CDMA Downlink System Research Articles

VLSI implementation of multicarrier complementary coded CDMA downlink system

In recent years, many studies on the development of CDMA have been conducted in industries and academic Institutions. Multicarrier complementary coded code division Multiple Access (MC CC-CDMA) is being largely used for high-speed data transmission .However the main limitation of such a system is Multi carrier Interference (MAI). The use of parallel Interference cancellation (PIC) gives an excellent solution to suppress MAI. In this article the author present the analytical testing and investigation of the MC CC-CDMA system using different schemes. The use of PIC in frequency-selective decomposition channels is also analyzed here. Simulations in Matlab are carried out on flat vanishing and bidirectional frequency selective disappearing channels and are used to verify theoretical analysis. The result shows that, error rate of MC CC-CDMA with PIC is much lower than without PIC. The author also presents an FPGA Implementation of the downlink system and achieved the power reduction with reduced complexity circuit.

MIMO solution for performance improvements of OFDM–CDMA system with pilot tone

In this paper, MIMO OFDM---CDMA downlink scheme is proposed as a solution for improving performance of the OFDM---CDMA downlink system with pilot tone and threshold detection combining (optimum TDC). The new presented system with MIMO included uses space---time block coding applied to two, three and four transmit antennas and it has an arbitrary number of receive antennas. Bit error rate performance in the case of Ricean frequency selective fading is evaluated for the original system as well as for the one with MIMO included. For that reason an adequate simulation model is developed. The results show that the proposed system significantly outperforms the OFDM---CDMA downlink system with pilot tone and optimum TDC.

Improved Channel Estimation and SIR Measurement in WCDMA Downlink Systems

The rake receiver performance of a direct-sequence code-division multiple-access (DS-CDMA) system can significantly be degraded unless the channel condition is properly estimated. Since the channel condition is time-varying and location-dependent, it is desirable to employ an adaptive channel estimator (ACE) that can properly adjust the bandwidth of the channel estimation filter (CEF) according to the channel condition such as the maximum Doppler frequency. To this end, we propose low-complexity ACE and signal-to-interference power ratio (SIR) estimator for wide-band CDMA downlink systems with and without the use of transmit antenna diversity. The proposed schemes adjust the bandwidth of the CEF by exploiting the correlation characteristics of the received pilot signal. The analytic design is verified by computer simulation. Simulation results show that the proposed ACE and SIR estimator can significantly improve the link performance for a wide range of channel condition, particularly when the channel condition is poor.

Unified power control, error correction coding and scheduling for a CDMA downlink system

Transmitting multimedia data over a CDMA channel presents a new set of challenges. Sometimes, data demands will exceed the system capacity, in which case the system must make the most efficient use of its limited resources. The resources we consider are: fixed bandwidth available for each user and the transmit power budget for each cell. In this paper, we present our approach for unifying power control, variable forward error correction (VFEC), and scheduling for a downlink system by allocating the system resources. Our objective is to maximize the overall system satisfaction, which we call “system utility”. This objective is achieved by applying a distributed algorithm which divides the overall optimization problem into a hierarchy of three levels (system, cell and user). At each level, the system performs independent and parallel optimizations; the critical information is then passed to the higher level for further optimization. Finally, an iterative and distributed algorithm is applied at the system level to achieve the overall system optimization.