Time-Efficient resource allocation algorithm over HSDPA in femtocell networks

This paper presents a time-efficient optimal resource allocation algorithm aiming to maximize the system throughput of the single-user High Speed Downlink Packet Access (HSDPA) deployed in femtocell base station. The system throughput maximization with constrained total power is rst formulated as a constrained integer programming problem. We rst prove that a two-group bit and energy allocation provides the global optimum solution in the system without multipath. We then focus on the use of the two-group allocation method over frequency selective channels. A pre-processing method was used to systematically cluster and remove channels to stop using energies over severely degraded channels with the two-group allocation approach. This improves the system throughput whilst greatly reducing the computation complexity. The proposed twogroup approach with channel removal is suitable for femtocell base station with limited signal processing capability.Accepted versio

Modulation-mode and power-assignment for SVD-and GMD-assisted downlink MIMO systems

Multiuser multiple-input multiple-output (MIMO) downlink (DL) transmission schemes experience both multiuser interference (MUI) as well as inter-antenna interference. However, instead of treating all the users jointly as in zero-forcing (ZF) multiuser transmission techniques, the investigated singular value decomposition (SVD) and geometric mean decomposition (GMD) assisted DL multiuser MIMO systems take the individual user's channel characteristics into account. The performed joint optimization of the number of activated MIMO layers and the number of bits per symbol along with the appropriate allocation of the transmit power shows that not necessarily all user-specific MIMO layers have to be activated in order to minimize the overall BER under the constraint of a fixed data throughpu

Power allocation in wireless multi-user relay networks

In this paper, we consider an amplify-and-forward wireless relay system where multiple source nodes communicate with their corresponding destination nodes with the help of relay nodes. Conventionally, each relay equally distributes the available resources to its relayed sources. This approach is clearly sub-optimal since each user experiences dissimilar channel conditions, and thus, demands different amount of allocated resources to meet its quality-of-service (QoS) request. Therefore, this paper presents novel power allocation schemes to i) maximize the minimum signal-to-noise ratio among all users; ii) minimize the maximum transmit power over all sources; iii) maximize the network throughput. Moreover, due to limited power, it may be impossible to satisfy the QoS requirement for every user. Consequently, an admission control algorithm should first be carried out to maximize the number of users possibly served. Then, optimal power allocation is performed. Although the joint optimal admission control and power allocation problem is combinatorially hard, we develop an effective heuristic algorithm with significantly reduced complexity. Even though theoretically sub-optimal, it performs remarkably well. The proposed power allocation problems are formulated using geometric programming (GP), a well-studied class of nonlinear and nonconvex optimization. Since a GP problem is readily transformed into an equivalent convex optimization problem, optimal solution can be obtained efficiently. Numerical results demonstrate the effectiveness of our proposed approach

Energy-Efficient Heterogeneous Cellular Networks with Spectrum Underlay and Overlay Access

In this paper, we provide joint subcarrier assignment and power allocation schemes for quality-of-service (QoS)-constrained energy-efficiency (EE) optimization in the downlink of an orthogonal frequency division multiple access (OFDMA)-based two-tier heterogeneous cellular network (HCN). Considering underlay transmission, where spectrum-efficiency (SE) is fully exploited, the EE solution involves tackling a complex mixed-combinatorial and non-convex optimization problem. With appropriate decomposition of the original problem and leveraging on the quasi-concavity of the EE function, we propose a dual-layer resource allocation approach and provide a complete solution using difference-of-two-concave-functions approximation, successive convex approximation, and gradient-search methods. On the other hand, the inherent inter-tier interference from spectrum underlay access may degrade EE particularly under dense small-cell deployment and large bandwidth utilization. We therefore develop a novel resource allocation approach based on the concepts of spectrum overlay access and resource efficiency (RE) (normalized EE-SE trade-off). Specifically, the optimization procedure is separated in this case such that the macro-cell optimal RE and corresponding bandwidth is first determined, then the EE of small-cells utilizing the remaining spectrum is maximized. Simulation results confirm the theoretical findings and demonstrate that the proposed resource allocation schemes can approach the optimal EE with each strategy being superior under certain system settings