Comparison of Downlink Power Allocation Mechanisms in Soft Handoff for the WCDMA System with Heterogeneous Cell Structures

Abstract

Handoff in heterogeneous cellular networks is one of the hot topics for wireless networks beyond the third generation. We observe that a power exhausting issue may occur in a code division multiple access (CDMA) system with mixed-sized cells. During soft handoff in the downlink transmission, a number of base stations transmit signals to a user simultaneously. Usually, a microcell has a more stringent limitation on the total available power than a macrocell. Thus, ignoring the impact of various cell sizes, the traditional downlink power allocation techniques for soft handoff may easily consume excessive power to serve soft handoff users, while leaving insufficient power for serving other regular users.To resolve such an power exhausting issue in CDMA systems, we investigate different downlink power allocation techniques used in soft handoff subject to the impact of mixed-sized cells. For the single-site power allocation technique we consider the site selection diversity transmission (SSDT) technique, while for the multi-site power allocation we study the link proportional power allocation (LPPA), the quality balancing power allocation (QBPA), and the equal power allocation (EPA) techniques. We find that the multi-site LPPA technique can more efficiently allocate power to both handoff and non-handoff users than others. In an example with the ratio of the micrcocell radius/macrocell radius equal to 1/3, it is demonstrated that LPPA can improve the capacity over EPA, QBPA, and SSDT by 125, 30, and 5%, respectively. By taking account of measurement errors in the same case, the capacity improvements of LPPA over EPA, QBPA, and SSDT become 180, 41, and 23%, respectively.

A novel joint power and rate assignment algorithm in mixed-size WCDMA cellular systems

“…It can be seen that the handoff forced termination probability of JPRA is much less than those of SSDT and LPPA schemes by over 300% and around 200%, respectively. The significant gain of JPRA over LPPA comes from the rate allocation for SHO by the ECRA method, and the gain of LPPA over SSDT comes from the SHO power allocation strategy [3]. The reasons are that the allowable transmission rates are highly correlated to the feasible solutions of power allocation.…”

“…The resultant q i,h (r) is proportional to the link quality between the BTS i ∈ D h and the SHO user h [3]. That is,…”

“…If the SHO is forced to terminate, q i,h (r) of each link i in the active set D h is reset to zero. We have proven that the LPPA scheme is convergent in [3]. Here, the LPPA scheme will calculate all power allocation combinations of q i,h (r),…”

“…Generally, congested microcells, which are with stringent power budget for maximum total transmission power and maximum link power, may easily exhaust their total transmission power because of serving SHO users in the downlink [3], and then there would have no enough power resource to serve other non-handoff users in the system. When taking into account multirate services, this power exhausting problem will become more critical.…”

Reinforcement‐learning‐based self‐organisation for cell configuration in multimedia mobile networks

“…The FQ-SOC without adaptive CAC scheme is considered for comparison, in which CAC thresholds for all classes of service rates are fixed. In FQ-SOC, P I b and H S ðrÞ are self-organised dynamically based on Equation (28). Assume the arrival rate is 0.15, and the traffic load ratio between the hotspot cell and other cells is changing from 1 to 5.…”