In 3G and 4G eras, many mobile communication services were initially created for users to consume content rather than generate it. Thus, the network traffic in the downlink (DL) tended to be much larger than that in the uplink (UL). As such, traditional networks were designed to mainly maximize DL capacity. However, with the rise of a new trend of user-centric wireless services and applications, the demand for the UL capacity is expected to intensify . A prominent factor that restricts the UL capacity in heterogeneous networks (HetNets) is the UL and DL imbalance problem. As there is a clear disparity between the transmission powers of the macro cells (MCells) and small cells (SCells), the best serving cell per user may be different in the UL and DL directions; hence, if the UL and DL associations are coupled, the UL capacity may be severely limited, and this problem will become even worse when the operating frequency increases. A potential solution to alleviate such a predicament is the DL/UL decoupling (DUDe) technique , which allows users to connect to different BSs at different frequency bands in the UL and DL to maximize the link capacity in each direction. DUDe not only shortens the distance between the user equipments (UEs) and serving base stations (BSs), but also makes better use of the spectral resources of SCells. Most studies of DUDe are based on the minimum path-loss (Min-PL) cell association scheme, which chooses the BS with the minimum path-loss in the UL. However, it does not take the cell loads into consideration and cannot make full use of the network resource. Thus, this thesis first considers decoupling the UL and DL BS from the perspective of maximizing network capacity. Moreover, the increasing desire to incorporate millimeter-wave (mmWave) communications and multi-connectivity in future networks further enriches the possibilities to achieve higher capacities, and they have potential to combine with DUDe to get better performance. MmWave communication is restricted by the high penetration and path loss, but DUDe can shorten the distance between UEs and their serving BSs in the UL, thus enriching the coverage of mmWave cells. As for multi-connectivity, it is highly controversial to adopt dual connectivity in the UL since the transmission power of a UE is much lower than that of a BS. However, DUDe makes it more power-efficient in the UL and brings a solution to this problem. Considering all those things, this thesis investigates the merits of adopting DUDe capacity-based multi-association in the ultra-high frequency (UHF) and mmWave hybrid networks, where mobile users may simultaneously connect to multiple different UHF SCells, mmWave SCells and/or UHF MCells. Apart from DUDe, mmWave communications, and multi-connectivity, another way to improve the network capacity is device-to-device (D2D) communication. It is more flexible than traditional cellular communication, and is a potential enabler for the Internet of Things (IoT) networks. However, D2D communication also increases the complexity and heterogeneity of the network structure, and bring challenges for interference management. As such, DUDe facilitates a more benign environment for D2D receivers by lowering the cellular user (CUE) UL transmission power, which results in less interference, and enables more D2D transmissions. To this end, we investigate the application of DUDe in D2D-underlay heterogeneous networks, and propose an efficient joint cell-association, subchannel allocation, and power control scheme for network sum-rate maximization. This thesis also investigates the potential of DUDe in cellular-enabled unmanned aerial vehicle (UAV) communication networks. Integrating UAVs with cellular networks is considered pivotal to tapping into new business opportunities for cellular operators, especially as the smartphone market is almost saturated. In this thesis, we propose a DUDe scheme for efficiently integrating UAVs within 5G cellular systems, where the UAVs' control and non-payload communication (CNPC) links, as well as the ground user (GUE) uplinks and downlinks, are decoupled from the perspectives of serving BSs and operating frequency bands. Moreover, as battery life is a major constraint for UL transmissions, an optimal power allocation algorithm based on fractional programming and successive convex approximation, and two algorithms based on Q-learning (QL) and deep Q-learning (DQL) are proposed for optimizing the EE of this DUDe scheme. Lastly, this thesis analyzes the application of DUDe to mobile edge computing (MEC). MEC is a key player in low latency 5G networks, particularly for resolving the conflict between computationally-intensive mobile applications and resource-limited mobile devices (MDs). As such, there has been intense interest in this topic. Generally, computational task offloading is limited by the type of MD-BS association with almost all previous works considering offloading an MD's computational task to the MEC servers attached to its serving BS. In multi-BS association, or DUDe scenarios, however, one MD can have multiple serving BSs, and hence more offloading choices can be exploited. Motivated by this, the thesis considers the communication and computational disparity of small BS (SBS) and macro BS (MBS) cloudlets with the objective to optimize the system performance subject to certain quality-of-service requirements. Specifically, a joint BS association and subchannel allocation algorithm, based on a student-project allocation (SPA) matching model and an optimal power allocation scheme, are proposed to minimize the network sum-latency.