The interference-reduced energy loading for multi-code HSDPA systems

Abstract

A successive interference cancelation (SIC) method is developed in this article to improve the performance of the downlink transmission throughput for the current high speed downlink packet access (HSDPA) system. The multicode code division multiplexing spreading sequences are orthogonal at the HSDPA downlink transmitter. However, the spreading sequences loose their orthogonality following transmission through frequency selective multipath channels. The SIC method uses a minimum-mean-square-error (MMSE) equalizer at the receiver to despread multicode signals to restore the orthogonality of the receiver signature sequences. The SIC scheme is also used as part of the resource allocation schemes at the transmitter and for the purpose of interference and inter-symbolinterference cancelation at the receiver. The article proposes a novel system value based optimization criterion to provide a computationally efficient energy allocation method at the transmitter, when using the SIC interference cancelation and MMSE equalizer methods at the receiver. The performance of the proposed MMSE equalizer based on the SIC receiver is significantly improved compared with the existing schemes tested and is very close to the theoretical upper bound which may be achieved under laboratory conditions.

System value-based optimum spreading sequence selection for high-speed downlink packet access (HSDPA) MIMO

“…This section describes the iterative WF optimization, which finds the optimum sub-channels K * WF using the system values for continuous unequal bit loading. This iterative WF algorithm can also be applied to the HSDPA system with and without SIC by using the system value λ k formulation given in (9) and (11), respectively. The algorithm first allocates energies to the channels before the rates and the optimum number of channels are determined.…”

“…. , K opt for that iteration, the system values are obtained from (9) or (11) The system values given in λ are sorted in an ascending order for the current K opt iteration and are stored in the K opt th column of the K × K matrix λ store , i.e., in [ λ store ] 1:K opt ,K opt . The indices of the ordered system values are stored in a K opt length vector k order , where indices range from 1 to K opt .…”

“…Therefore, this article uses the system value optimization originally presented in [9], where the system value λ k of the kth channel is calculated using (9) and (11) for the non-SIC and the SIC-based receivers, respectively. Differing from [9], in this article a method is proposed to calculate the discrete rate for each spreading sequence using the mean system value λ mean prior to allocating the energy for each sequence.…”

“…If the throughput reduction problem is not solved in the HSDPA system, the OFDM-based systems will have the upper hand over the HSDPA system in urban environments. The HSDPA single-input singleoutput (SISO) system has been the main focus of the study in [9], which provides tools to combat frequency selectivity, when bringing the HSDPA SISO performance close to the OFDM-based systems. Should the ISI problem be solved for the HSDPA MIMO-based systems, the current HSDPA MIMO system would achieve throughputs close to the LTE advanced without the need to change the whole infrastructure by using throughput optimization methods.…”