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  • RESEARCH Open Access

    The interference-reduced energy loading formulti-code HSDPA systemsMustafa K Gurcan*, Irina Ma and Hadhrami Ab Ghani

    Abstract

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

    Keywords: resource allocation, high speed downlink packet access system, iterative energy allocation, sum capacitymaximization

    1 IntroductionThe third generation mobile radio system uses a codedivision multiple access (CDMA) transmission schemeand has been extensively adopted worldwide. Three GPPhas developed the high speed downlink packet access(HSDPA) system as a multi-code wide-band code divi-sion multiple access (WCDMA) system in the Releasefive specification [1,2] of the universal mobile telecom-munications system (UMTS). The success of third gen-eration wireless cellular systems is based largely on theefficient resource allocation scheme used by the HSDPAsystem to improve the downlink throughput.With the recent availability of enabling technologies

    such as adaptive modulation and coding and hybridautomatic repeat request, it has been possible to intro-duce internet enabled smart phones for internet-centricapplications. The trend for the HSDPA system is toimprove the downlink throughput for smart phoneswith high-data-rate applications. The throughput of the

    HSDPA downlink has been extensively evaluated in[3,4]. A recent investigation conducted in [5] shows thatthe data throughput achievable in practice is signifi-cantly lower than the theoretical upper-bound whenusing the multiple-input multiple-output (MIMO)HSDPA system. This article aims to optimize the down-link throughput close to the upper-bound without toomuch complexity.The downlink throughput optimization for the

    HSDPA multi-code CDMA system is considered to be atwo part problem in [6]. The first involves the schedul-ing of users for transmissions such as [7,8] and the sec-ond is the link throughput optimization for a givenresource allocation, which is the focus of this article.The link throughput can be optimized through signaturesequence design, receiver design and power allocation.Optimal signature sequence design ensures that the

    received spreading codes are orthogonal to each other atthe expense of extensive channel state information (CSI)feedback [9,10]. Therefore, three GPP has standardizedthe use of a fixed set of signature sequences known asthe orthogonal variable spreading factor (OVSF) codes

    * Correspondence: [email protected] of Electrical and Electronic Engineering, Imperial CollegeLondon, SW7 2AZ, UK

    Gurcan et al. EURASIP Journal on Wireless Communications and Networking 2012, 2012:127http://jwcn.eurasipjournals.com/content/2012/1/127

    2012 Gurcan et al; licensee Springer. This is an Open Access article distributed under the terms of the Creative Commons AttributionLicense (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium,provided the original work is properly cited.

    mailto:[email protected]://creativecommons.org/licenses/by/2.0

  • to minimize the CSI feedback required. For the MIMOsystem, which requires a larger signature sequence set,3GPP standardized the use of a given OVSF set multi-plied with the pre-coding weights and then concatenat-ing the weighted set of spreading sequences. Thisensures that each symbol is spread by a unique pre-coded spreading sequence, while making sure that theconcatenated spreading sequence is orthogonal to theremaining set of spreading sequences at the transmitter.Although the signature sequences generated by OVSF

    codes with pre-coding weights are orthogonal to eachother at the transmitter, their orthogonality is lost at thereceiver after transmission over the frequency selectivemultipath channels. This is known as the inter-codeinterference. Similarly, the transmitted symbols overlapwith the neighboring symbol period, creating inter-sym-bol interference (ISI). These interferences are part ofself interference (SI). The presence of SI produces a dif-ference between practical system throughput and thetheoretical upper-bound shown in [5].Linear minimum mean square error (MMSE) equali-

    zers are used to reduce part of SI in [11-13]. The LinearMMSE equalizers in [11,12] restore orthogonalitybetween the received codes. [13] reduces the overall SIby using a symbol level MMSE equalizer followed by asymbol-level successive interference cancelation (SIC)scheme, with the aim to obtain practical systemthroughput closer to the theoretical upper-bound. Inreferences [12-15] the use of a SIC receiver in collabora-tion with either a chip or a symbol level MMSE equali-zer has been examined for the HSDPA downlinkthroughput optimization.Link-throughput is also examined in terms of the joint

    optimization of the transmitter and the receiver in [6]where power allocation is incorporated with a two-stageSIC for a multi-code MIMO systems. In each SIC itera-tion, the equalizer coefficient and the power allocationcalculations require an inversion of a large dimensioncovariance matrix, which makes the system computa-tionally expensive. Simplifications for inversion of largematrices is examined in [16] to make the implementa-tion of the linear MMSE equalizers followed by the sym-bol level SIC practically feasible. There is a need for amethod, which eliminates the requirement to have itera-tive covariance matrix inversions when dealing with theinter-code interference and the intra-cell ISI interfer-ences. A method has not yet been developed to jointlyoptimize the linear symbol level MMSE equalizer, theSIC detector and then to allocate the transmissionpowers when maximizing the total transmission rate.The objective of this article is to propose a novel

    receiver with a symbol level linear MMSE equalizer fol-lowed by a single level SIC detector. The objective isalso to jointly optimize the transmission power and the

    receiver for a single-user multi-code downlink transmis-sion system. The receiver proposed in this article sup-presses the inter-code interference and ISI interferencesiteratively without the need to invert a large covariancematrix for each iteration for when transmitting over fre-quency selective channels. The article also describes anovel iterative transmission power/energy adaptationscheme to maximize the sum capacity of the downlinkfor a single user, when using discrete transmission ratesand a constrained total transmission power.When transmitting data streams at discrete rates, an

    optimization criterion is usually used to deliver a givenconstrained signal to interference plus noise ratio(SINR) at the output of each receiver. In this article anovel energy adaptation criterion known as the systemvalue optimization criterion is used to maximize thetotal rate. The system value approach is a modified ver-sion of the total mean square error (MSE) minimizationcriterion [17,18] used in the open literature. The relatedstudy is reviewed for the system value criterion in Sec-tion 2.The remainder of this article is organized as follows:

    in Section 3 the system model used in this article isgiven. The optimization criterion adopted here isdescribed in Section 4 before introducing the SIC recei-ver model in Section 5. Section 6 presents the proposedSIC-based power and rate allocation scheme to optimizethe total rate. Its performance and results are discussedin Section 7 before the conclusion is presented in Sec-tion 8.

    2 Related study on optimization criteriaVarious optimization criteria are used when allocatingpowers for the multi-code downlink throughput optimi-zation. References [11,19-21] focus on the transceiverdesign optimization criteria and references [22-24] con-centrate on criteria for the joint rate and power alloca-tion. These joint rate and power adaptation methods aregeneralized in reference [22] under three headings asfollows.

    1. The first criterion includes systems which opti-mize the transmission power to maximize the ratefor a given realization of channel gains such as[19-21,24,25]. The aim is to maximize the total rateby iteratively adjusting the transmission powers andsatisfying a target SINR or MSE.2. The second method, such as [26] aims to main-tain the received power at a target level, whilst maxi-mizing the total rate by jointly optimizing thetransmission power, rate and signature sequencesand also the linear MMSE equalizers at the receiver.3. The third method, examples of which are [22,23],uses the average system performance as an

    Gurcan et al. EURASIP Journal on Wireless Communications and Networking 2012, 2012:127http://jwcn.eurasipjournals