In this paper, as part of the adaptive resource allocation and management (ARAM) system (Alagoz, 2001), we propose an adaptive admission control strategy, which is aimed at combating link congestion and compromised channel conditions inherent in multimedia satellite networks. We present the performance comparisons of a traditional (fixed) admission control strategy versus the new adaptive admission control strategy for a direct broadcast satellite (DBS) network with return channel system (DBS-RCS). Performance comparisons are done using the ARAM simulator. The traffic mix in the simulator includes both available bit rate (ABR) traffic and variable bit rate (VBR) traffic. The dynamic channel conditions in the simulator reflect time variant error rates due to external effects such as rain. In order to maximize the resource utilization, both for fixed and adaptive approaches, assignment of the VBR services are determined based on the estimated statistical multiplexing and other system attributes, namely, video source, data transmission, and channel coding rates. In this paper, we focus on the admission control algorithms and assess their impact on quality-of-service (QoS) and forward link utilization of DBS-RCS. We show that the proposed adaptive admission control strategy is profoundly superior to the traditional admission control strategy with only a marginal decrease in QoS. Since the ARAM system has several parameters and strategies that play key roles in terms of the performance measures, their sensitivity analysis are also studied to verify the above foundations.

We propose a new suboptimum multiuser detector for synchronous and asynchronous multiuser communications. In this approach, a greedy strategy is used to maximize the cost function, the maximum-likelihood (ML) metric. The coefficients of the ML metric are utilized as weights indicating in which order bits can be estimated. The complexity of the algorithm is approximately K/sup 2/ log K per bit, where K is the number of users. We analyze the performance of the greedy multiuser detection in the additive white Gaussian noise channel as well as in the frequency-nonselective Rayleigh fading channel, and compare it with the optimum detector and several suboptimum schemes such as conventional, successive interference cancellation, decorrelator, sequential, and multistage detectors. The proposed greedy approach considerably outperforms these suboptimum schemes, especially for moderate and high loads in low and moderate signal-to-noise ratio regions. The results show that when there is a significant imbalance in the values of the coefficients of the ML metric due to moderate to high noise, fading, and asynchronous transmission, near-optimum performance is achieved by the greedy detection.

Previous results have demonstrated excellent performance of turbo coded modulation with iterative demodulation-decoding for systems with antenna diversity. However, the computational complexity at the receiver is exponential in the number of transmit antennas; hence it is too high for the case of large number of transmit and receive antennas. We present a new iterative-greedy demodulation-decoding algorithm for turbo codes for multiple antenna systems. The decoding algorithm is based on a novel greedy detection method for multiuser communications. The iterative-greedy demodulation-decoding algorithm is characterized by the exchange of soft information between the demodulator and the decoder, and the significant decrease in computational complexity, as compared to the standard method of iterative demodulation-decoding, with a slight degradation in performance. This is due to the novel, greedy method of calculating the log-likelihoods to be used in the iterative decoding process, where only a small subset of the possible received vectors is considered, resulting in a receiver with only polynomial complexity in the number of transmit antennas.

Previously, a novel scheme for iterative multiuser detection and turbo decoding was proposed by Damnjanovic and Vojcic (2000, 2001). In this scheme, multiuser detection and single-user turbo decoding are tightly coupled to maximize the overall gain. The extrinsic probabilities for the coded bits of the interfering users, obtained after each turbo decoding iteration, are used as a priori probabilities in the following multiuser iteration and the extrinsic information for the systematic bits of the desired user is used as a priori information in the next single-user turbo decoding iteration. Turbo decoding of parallel concatenated convolutional codes is carried out in parallel fashion. It has been shown that the proposed detector approaches the multiuser capacity limit within 1 dB in the low signal-to-noise ratio region. However, the main drawback of the scheme is its exponential complexity in the number of users, which is due to the complexity of the maximum a posteriori probability (MAP) multiuser detector. In this paper, we show that the complexity of the scheme can be significantly reduced by replacing the (MAP) multiuser detector with an iterative detector derived from the greedy multiuser detector proposed by AlRustamani and Vojcic (2000). In this paper, we demonstrate that, for both the additive white Gaussian noise and the frequency-nonselective Rayleigh fading, the substantial reduction in complexity of the iterative scheme proposed by Damnjanovic and Vojcic when the greedy detector is utilized introduces a slight degradation in performance.