Research On Efficient Receivers In Multi-carrier And Non-orthogonal Multiple Access Wireless Communication Systems

The 5G wireless communication networks aim to facilitate a step change in the volume and quality of wireless service,such as enhanced mobile broadband,massive Machine-TypeCommunications(MTC),and ultra-reliable-low-latency data transfer.The existing orthogonal multi-carrier modulation and orthogonal multiple access technologies cannot meet the requirements for high speed,low latency and ultra-large scale reliable connectivities in 5G.In particular,generalized frequency division multiplexing(GFDM)and non-orthogonal multiple access(NOMA)have received a lot of attention due to their flexible system configuration and high spectrum utilisation.Meanwhile,the next generation communication system puts forward higher requirements for system performance and transmission efficiency,which poses new challenges for efficient receiver design.Therefore,this thesis focuses on the design of receivers in the presence of I/Q imbalance in GFDM systems,the non-perfect characteristics of interference cancellation receivers in power domain NOMA systems and the high complexity of message passing algorithm receivers in code domain NOMA systems.The main contributions of this dissertation are listed as follows:1.Physical distortions,such as in-phase and quadrature(I/Q)imbalance caused by the imperfections of radio frequency(RF)components within direct-conversion transceivers(DCTs),may cause severe performance degradation in GFDM based wireless systems.To this end,we first conduct a rigorous sum rate analysis to quantify the impact of I/Q imbalance in both the transmitter(Tx)and the receiver(Rx)on the GFDM wireless transmission.An efficient I/Q imbalance compensation scheme is next proposed based on pilots? this is achieved through a nonlinear least squares(NLS)analysis of the joint channel and I/Q imbalance estimation,and a simple symbol detection procedure.For rigor,the Cramer-Rao lower bounds(CRLBs)for both the I/Q imbalance parameters and the channel coefficients are also derived.Simulation results illustrate that the mean square error(MSE)performance of the proposed estimator closely approaches the corresponding CRLB over static frequency selective channels,thus significantly reducing the sensitivity of GFDM DCTs to physical I/Q impairments.2.Like the standard OFDM,the direct-conversion receivers of Generalized frequency division multiplexing(GFDM)are vulnerable to radio frequency impairments,due to their cost and size constraints.In this sense,the performance deterioration resulting from inphase/quadrature(I/Q)imbalance is first analyzed in terms of signal-to-interference plusnoise ratio(SINR)for typical GFDM receivers.Next,a blind adaptive I/Q imbalance compensator based on normalized complex least mean square(NCLMS),originally designed for OFDM receivers,is extended for GFDM ones.In order to provide more physical insight into its compensation capability,a full second order performance assessment is established,via a joint consideration of the weight error variance and its complementary variance of the proposed compensator in both the transient and steady-state stages.Apart from an accurate evaluation on its overall self-image attenuation performance,the proposed full second order analysis is also able to quantify the individual contributions from both the I and Q channels of the compensator,an important finding missing in the literature and not possible to discover by using the standard variance analysis only.This analysis also facilitates theoretical quantifications of SINR improvements by NCLMS for GFDM receivers.Simulations on GFDM waveforms support the analysis.3.The achievable rate improvement for the downlink NOMA system,in the context of imperfect successive interference cancellation(SIC),by means of the improper Gaussian signaling(IGS)technique,is addressed.A basic scenario where the strong user transmits the conventional proper data,while the weak user adopts an improper signaling scheme,is investigated.The users’ data rates are first formulated in terms of the impropriety degree of the improper signaling,under residual interference introduced by the imperfect SIC.In this way,analytical expressions for the best improper transmission can be characterized by jointly optimizing the user’s power and the impropriety degree,where their sufficient and necessary conditions are provided.When the strong user transmits with its maximum power,the improper signaling scheme always increases the achievable rate of the strong user while the weak user may also benefit.When the weak user transmits with its maximum power,such a scheme enables us optimize the achievable rate of the strong user under various levels of channel-to-noise ratios(CNR)and imperfect SIC.Finally,when both the users are imposed by quality of service(Qo S)constraints,a Q-learning based solution is proposed to maximize their sum rate.Simulations on the downlink NOMA system support the analysis.4.The computational complexity of the conventional message passing algorithm(MPA)for the multiuser Sparse code multiple access detection increases exponentially with the degree of resource nodes(RNs).To address this issue,two low complexity MPA schemes are proposed by utilizing the sparse feature of codewords.First,a sorted MPA(SMPA)detector is introduced to reduce the message exchanging from RNs to variable nodes(VNs)by dropping the redundant superposed constellation points outside a belief interval.Next,in order to further speed up the sorting process of the Euclidean distances between the received signal and codeword combinations,a deep neural network aided MPA(DNNMPA)is proposed,in which,the DNN behaves as a function approximator to generate the belief interval and operates in parallel with the initialization procedure before iterative message passing.Simulation results illustrate that the proposed SMPA and DNNMPA detectors significantly reduce the computational complexity of the conventional MPA one,but with comparable decoding capabilities,for the uplink NOMA system.5.The high computational complexity of the conventional message passing algorithm(MPA)for the downlink MIMO-NOMA detection remains a big concern for its practical application.The serial schedule strategy based MPA helps to accelerate the convergence rate of the original one.To further reduce the computation,two novel fixed low complexity MPA detectors are proposed by utilizing the sparse feature of codewords.First,a maximum distance MPA(MDMPA)detector is introduced to reduce the number of variable nodes(VNs)involved in the messge updating procedure in the first T0 iterations and fix T J0 codewords at the L0 iteration,which subsequently drops the redundant codeword combinations in the remaining iterations.Next,in order to improve the bit error ratio(BER)performance,an improved MDMPA(IMDMPA)is proposed,in which,the VNs associated with the target user are always allowed to participate in the iterative propagation of message.An efficient linear squares(LS)channel estimation scheme is also derived based on block pilots by stacking all the received signals at the same subcarrier together.Simulation results illustrate that the proposed MDMPA and IMDMPA detectors significantly reduce the computational complexity of the original MPA,but with comparable decoding capabilities,and the proposed LS channel estimator closely approaches the corresponding lower bound over frequency selective channels.