By Thomas Barber, Aiguo Yan and Zoran Zvonar

Receiver design is the most difficult task in the development of the UE since it carries the most complexity in the overall UE implementation. Multiple users in LCR are multiplexed via their assigned OVSF codes, however the orthogonality among different code channels is not preserved due to the delay spread in the multipath channel and the received signal at the input of the UE is subject to MUI in addition to ISI. Conventional receivers applied in CDMA systems (e.g. RAKE receiver) have poor performance in this case and a more complex multi-user receiver design is a better choice.

Figure 1. UE partitioning based on integrated solution.
The area of multi-user reception has emerged in the last decade of the 20th century, providing the theoretical framework for development and analysis of multi-user detectors. Certain receiver structures, for example linear receivers, are proven to be more suitable for given link level scenarios. Specifically, in the TD-SCDMA case, the maximum number of code channels in a time slot and length of the scrambling codes are 16 so all code channels can be easily processed in parallel.

MUD algorithms can be derived under different criteria.1 The class of sub-optimal multi-user detectors, commonly referred to as JD, can be used to reduce the MUI by using a linear receiver structure. Several approaches can be used for linear receiver design — the two most common optimization criteria are ZF-BLE and MMSE-BLE. ZF-BLE can completely eliminate the ISI and MAI at the expense of noise enhancement. MMSE-BLE takes a balance in mitigating impact of ISI/MAI and noise. The complexity of joint detection is independent of the symbol constellation.

While the JD algorithm is the central piece of the receiver structure, the key to the performance is in the surrounding functions, including channel estimation, active code detection, SNR estimation and synchronization in general.2 One very important information is how many CDMA code channels in a time slot are active and what they are.

Channel estimation in the LCR receiver is performed based on a structured midamble. The different schemes are outlined in the standard for midamble design. The use of the common midamble allocation scheme is signaled to the UE by higher layers as a part of the physical channel configuration.

The first midamble allocation scheme is the CMA in which all downlink channels in a time slot use the same basic midamble. The midamble is cyclically shifted depending on the number of active channelization codes in the slot. In the CMA case, we assume that all users share the same air propagation channel.

The alternative in the system is to use the DMA scheme. The standard specifies a fixed rule and procedure to allocate a particular midamble with the associated code channels. The same basic midamble with different shifts for a different group of code channels is used. In the DMA case, the UE shall assume different air propagation channel estimates for each of the individual midambles.

In the third midamble allocation scheme, the networks can also explicitly inform an UE which channel uses what midamble, without the constraints from either CMA and DMA. In this case, the UE shall also assume different air propagation channel estimates for each of the individual midambles.

The CE structure is derived based on cyclic properties of the midamble. The number of channel taps and length of the channel estimate directly impact the structure and the size of the generic channel matrix T. One of the challenges in CE is to remove noise-only channel taps that do not benefit the performance of the receiver. Another challenge is to determine if a midamble with a particular shift exists or not. If a midamble is deemed inactive, we can then deduce that all associated code channels are inactive. When a midamble is deemed active, we still don’t know how many associated code channels are active.

SNR estimations can be viewed as the integral part of channel estimation. MMSE JD receiver requires SNR estimation to achieve better performance than the ZF counterpart. Different techniques for SNR estimation can be applied in the receiver design — as usual, the tradeoff is between the quality of the estimate and complexity of the estimation algorithm.2

The implicit assumption at the receiver side is that the UE knows the channelization codes used by all UEs, which is not true in reality. To avoid performance loss caused by active codes mismatch, UE is required to detect the active channelization codes, whose number could be much less than 16 and varies from slot to slot. Different algorithms are proposed to perform the active code detection — the key requirement is to introduce minimum degradation in the system performance compared to the case where channelization codes are known.

Besides JD, the second largest contributor to the receiver complexity is the decoding part of the outer receiver. Depending on the amount of protection, determined by the class and data rate capability of UE, either turbo or convolutional coding can be applied. The complexity of decoding techniques is well understood in wireless systems. Typical implementations of convolutional decoders are based on the Viterbi algorithm, while the performance/complexity tradeoff in the case of turbo decoding points to the use of the MAX-log-MAP algorithm.

Integrated Solutions

A typical partitioning of the UE is depicted in Figure 1. The elements of the chipset include RF transmit/receive portion, analog baseband with mixed-signal and power management blocks and digital baseband. A complete phone design includes the chipset, memory modules, applications modules (camera, display etc) and peripherals such as Bluetooth® or an SD or MMC. Multiple design challenges are associated with each of the blocks. However, the system requirements of TD-SCDMA impose unique problems to digital baseband design that will be outlined in this section.

The entire signal chain — RF, mixed-signal and digital, should be optimized to provide stable performance margins. If the pieces of the signal chain are designed independently, each piece must be designed such that it can be integrated with other pieces of the signal chain whose performance is unknown. If the entire signal chain is optimized, the cost and complexity can be traded between components to achieve a more efficient solution. For example, the RF filter requirements can be relaxed if a digital filter is available to compensate for any distortions the relaxed RF filter introduces.

The LCR option for the time division duplex mode of UTRAN was introduced in Release 4 of the 3GPP specifications. A number of test networks have been running in China for the past few years, and wide scale commercial deployment of TD-SCDMA is likely within the next year. Early solutions for TD-SCDMA have had to provide flexibility to accommodate changes in the standard. The most flexible solution is a full software solution that can be achieved using a digital baseband processor such as the AD6901 which provides sufficient processor cycles to handle all of the algorithms and control code in software for a certain class of UE.

The AD6901 digital baseband processor in the SoftFone-LCR chipset is an example of a scalable solution targeted for TD-SCDMA terminals. The AD6901 is based on the Blackfin® processor as the computational engine. This device has all the attributes of an advanced digital baseband platform, including the capability to handle new features and absorb a number of hardware features in an efficient way, to achieve necessary speed for a broad class of UE, to provide scalable power consumption, to efficiently handle control code, to provide flexible I/O and to support optimizing compiler for production code quality.

To be commercially successful, TD-SCDMA handsets must meet or exceed the performance of existing handsets at the same cost. The easiest way to match the performance and cost of existing handsets is to build on an existing commercially accepted platform. For example, the SoftFone-LCR™ platform is based on ADI’s SoftFone® platform for GSM/GPRS/EDGE, which is the end result of years of investment in performance/cost improvement and power reduction. These improvements include high performance low power processor cores, such as the Blackfin® Processor and the ARM7 core, the use of dynamic voltage scaling to match power consumption to processor performance and the use of advanced RF and mixed-signal techniques such as direct conversion receivers and sigma-delta data converters.

Finally, as TD-SCDMA networks roll out nationwide in China, there are likely to be gaps in coverage areas for some time. Therefore, most TD-SCDMA handsets will need access to an existing network if a TD-SCDMA network is not available. Both GSM and CDMA networks are available in China; however, since TD-SCDMA has been accepted within the 3GPP framework, the most likely candidate for dual mode operations is GSM/TD-SCDMA. Fortunately, only a few additional system components are required for a dual mode TD-SCDMA handset. Soft handover is not required between GSM and TD-SCDMA, so two independent radios, one for GSM and one for TD-SCDMA can be used without modification. The audio, power management and auxiliary functions can be shared by GSM and TD-SCDMA so only an additional pair of DACs and ADCs for the GSM signal chain are required, and these have been integrated into the analog interface IC in the SoftFone-LCR chipset.


1. M. Vollmer et. Al., “Comparative study of joint-detection techniques for TD-CDMA based mobile radio systems”, IEEE JSAC, August 2001.

2. K.Shi et al., “Downlink joint detection for TD-SCDMA systems: SNR estimation and active code detection”, in Proceddings of IEEE VTC 2005.

About the Author

Thomas Barber is a Senior System Engineer in the RF and Wireless System Group at Analog Devices working on the chipsets for 3G mobile phones including UMTS and TD-SCDMA. Aiguo Yan is the senior wireless systems engineer focusing on the design of algorithms and architectures for wireless communications systems. He is currently leading the effort for TD-SCDMA algorithm and architecture development. Zoran Zvonar is the Manager of the Systems Development Group involved in the development of integrated solutions for wireless handsets.

Glossary of Terms

CDMA— Code Division Multiple Access CE— Channel Estimation CMA— Common Midamble Allocation DMA— Default Midamble Allocation EDGE— Enhanced Data for GSM Evolution GRPS— General Packet Radio Service GSM— Global System for Mobile Communications ISI— Inter-Symbol Interference JD— Joint detection LCR— Low Chip Rate MMC— Multi Media Card MMSE-BLE— Minimum Mean Square Error Block Linear Equalizer MUD— Multi-user detection MUI— Multi-User Interference OVSF— Orthogonal Variable Spreading Factor SD— Software Documentation SNR— Signal-to-Noise Ratio TD-SCDMA— Time Division Synchronous Code Division Multiple Access UMTS— Universal Mobile Telecommunications System UTRAN— Terrestrial Radio Access Network ZF-BLE— Zero Forcing Block Linear Equalizer