Performance Analysis of Cognitive Radio Systems under QoS Constraints and Channel Uncertainty

In this paper, performance of cognitive transmission over time-selective flat fading channels is studied under quality of service (QoS) constraints and channel uncertainty. Cognitive secondary users (SUs) are assumed to initially perform channel sensing to detect the activities of the primary users, and then attempt to estimate the channel fading coefficients through training. Energy detection is employed for channel sensing, and different minimum mean-square-error (MMSE) estimation methods are considered for channel estimation. In both channel sensing and estimation, erroneous decisions can be made, and hence, channel uncertainty is not completely eliminated. In this setting, performance is studied and interactions between channel sensing and estimation are investigated. Following the channel sensing and estimation tasks, SUs engage in data transmission. Transmitter, being unaware of the channel fading coefficients, is assumed to send the data at fixed power and rate levels that depend on the channel sensing results. Under these assumptions, a state-transition model is constructed by considering the reliability of the transmissions, channel sensing decisions and their correctness, and the evolution of primary user activity which is modeled as a two-state Markov process. In the data transmission phase, an average power constraint on the secondary users is considered to limit the interference to the primary users, and statistical limitations on the buffer lengths are imposed to take into account the QoS constraints of the secondary traffic. The maximum throughput under these statistical QoS constraints is identified by finding the effective capacity of the cognitive radio channel. Numerical results are provided for the power and rate policies

Bandwidth-efficient pilot-symbol-aided technique for multipath-fading channels

Pilot-symbol-aided (PSA) transmission is one of the effective methods to combat multipath fading in digital mobile communications systems. In the PSA systems, redundant bandwidth and power are required to transmit the pilot symbols. In this paper, we propose a novel fading estimation technique that requires a very low bandwidth redundancy in the PSA systems. The proposed technique uses simple linear interpolation on the pilot symbols and the detected data symbols to obtain the estimates of the channel fading effects. Monte Carlo computer simulation has been carried out to study the effects of the technique on the bit error rate performance of 16-ary quadrature amplitude modulation in the flat and the frequency-selective Rayleigh-fading channels corrupted with cochannel interference and additive white Gaussian noise. Results have shown that the proposed technique can, at the expense of a little power efficiency, significantly improve the bandwidth efficiency of the PSA systems using receivers with low com plexity and latency.published_or_final_versio

Hybrid solutions to instantaneous MIMO blind separation and decoding: narrowband, QAM and square cases

Future wireless communication systems are desired to support high data rates and high quality transmission when considering the growing multimedia applications. Increasing the channel throughput leads to the multiple input and multiple output and blind equalization techniques in recent years. Thereby blind MIMO equalization has attracted a great interest.Both system performance and computational complexities play important roles in real time communications. Reducing the computational load and providing accurate performances are the main challenges in present systems. In this thesis, a hybrid method which can provide an affordable complexity with good performance for Blind Equalization in large constellation MIMO systems is proposed first. Saving computational cost happens both in the signal sep- aration part and in signal detection part. First, based on Quadrature amplitude modulation signal characteristics, an efficient and simple nonlinear function for the Independent Compo- nent Analysis is introduced. Second, using the idea of the sphere decoding, we choose the soft information of channels in a sphere, and overcome the so- called curse of dimensionality of the Expectation Maximization (EM) algorithm and enhance the final results simultaneously. Mathematically, we demonstrate in the digital communication cases, the EM algorithm shows Newton -like convergence.Despite the widespread use of forward -error coding (FEC), most multiple input multiple output (MIMO) blind channel estimation techniques ignore its presence, and instead make the sim- plifying assumption that the transmitted symbols are uncoded. However, FEC induces code structure in the transmitted sequence that can be exploited to improve blind MIMO channel estimates. In final part of this work, we exploit the iterative channel estimation and decoding performance for blind MIMO equalization. Experiments show the improvements achievable by exploiting the existence of coding structures and that it can access the performance of a BCJR equalizer with perfect channel information in a reasonable SNR range. All results are confirmed experimentally for the example of blind equalization in block fading MIMO systems

A Study of Channel Estimation in Multi-Band OFDM UWB Systems

In this paper, the channel estimation techniques for multiband (MB) OFDM ultra-wideband (UWB) wireless communications are investigated. By combining orthogonal frequency-division multiplexing (OFDM) with multi-band, the MB-OFDM systems can capture multipath energy more efficiently than single-band direct sequence UWB (DS-UWB). However, most researches for UWB channel estimation are focused on the latter. Through the analysis of architecture, signal and channel model of MB-OFDM UWB wireless systems, we studied the channel estimation techniques based on preamble training sequences and pilot sub-carriers respectively. Further more, the linear estimations of least square (LS) and minimum mean square error (MMSE) are analysed and compared under different UWB channel conditions. The characteristic of estimation error changing with the SNR is also discussed. The estimation error includes the impact of interpolation error and channel noise