Performance study of an underlay cognitive radio network in the presence of co-channel interference

PhD ThesisMassive innovation in all aspects of the wireless communication network has been witnessed over the last few decades. The demand for data throughput is continuously growing, as such, the current regulations for allocating frequency spectrum are not able to respond to this exponential growth. Cognitive radio (CR), has been proposed as a solution to this problem. One of the possible scenarios of the implementation of CR is underlay cognitive radio. In this thesis the performance of an underlay cognitive radio network (UCRN) in the presence of the co-channel interference (CCI) is assessed. Firstly, the impact of CCI on the dual-hop cooperative UCRN is investigated over Rayleigh fading channels. In order to do this, the exact outage probability (OP), average error probability (AEP) and the ergodic capacity (EC) are studied. In addition, simple and asymptotic expressions for the OP and AEP are derived. Furthermore, the optimal power allocation is investigated to enhance the network performance. Moreover, the performance of a multi-user scenario is studied by considering the opportunistic SNR-based selection technique. Secondly, the effect of both primary network interference and CCI on the dual-hop UCRN over Rayleigh fading channels are studied. The equivalent signal-to-interference-plus-noise ratio (SINR) for this network scenario is obtained by considering multi-antenna schemes at all receiver nodes. The different signal combinations at the receiver nodes are investigated and compared, such as selection combining (SC) and maximum ratio combining (MRC) techniques. Then, the equivalent probability density function (PDF) and cumulative distribution function (CDF) of the network’s equivalent SINR are derived and discussed. Furthermore, expressions for the exact OP, AEP, and EC are derived and reviewed. In addition, asymptotic OP expressions are obtained for different case scenarios to gain an insight into the network parameters. Thirdly, multiple-input multiple-output (MIMO) UCRN is investigated under the influence of primary transmitter interference and CCI over Rayleigh fading channels. The transmit antenna selection and maximum ratio combining (TAS/MRC) techniques are considered for examining the performance of the secondary network. At first the equivalent SINR for the system is derived, then the exact and approximate expressions for the OP are derived and discussed. Fourthly, considering Nakagami-m fading channels, the performance of the UCRN is thoroughly studied with the consideration of the impact of primary network interference and CCI. The equivalent SINR for the secondary system is derived. Then, the system equivalent PDF and CDF are derived and discussed. Furthermore, the OP and AEP performances are investigated. Finally, for the cases mentioned above, numerical examples in conjunction with MatLab Monte Carlo simulations are provided to validate the derived results. The results show that CCI is one of the factors that severely reduces the UCRN performance. This can be more observable when the CCI power increases linearly with the transmission power of the secondary transmitter nodes. Furthermore, it was found that in a multi-user scenario the opportunistic SNR-based selection technique consideration can improve the performance of the network. Moreover, adaptive power allocation is found to give better results than equal power allocation. In addition, cooperative communication can be considered to be an effective way to combat the impact of transmission power limitation of the secondary network and interference power constraint. The multi-antenna schemes are another important consideration for enhancing the overall performance. In fact, despite the interference from the CCI and primary user sources, the multi-antennas scheme does not lose its advantage in the UCRN performance improvementHigher Committee for Education Development in Iraq (HCED). I am also grateful to the Ministry of Transportation and Communication, Kurdistan Regional Government-Iraq

Performance analysis of diversity techniques in wireless communication systems: Cooperative systems with CCI and MIMO-OFDM systems

This Dissertation analyzes the performance of ecient digital commu- nication systems, the performance analysis includes the bit error rate (BER) of dier- ent binary and M-ary modulation schemes, and the average channel capacity (ACC) under dierent adaptive transmission protocols, namely, the simultaneous power and rate adaptation protocol (OPRA), the optimal rate with xed power protocol (ORA), the channel inversion with xed rate protocol (CIFR), and the truncated channel in- version with xed transmit power protocol (CTIFR). In this dissertation, BER and ACC performance of interference-limited dual-hop decode-and-forward (DF) relay- ing cooperative systems with co-channel interference (CCI) at both the relay and destination nodes is analyzed in small-scale multipath Nakagami-m fading channels with arbitrary (integer as well as non-integer) values of m. This channel condition is assumed for both the desired signal as well as co-channel interfering signals. In addition, the practical case of unequal average fading powers between the two hops is assumed in the analysis. The analysis assumes an arbitrary number of indepen- dent and non-identically distributed (i.n.i.d.) interfering signals at both relay (R) and destination (D) nodes. Also, the work extended to the case when the receiver employs the maximum ratio combining (MRC) and the equal gain combining (EGC) schemes to exploit the diversity gain

BER Performance Improvement in UWA Communication via Spatial Diversity

In present era while wireless communication has become an integral part of our life, the advancements in underwater communications (UWA) is still seem farfetched. Underwater communication is typically essential because of its ability to collect information from remote undersea locations. It don’t use radio signals for signal transmission as they can propagate over extremely short distance because of degradation in signal strength due to salinity of water, rather it uses acoustic waves. The underwater acoustic channel has many characteristics which makes receivers very difficult to be realized. Some of the characteristics are frequency dependent propagation loss, severe Doppler spread multipath, low speed of sound. Due to motion of transmitter and receiver the time variability and multipath makes underwater channel very difficult to be estimated. There are various channel estimation techniques to find out channel impulse response but in this thesis we have considered a flat slow fading channel modeled by Nakagami-m distribution. Noise in underwater communication channel is frequency dependent in nature as for a particular range of frequency of operation one among the various noise sources will be dominant. Here they don’t necessarily follow Gaussian statistics rather follows Generalized Gaussian statistics with decaying power spectral density. The flexible parametric form of this statistics makes it useful to fit any source of underwater noise source. In this thesis we have gone through two step approach. In the first step, we have considered transmission of information in presence of noise only and designed a suboptimal maximum likelihood detector. We have compared the performance of this proposed detector with the conventional Gaussian detector where decision is taken based on a single threshold value and the threshold value is calculated by using various techniques. Here it is being observed that the ML detector outperforms the Gaussian detectors and the performance can be improved further by exploiting the multipath components. In the second step we have considered channel along with noise and have designed a ML detector where we have considered the receiver is supplied with two copies of the same transmitted signal and have gone through a two-dimensional analysis. Again we compared the performance with conventional maximal ratio combiner where we can observe the ML detector performance is better. Further we have incorporated selection combining along with these detectors and compared the performance. Simulation results shows that the proposed detector always outperforms the existing detectors in terms of error performance