This thesis studies a two-way relay network (TWRN), which consists of two single antenna source nodes and a multi-antenna relay node. The source nodes exchange information via the assistance of the relay node in the middle. The relay scheme in this TWRN is amplify-and-forward (AF) based analog network coding (ANC). A robust beamforming matrix optimization algorithm is presented here with the objective to minimize the transmit power at the relay node under given signal to interference and noise ratio (SINR) requirements of source nodes. This problem is first formulated as a non-convex optimization problem, and it is next relaxed to a semi-definite programming (SDP) problem by utilizing the S-procedure and rank-one relaxation. This robust beamforming optimization algorithm is further validated in a MATLAB-based orthogonal frequency-division multiplexing (OFDM) MIMO two-way relay simulation system. To better investigate the performance of this beamforming algorithm in practical systems, synchronization issues such as standard timing offset (STO) and carrier frequency offset (CFO) are considered in simulation. The transmission channel is modeled as a frequency selective fading channel, and the source nodes utilize training symbols to perform minimum mean-square error (MMSE) channel estimation. BER curves under perfect and imperfect synchronization are presented to show the performance of TWRN with ANC. It is shown that the outage probability of robust beamforming algorithm is tightly related to the SINR requirements at the source nodes, and the outage probability increases significantly when the SINR requirements are high.

Orthogonal frequency division multiplexing (OFDM) has become a popular modulation method in high-speed wireless communications. By partitioning a wideband fading channel into flat narrowband channels, OFDM is able to mitigate the detrimental effects of multipath fading using a simple one-tap equalizer. However, in the time domain OFDM signals suffer from large envelope variations, which are often characterized by the peak-to-average ratio (PAR). High PAR signals, like OFDM, require that transmission amplifiers operate at very low power efficiencies to avoid clipping. In this thesis we review the most popular OFDM PAR-reduction techniques and demonstrate that selected mapping (SLM) is a particularly promising reduction technique. In a SLM system, an OFDM symbol is mapped to a set of quasi-independent equivalent symbols and then the lowest-PAR symbol is selected for transmission. The tradeoff for PAR reduction in SLM is computational complexity as each mapping requires an additional inverse fast fourier transform (IFFT) operation in the transmitter. In additional to an overview of current SLM work, we present a thorough analysis of SLM as well as several novel SLM proposals. First, we derive the closed-form expression for the expected PAR in an SLM system. The expected PAR can be thought of as a metric of PAR reduction capability. Second, we provide a power analysis of SLM to determine if the computational power costs outweigh the power saved through PAR reduction. Through this analysis, we show that SLM is capable of several Watts of net power savings when used in a wireless transmission system. Third, we propose that a PAR threshold should be set in SLM. Such thresholding leads to significant complexity decreases. Fourth, we derive the maximum likelihood (ML) and maximum extit{a posteriori} (MAP) detection metrics for blind SLM (BSLM) and threshold BSLM respectively. Lastly, we demonstrate that by using monomial phase sequences in SLM blind phase sequence detection is possible with a single FFT operation in the receiver.

In this thesis, we investigate a wireless communications system with distributed transmit antennas. Under such system scenario, the received signal has multiple carrier frequency offsets (CFOs) since each transmitter has its own oscillator, leading to serious inter-carrier interference (ICI) at the receiver end. Therefore, an ICI self-cancellation scheme is proposed in this thesis, where two different relay nodes use different sub-carriers. When the signals from different relay nodes are combined at the destination node, the ICI self-cancellation can be achieved. In addition, the quality of the received signal can be further improved if the residual CFO can be properly compensated. Traditionally, the medium value of the various CFOs is taken for compensation because of its simplicity. However, a medium value does not result in the optimal performance. In this thesis, a close form expression of optimal CFO is derived to maximize the average signal to interference power ratio. It is shown that the optimal CFO compensation is a function of channel state and individual CFOs. Simulation experiments are conducted to investigate the performance of the proposed scheme. It is shown that the system bit error rate can be substantially improved when the CFO is less than 0.3 subcarrier spacing.

High peak to average power ratio (PAPR) is one of the major drawbacks in orthogonal frequency division multiplexing (OFDM) systems. In recently years, various methods have been proposed to reduce the PAPR performance. The selected mapping (SLM) scheme is perhaps the most popular one because it provides outstanding PAPR reduction performance. In addition, the subcarrier magnitude remains the same in the SLM scheme. However, there are two major shortcomings in the SLM scheme. First of all, it requires a number of inverse fast Fourier transforms (IFFTs) to produce candidate signals, dramatically increasing the computational complexity. In addition, side information has to be transmitted to the receiver to indicate the candidate signal that results in the best PAPR, leading to the decrease in bandwidth utilization. To overcome these two drawbacks, this thesis proposes a novel SLM scheme that does not need side information. The proposed scheme is based on a low complexity SLM scheme [C.-P. Li, S.-H. Wang, and C.-L. Wang, ¡§Novel low-complexity SLM schemes for PAPR reduction in OFDM systems,¡¨ IEEE Trans. Signal Process., vol. 58, no. 5, pp. 2916¡V2921, May 2010] in pilot-aided OFDM system. Simulation experiments are conducted to verify the performance of the proposed scheme. It is shown that the bit error rate (BER) performance of the proposed scheme is very similar to that of the traditional SLM scheme with perfect knowledge of the side information. Therefore, the proposed scheme not only has the advantages of low complexity and high bandwidth utilization, but also has a superior BER performance.

High peak-to-average power ratio (PAPR) is a serious drawback in orthogonal frequency division multiplexing (OFDM) systems. Various methods have been proposed to reduce PAPR, active constellation extension (ACE) scheme has excellent performance. There are two schemes were proposed in traditional ACE, the one of which is ACE-Smart Gradient-Project (SGP) which can significantly reduce PAPR through first iteration. In fact, optimal solution is not obtained in ACE-SGP, we find the scheme can be formulated as convex optimization problem, that is, we can find out optimal solution to minimize PAPR by convex optimization algorithm. Two proposed schemes are based on two low complexity schemes, respectively, and they were proved to satisfy convex optimization problem. Although the power of transmission and complexity of optimization algorithm in the proposed schemes are higher than that of the traditional ACE-SGP scheme, but proposed schemes has proper improvement in PAPR reduction.

In this thesis, we study the noise power estimation in the LTE system. Two approaches, the weight method and the subspace method, are considered. The performance of noise power estimation using the weight method highly depends on the accuracy of the channel estimation. The channel estimation usually gets poor results under scenarios with long delay spreads. Therefore, the weight method also gets poor result. To overcome the mentioned drawback, we propose the subspace method which is independent from the channel estimation. From simulation results, we observe that the subspace method gets bias results. However, the bias depends on the length of the observation window and only gets a little influence from the channel conditions. Therefore, we can correct the bias using a simple look-up-table approach. Computer simulations show that the subspace method gets the more accurate result than the weight method.

In orthogonal frequency division multiplexing (OFDM) system, blind estimator was proposed which can obtain high bandwidth efficiently. There is a serious ambiguity problem in blind data detector structure. Solution methods can divide into three cases: pilot signal, superimposed training, and channel coding. In order to achieve totally blind estimate, we use channel coding to solve ambiguity in this thesis. In previous study, it had been use low-density-parity-check code (LDPC) to solve ambiguity, and proposed an encoding method to avoid ambiguity for BPSK. However, we consider generic linear block code (LBC) and want to extend BPSK modulation to higher modulation scheme, including QPSK, 16QAM, and 64QAM. For any constellation follows grey coding, we induct a difference of inner product for ambiguity and derive some sufficient conditions for LBC. If LBC satisfy some conditions, then it could avoid ambiguity between valid code words and it can achieve totally blind estimate. In simulation section, for data estimate, we respectively use two LBC cases, which exist ambiguity or not. In order to be fair, we insert a pilot to solve ambiguity in LBC, which exist ambiguity. In simulation results, the performance of two cases is similar in high signal to noise ratio (SNR). In other words, if we use proper channel code which it satisfy sufficient conditions, then we can increase bandwidth efficiently.

In recent years, the development of OFDM system has received a lot of attention. Some examples of existing systems where OFDM system is used are digital audio broadcasting, high-definition television terrestrial broadcasting, asymmetric digital subcarrier lines and so on. There are several reasons for using OFDM systems. First, OFDM system is an efficient way to deal with multipath effect. Under a fixed amount of delay spread, the implementation complexity of OFDM system is much less than that of single-carrier system. The reason is that OFDM system can simply use guard time to process delay spread without a complex equalizer. Second, OFDM system can achieve high data rate to transmit by using large number of subcarriers. Third, OFDM system can also efficiently combat with narrow band interference. On the other hand, OFDM system also has two main drawbacks. One is more sensitive to frequency offset, the other is higher PAPR. This thesis focuses on the PAPR problem. Pulse shaping method is an effective way to solve this problem. It can be used for any number of subcarriers of OFDM systems, so it is very flexible. It doesn¡¦t have any additional IFFTs in comparison to the selected mapping or partial transmit sequence method. Its implementation is simpler. And because it also doesn¡¦t distort the OFDM symbols, its bit error performance should be better than the clipping method. According to the pulse shaping method, we get a better waveform that can make the PAPR of OFDM symbols do not exceed about 2.

Selected mapping (SLM) schemes are commonly employed to reduce the peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. It has been shown that the computational complexity of the traditional SLM scheme can be substantially reduced by adopting conversion vectors obtained by using the inverse fast Fourier transform (IFFT) of the phase rotation vector in place of the conventional IFFT operations [21]. Unfortunately, however, the elements of these phase rotation vectors of the conversion vectors in [21] do not generally have an equal magnitude, and thus a significant degradation in the bit error rate (BER) performance is incurred. This problem can be remedied by utilizing conversion vectors having the form of a perfect sequence. This paper presents three novel classes of perfect sequence, each of which comprises certain base vectors and their cyclic-shifted versions. Three novel low-complexity SLM schemes are then proposed based upon the unique structures of these perfect sequences. It is shown that while the PAPR performances of the proposed schemes are marginally poorer than that of the traditional SLM scheme, the three schemes achieve an identical BER performance and have a substantially lower computational complexity.

Multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) technology has been used widely in many wireless communication systems. Signals will be distorted when they are transmitted in wireless channels. For the reason that wireless channel is time or location variant, we have to estimate the channel impulse response and use the channel state information to compensate the channel distortion. In order to estimate the state of the channel, let the known training symbols put in front of the data symbols and use training symbols to estimate channel response. A typical channel estimate for MIMO OFDM systems is treated as spatially uncorrelated. However in many realistic scenarios, the channel tends to be spatially correlated. Indeed, we have no prior knowledge of the channel spatial correlation. So consider the spatial correlation, the channel can estimate accurately. And it is important that how to combine spatial correlation and channel estimation to reduce the estimation error. In the paper we propose a iterative channel spatial correlation and channel estimation algorithm. At first, channel spatial correlation estimation is obtained by synchronize symbols. The receiver uses the estimated channel to help the detection/decision of data symbol. And then the channel estimation treats the detected signals as known data to perform a next stage channel estimation iteratively. By utilizing the iterative channel estimation and signal detection process we can reduce the estimation error caused by channel spatial correlation estimation. The accuracy of the channel estimation can be improved by increasing the number of iteration process. Simulation results demonstrate the iterative spatial correlation and channel estimation algorithm can provide better mean-square-error performance.