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The continuous growth of high data rates with huge increase in the number of mobile devices and communication infrastructure have led to greenhouse gas emission, higher pollution and higher energy costs. After the deployment of 4G and immense data rate and QoS requirements for 5G, there is an urgent need to design future wireless systems that aim to improve energy efficiency (EE) and spectral efficiency (SE). One of the possible solutions is to use energy harvesting (EH), which promises to reduce energy consumption issues in information and communication technology sector. In order to tackle these challenges, this thesis is focused on the design and performance analysis of EH systems. EH has emerged as a potential candidate for green wireless communication which not only provides solution to the energy limitation problem but also prolongs the lifetime of batteries. First, the performance evaluation of an EH-equipped dual-hop relaying system is proposed to improve the system throughput and the end-to-end signal-to-noise ratio (SNR). We derive novel closed-form expressions for cumulative distribution function of individual link's SNR and of the end-to-end SNR. In addition, the proposed model analyses the ergodic capacity which is an important performance metric for delay-sensitive services. Further, these closed-form expressions reduce the computational complexity of the receiver architecture for practical systems. An insight through system parameters provide significant improvement in end-to-end SNR especially when both transmitter and relay nodes are equipped with harvesting sources. Second, performance analysis and optimal transmission power allocation techniques for EH-equipped system are studied. Our proposed model investigates and provides the conditions under which the harvesting can improve the system performance. In this work, novel closed-form expressions are calculated for the maximum achievable EE, SE and EH beneficialness condition. We studied two cases such as power is adapted to variations in the channel and when transmit power is fixed. We proved that EE-optimum input power decreases with EH power level. Also, system parameters demonstrate the conditions under which EH improves overall system performance. Finally, a multi-objective optimization problem is formulated that jointly maximizes EE and SE for point-to-point EH-equipped system. We introduce new importance weight which set the priority levels of EE versus SE of the system. The formulated problem is solved by using convex optimization method to achieve optimal solution. The proposed system model provides freedom to choose any value for importance weight to satisfy quality of service (QoS) requirements and the flexibility of balancing between EE and SE performance metrics.