As an emerging short-range wireless technology, IEEE 802.15.4/ZigBee Wireless Sensor Networks (WSNs) are increasingly used in the fields of home control, industrial control, consumer electronics, energy management, building automation, telecom services, personal healthcare, etc. IEEE 802.15.4/Zig-Bee WSNs share the same 2.4 GHz license-free Industrial, Scientific, and Medical (ISM) band with many other wireless systems such as IEEE 802.11b/g WLANs, Bluetooth, cordless phones, etc. Due to the low power, IEEE 802.15.4/ZigBee WSNs are potentially more vulnerable to interference by those systems. Among those systems, IEEE 802.11b/g WLANs are probably the most widely deployed ones. Because of their complementary applications, IEEE 802.15.4WSNs and IEEE 802.11b/gWLANs are often colocated, which causes the coexistence issue between them. In this thesis, we focus on the coexistence between IEEE 802.15.4/ZigBee WSNs and IEEE 802.11b/g WLANs. The targets of this thesis work are to achieve a clear understanding on the coexistence issue between IEEE 802.15.4/ZigBee WSNs and IEEE 802.11b/g WLANs, and then to propose cost-effective methods to enhance the coexistence capability of IEEE 802.15.4/ZigBee WSNs. Although many studies on the coexistence issue between IEEE 802.15.4/Zig-Bee WSNs and IEEE 802.11b/g WLANs have been done, the conclusions they drew are incomplete and/or conflicting, and therefore confusing. To get a clear understanding about the coexistence issue between them, an extensive study is needed. First, we propose a coexistence model of IEEE 802.15.4 nodes and IEEE 802.11b/g nodes. The model is based on two aspects, i.e., power and the timing. Due to the significant difference in transmit powers of IEEE 802.15.4 and IEEE 802.11b/g, the sensing ranges of them are quite asymmetric. As a result, three distinct coexistence regions can be identified. In each of these coexistence regions, IEEE 802.11 nodes and IEEE 802.15.4 nodes exhibit different interactive behavior and hence different coexistence performances, which may not be the same as we expected. For example, instinctively, we may feel that the closer an IEEE 802.15.4 node gets to an IEEE 802.11b/g interferer, the worse performance the IEEE 802.15.4 node would have. Our coexistence model, however, reveals that this perception is not true. In fact, as the IEEE 802.15.4 node and the IEEE 802.11b/g interferer get so close that they are in the coexistence region R1, where they can sense each other, the coexistence performance of the IEEE 802.15.4 node is not necessarily the worst. Instead, in the coexistence region R2, where the IEEE 802.11b/g interferer cannot sense the IEEE 802.15.4 and therefore does not respect the IEEE 802.15.4 transmission, the coexistence performance of the IEEE 802.15.4 node could get even worse than in R1. Clearly, the three coexistence regions and the different interactive behavior between IEEE 802.15.4 WSNs and IEEE 802.11b/g WLANs in each region explain the incomplete/conflicting conclusions drawn by many previous studies from their incomplete analysis and/or observations. Next, by taking into account some important implementation factors, we improved the coexistence model and studied the coexistence performance of IEEE 802.15.4 WSNs under IEEE 802.11b/g interference in a real-life environment. We revealed that some implementation factors such as IEEE 802.15.4 Rx-to-Tx turnaround time and Clear Channel Assessment (CCA) partial detection effect can have significant impact on IEEE 802.15.4 WSNs coexistence performance in reality, e.g., a long IEEE 802.15.4 Rx-to-Tx turnaround time can impair the CCA performance and therefore the IEEE 802.15.4 WSNs coexistence performance. The enhanced model can precisely explain and predict the IEEE 802.15.4WSNs coexistence performance. Furthermore, under the guidance of the model, the IEEE 802.15.4 WSNs coexistence performance were extensively investigated in all of the three coexistence regions in different scenarios by analysis, simulation and experiments. The simulation and experimental results agree with our analysis. Based on the clear understanding achieved from the work above, we then explore the solutions to help IEEE 802.15.4 WSNs deal with interference. Basically, there are two categories for the ways of dealing with interference: interference control/mitigation and interference avoidance. We address solutions in each of these two categories, respectively. We first propose an interference mitigation approach, which enables an IEEE 802.15.4 WSN to mitigate heavy interference by adaptively adjusting CCA thresholds of its nodes in a distributed manner. As the heavy interference appears, the CCA thresholds are increased in order to reduce the inhibition loss, whereas the CCA threshold gets decreased so as to avoid having a permanent channel access privilege over peers as the interference disappears. Compared to the centralized interference management approaches, e.g., the frequency agility approach specified in the ZigBee specification, which inappropriately assumes a reliable two-way communication between nodes even in the presence of heavy interference, our adaptive CCA approach is simpler but more robust, more responsive, and easier to be implemented at a lower cost. The simulation results validate that the adaptive CCA approach may significantly improve IEEE 802.15.4 WSNs performance in the presence of heavy interference. Then, we consider an interference avoidance solution. ZigBee specification proposes a feature called frequency agility, which refers to the ability of ZigBee networks to change the operational channel in the presence of interference. However, for a large-scale ZigBee network, changing the whole network operational channel to an idle one, may be neither appropriate if there is only local interference nor possible if there is no single idle channel available globally. Therefore, we propose a distributed adaptive interference-avoidance multi-channel protocol, which enables a conventional single-channel largescale ZigBee network to distributively, adaptively and partially change the operational channel in the presence of local interference. As a result, the Zig-Bee network performance under interference can be effectively and efficiently improved. The main contributions of this thesis are a coexistence model of IEEE 802.15.4/ZigBee WSNs and IEEE 802.11b/g WLANs, and two solutions to the coexistence issue between them. The model not only explains the interesting interactive coexistence behavior of the two systems, but provides many insights on the coexistence issue. Under the guidance of those insights, two solutions are proposed. The solutions can enhance the coexistence capability of IEEE 802.15.4/ZigBee WSNs and therefore their coexistence performance in the presence of interference, which includes but not limited to IEEE 802.11b/g interference.