorithm for RZF coordinated beamforming is provided in general cases. Furthermore, the rate control problem under the RZF framework is considered. A centralized approach and a distributed heuristic approach are proposed to control the position of the designed rate-tuple in the achievable rate region. Finally, the RZF framework is extended to MIMO interference channels by deriving a new lower bound on the rate of each user.Comment: Lemma 1 proof corrected; a new SOPC algorithm invented; K > N case considere

Técnicas de equalização e pré-codificação para sistemas MC-CDMA

Mestrado em Engenharia Eletrónica e TelecomunicaçõesO número de dispositivos com ligações e aplicações sem fios está a aumentar exponencialmente, causando problemas de interferência e diminuindo a capacidade do sistema. Isto desencadeou uma procura por uma eficiência espectral superior e, consequentemente, tornou-se necessário desenvolver novas arquitecturas celulares que suportem estas novas exigências. Coordenação ou cooperação multicelular é uma arquitectura promissora para sistemas celulares sem fios. Esta ajuda a mitigar a interferência entre células, melhorando a equidade e a capacidade do sistema. É, portanto, uma arquitectura já em estudo ao abrigo da tecnologia LTE-Advanced sob o conceito de coordenação multiponto (CoMP). Nesta dissertação, considerámos um sistema coordenado MC-CDMA com pré-codificação e equalização iterativas. Uma das técnicas mais eficientes de pré-codificação é o alinhamento de interferências (IA). Este é um conceito relativamente novo que permite aumentar a capacidade do sistema em canais de elevada interferência. Sabe-se que, para os sistemas MC-CDMA, os equalizadores lineares convencionais não são os mais eficientes, devido à interferência residual entre portadoras (ICI). No entanto, a equalização iterativa no domínio da frequência (FDE) foi identificada como sendo uma das técnicas mais eficientes para lidar com ICI e explorar a diversidade oferecida pelos sistemas MIMO MC-CDMA. Esta técnica é baseada no conceito Iterative Block Decision Feedback Equalization (IB-DFE). Nesta dissertação, é proposto um sistema MC-CDMA que une a pré-codificação iterativa do alinhamento de interferências no transmissor ao equalizador baseado no IB-DFE, com cancelamento sucessivo de interferências (SIC) no receptor. Este é construído por dois blocos: um filtro linear, que mitiga a interferência inter-utilizador, seguido por um bloco iterativo no domínio da frequência, que separa eficientemente os fluxos de dados espaciais na presença de interferência residual inter-utilizador alinhada. Este esquema permite atingir o número máximo de graus de liberdade e permite simultaneamente um ganho óptimo de diversidade espacial. O desempenho deste esquema está perto do filtro adaptado- Matched Filter Bound (MFB).The number of devices with wireless connections and applications is increasing exponentially, causing interference problems and reducing the system’s capacity gain. This initiated a search for a higher spectral efficiency and therefore it became necessary to develop new cellular architectures that support these new requirements. Multicell cooperation or coordination is a promising architecture for cellular wireless systems to mitigate intercell interference, improving system fairness and increasing capacity, and thus is already under study in LTE-Advanced under the coordinated multipoint (CoMP) concept. In this thesis, efficient iterative precoding and equalization is considered for coordinated MC-CDMA based systems. One of the most efficient precoding techniques is interference alignment (IA), which is a relatively new concept that allows high capacity gains in interfering channels. It is well known that for MC-CDMA systems standard linear equalizers are not the most efficient due to residual inter carrier interference (ICI). However, iterative frequency-domain equalization (FDE) has been identified as one of the most efficient technique to deal with ICI and exploit the inherent space-frequency diversity of the MIMO MC-CDMA systems, namely the one based on Iterative Block Decision Feedback Equalization (IB-DFE) concept. In this thesis, it is proposed a MC-CDMA system that joins iterative IA precoding at the transmitter with IB-DFE successive interference cancellation (SIC) based receiver structure. The receiver is implemented in two steps: a linear filter, which mitigates the inter-user aligned interference, followed by an iterative frequency-domain receiver, which efficiently separates the spatial streams in the presence of residual inter-user aligned interference. This scheme provides the maximum degrees of freedom (DoF) and allows almost the optimum space-diversity gain. The scheme performance is close to the matched filter bound (MFB)

Técnicas de pré-codificação para sistemas multicelulares coordenados

Doutoramento em TelecomunicaçõesCoordenação Multicélula é um tópico de investigação em rápido crescimento e uma solução promissora para controlar a interferência entre células em sistemas celulares, melhorando a equidade do sistema e aumentando a sua capacidade. Esta tecnologia já está em estudo no LTEAdvanced sob o conceito de coordenação multiponto (COMP). Existem várias abordagens sobre coordenação multicélula, dependendo da quantidade e do tipo de informação partilhada pelas estações base, através da rede de suporte (backhaul network), e do local onde essa informação é processada, i.e., numa unidade de processamento central ou de uma forma distribuída em cada estação base. Nesta tese, são propostas técnicas de pré-codificação e alocação de potência considerando várias estratégias: centralizada, todo o processamento é feito na unidade de processamento central; semidistribuída, neste caso apenas parte do processamento é executado na unidade de processamento central, nomeadamente a potência alocada a cada utilizador servido por cada estação base; e distribuída em que o processamento é feito localmente em cada estação base. Os esquemas propostos são projectados em duas fases: primeiro são propostas soluções de pré-codificação para mitigar ou eliminar a interferência entre células, de seguida o sistema é melhorado através do desenvolvimento de vários esquemas de alocação de potência. São propostas três esquemas de alocação de potência centralizada condicionada a cada estação base e com diferentes relações entre desempenho e complexidade. São também derivados esquemas de alocação distribuídos, assumindo que um sistema multicelular pode ser visto como a sobreposição de vários sistemas com uma única célula. Com base neste conceito foi definido uma taxa de erro média virtual para cada um desses sistemas de célula única que compõem o sistema multicelular, permitindo assim projectar esquemas de alocação de potência completamente distribuídos. Todos os esquemas propostos foram avaliados em cenários realistas, bastante próximos dos considerados no LTE. Os resultados mostram que os esquemas propostos são eficientes a remover a interferência entre células e que o desempenho das técnicas de alocação de potência propostas é claramente superior ao caso de não alocação de potência. O desempenho dos sistemas completamente distribuídos é inferior aos baseados num processamento centralizado, mas em contrapartida podem ser usados em sistemas em que a rede de suporte não permita a troca de grandes quantidades de informação.Multicell coordination is a promising solution for cellular wireless systems to mitigate inter-cell interference, improving system fairness and increasing capacity and thus is already under study in LTE-A under the coordinated multipoint (CoMP) concept. There are several coordinated transmission approaches depending on the amount of information shared by the transmitters through the backhaul network and where the processing takes place i.e. in a central processing unit or in a distributed way on each base station. In this thesis, we propose joint precoding and power allocation techniques considering different strategies: Full-centralized, where all the processing takes place at the central unit; Semi-distributed, in this case only some process related with power allocation is done at the central unit; and Fulldistributed, where all the processing is done locally at each base station. The methods are designed in two phases: first the inter-cell interference is removed by applying a set of centralized or distributed precoding vectors; then the system is further optimized by centralized or distributed power allocation schemes. Three centralized power allocation algorithms with per-BS power constraint and different complexity tradeoffs are proposed. Also distributed power allocation schemes are proposed by considering the multicell system as superposition of single cell systems, where we define the average virtual bit error rate (BER) of interference-free single cell system, allowing us to compute the power allocation coefficients in a distributed manner at each BS. All proposed schemes are evaluated in realistic scenarios considering LTE specifications. The numerical evaluations show that the proposed schemes are efficient in removing inter-cell interference and improve system performance comparing to equal power allocation. Furthermore, fulldistributed schemes can be used when the amounts of information to be exchanged over the backhaul is restricted, although system performance is slightly degraded from semi-distributed and full-centralized schemes, but the complexity is considerably lower. Besides that for high degrees of freedom distributed schemes show similar behaviour to centralized ones

Downlink Achievable Rate Analysis for FDD Massive MIMO Systems

Multiple-Input Multiple-Output (MIMO) systems with large-scale transmit antenna arrays, often called massive MIMO, are a very promising direction for 5G due to their ability to increase capacity and enhance both spectrum and energy efficiency. To get the benefit of massive MIMO systems, accurate downlink channel state information at the transmitter (CSIT) is essential for downlink beamforming and resource allocation. Conventional approaches to obtain CSIT for FDD massive MIMO systems require downlink training and CSI feedback. However, such training will cause a large overhead for massive MIMO systems because of the large dimensionality of the channel matrix. In this dissertation, we improve the performance of FDD massive MIMO networks in terms of downlink training overhead reduction, by designing an efficient downlink beamforming method and developing a new algorithm to estimate the channel state information based on compressive sensing techniques. First, we design an efficient downlink beamforming method based on partial CSI. By exploiting the relationship between uplink direction of arrivals (DoAs) and downlink direction of departures (DoDs), we derive an expression for estimated downlink DoDs, which will be used for downlink beamforming. Second, By exploiting the sparsity structure of downlink channel matrix, we develop an algorithm that selects the best features from the measurement matrix to obtain efficient CSIT acquisition that can reduce the downlink training overhead compared with conventional LS/MMSE estimators. In both cases, we compare the performance of our proposed beamforming method with traditional methods in terms of downlink achievable rate and simulation results show that our proposed method outperform the traditional beamforming methods