In this thesis, advanced interference management techniques are designed and evaluated for largescale wireless networks with realistic assumptions, such as signal propagation loss, random node distribution and non-instantaneous channel state information at the transmitter (CSIT). In the first part of the thesis, the Maddah-Ali and Tse (MAT) scheme for the 2-user and 2-antenna base station (BS) broadcast channel (BC) is generalised and optimised using the probabilisticconstrained optimisation approach. With consideration of the unknown channel entries, the proposed optimisation approach guarantees a high probability that the interference leakage power is below a certain threshold in the presence of minimum interference leakage receivers. The desired signal detectability is maximised at the same time and the closed-form solution for the receiving matrices is provided. Afterwards, the proposed optimisation approach is extended to the 3-user BC with 2-antenna BS. Simulation results show substantial sum rate gain over the MAT scheme, especially with a large spatial correlation at the receiver side. In the second part, the MAT scheme is extended to the time-correlated channels in three scenarios, in which degrees of freedom (DoF) regions as well as achievability schemes are studied: 1) 2-user interference channel (IC) using imperfect current and imperfect delayed CSIT; 2) K-user BC with K-antenna BS using imperfect current and perfect delayed CSIT; 3) 3-user BC with 2-antenna BS using imperfect current and perfect delayed CSIT. Notably, the consistency of the proposed DoF regions with the MAT scheme and the ZF beamforming schemes using perfect current CSIT consents to the optimality of the proposed achievability schemes. In the third part, the performance of the ZF receiver is evaluated in Poisson distributed wireless networks. Simple static networks as well as dynamic networks are studied. For the static network, transmission capacity is derived whereby the receiver can eliminate interference from nearby transmitters. It is shown that more spatial receive degrees of freedom (SRDoF) should be allocated to decode the desired symbol in the presence of low transmitter intensity. For the dynamic network, in which the data traffic is modelled by queueing theory, interference alignment (IA) beamforming is considered and implemented sequentially. Interestingly, transmitting one data stream achieves the highest area spectrum efficiency. Finally, a distance-dependent IA beamforming scheme is designed for a generic 2-tier heterogeneous wireless network. Second-tier transmitters partially align their interferences to the dominant cross-tier interference overheard by the receivers in the same cluster. Essentially, the proposed IA scheme compromises between enhancing the signal-to-interference ratio and increasing the multiplexing gain. It is shown that acquiring accurate distance knowledge brings insignificant throughput gain compared to statistical distance knowledge. Simulation results validate the derived expressions of success probabilities as well as throughput, and show that the distance-dependent IA scheme significantly outperforms the traditional IA scheme in the presence of path-loss effect.

In this paper, we propose a new interference alignment (IA) scheme that jointly designs the linear transmitter and receiver for the 2-user MIMO X channel system, using minimum total mean square error criterion, subject to each transmitter power constraint. We show that transmitters and receivers under such criteria could be realized through a joint iterative algorithm. Considering the imperfection of channel state information (CSI), we also extend the minimum mean square error interference alignment schemes for the MIMO X channel with CSI estimation error. A robust iterative algorithm which is insensitve to CSI estimation error is proposed. Simulation results are also provided to demonstrate the proposed algorithm.

In this paper, we propose a new interference alignment (IA) scheme designing jointly the linear transmitter and receiver for the MIMO interference channel system, using minimum total mean square error criterion, subject to individual transmit power constraints. We show that transmitter and receiver under such criterion could be realized through a joint iterative algorithm. The convergence of the proposed algorithm is discussed. We also proposed a robust MMSE-based iterative design with imperfect channel state information (CSI). The proposed robust MMSE-based iterative interference alignment scheme is shown to be less sensitive to channel estimation errors. Simulation results show that the proposed schemes outperform the existing IA schemes with fast convergence.

In this paper, an interference alignment system for the distributed MIMO network is investigated. We propose a new precoding scheme using interference alignment in modulation signal domain. The simulation results show that the proposed one-dimensional precoding scheme can provide significant performance improvement over the conventional schemes using interference alignment.

Interference can be aligned in either vector space (MIMO) or signal scale (lattice). Existing literatures on interference alignment treat these two approaches separately. In this paper, a unified design framework of interference suppression is proposed for interference channel, where both vector alignment and lattice alignment are considered jointly. The framework could adapt the interference alignment mode (vector or lattice) dynamically according to the channel state information (CSI), therefore, bringing more “ optimization freedom” in transmission design. Moreover, since perfect interference alignment schemes are designed for infinite SNR, we allow the imperfect interference alignment in low to medium SNR regime, and formulate the joint precoder and equalizer design as a sum-MSE minimization problem. Finally, it's shown by simulations that our proposed scheme has a significant performance gain over the conventional interference mitigation schemes in pure vector space.

In this paper, an interference alignment system for the MIMO network is investigated. Three different precoding schemes, which are based on zero-forcing (ZF), minimum mean square error (MMSE) and maximum SLR criteria, are proposed. The simulation results show that the proposed precoding schemes are very efficient and can provide good performance for the considered MIMO network.

In this paper, we propose an improved precoding scheme using interference alignment on modulation signal for multi-user MIMO downlink transmission. The simulation shows that the new precoding scheme can significantly reduce interference and provide much better bit error rate performance than the conventional precoding schemes for multi-user MIMO.

In this paper, we propose a new interference alignment (IA) scheme designing jointly the linear transmitter and receiver for the 2 user MIMO X channel system, using minimum total mean square error criterion, subject to each transmitter power constraint. Considering the channel estimation errors, we further propose a robust design for the IA. Iterative method is used to obtain the optimal solutions. Simulation results show that the proposed schemes outperform the existing with fast convergence.

In this paper, we propose an improved precoding scheme using interference alignment on modulation signal for multi-user MIMO downlink transmission. The simulation shows that the new precoding scheme can significantly reduce interference and provide much better bit error rate performance than the conventional precoding schemes for multi-user MIMO.