Amina AlRustamani

A new approach to greedy multiuser detection

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.

Fixed versus adaptive admission control in direct broadcast Satellite networks with return channel systems

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.

Adaptive rate control and QoS provisioning in direct broadcast satellite networks

Adaptive rate control, if properly employed, is an effective mechanism to sustain acceptable levels of Quality of Service (QoS) in wireless networks where channel and traffic conditions vary over time. In this paper we present an adaptive rate (source and channel) control mechanism, developed as part of an Adaptive Resource Allocation and Management (ARAM) algorithm, for use in Direct Broadcast Satellite (DBS) networks. The algorithm performs admission control and dynamically adjusts traffic source rate and Forward Error Correction (FEC) rate in a co-ordinated fashion to satisfy QoS requirements. To analyze its performance, we have simulated the adaptive algorithm with varying traffic flows and channel conditions. The traffic flow is based on a variable bit rate (VBR) source model that represents Motion Picture Expert Group (MPEG) traffic fluctuations while the DBS channel model is based on a two-state Additive White Gaussian Noise (AWGN) channel. For measures of performance, the simulator quantifies throughput, frame loss due to congestion during transmission as well as QoS variations due to channel (FEC) and source (MPEG compression and data transmission) rate changes. To show the advantage of the adaptive FEC mechanism, we also present the performance results when fixed FEC rates are employed. The results indicate significant throughput and/or quality gains are possible when the FEC/source pairs are adjusted properly in co-ordination with source rate changes.

Turbo greedy multiuser detection

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.

Greedy multiuser detection over single-path fading channel

In this paper, we present a greedy multiuser detector for code-division multiple-access (CDMA) systems in single-path Rayleigh fading channel. In this approach the coefficients of the maximum likelihood (ML) metric are utilized as weights indicating the order in which bits can be estimated, i.e. we take into consideration the order of the coefficients contribution to the ML metric. The complexity of the algorithm is O(K/sup 2/ log K) per bit interval, where K is the number of users. The results show that the greedy algorithm achieves near-optimum performance if there is a significant imbalance in the values of the coefficients resulting from fading, asynchronous transmission and in the low to moderate signal-to-noise ratio (SNR) region. For the high SNR region the performance reaches an error floor, which can be eliminated at the expense of insignificant increase in the complexity of the algorithm.

Turbo-greedy coding for multiple antenna systems

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.

Greedy Detection

In this paper, we introduce a new greedy algorithm developed for communication systems characterized with multiple simultaneous data transmission. Specifically, we consider code-division multiple-access (CDMA) systems and systems employing space-time coding (STC). The optimum detection in such systems has an exponential complexity and cannot be used in practical systems. We show that performance close to the optimum performance yet with significantly lower complexity can be achieved by the proposed algorithm. Also, we show that its performance is significantly better than that of most of the existing sub-optimum schemes for a wide range of operating conditions.

Adaptive Resource Allocation and Rate Control for Heterogeneous Traffic on DBS Links

In a Direct Broadcast Satellite (DBS) system, the capacity of the DBS forward satellite link may become a “bottleneck” operating under heterogeneous traffic and dynamically changing channel conditions. To meet this challenge, we propose an Adaptive Resource Allocation and Management (ARAM) system that attempts to maximize the utilization of the available capacity on the forward DBS link while maintaining Quality of Service (QoS) in the presence of channel effects and congestion in the network. The proposed algorithm attempts to maximize statistical multiplexing gain, under varying channel and traffic conditions, by distributing the rate reduction during congestion evenly among services, thus, providing graceful degradation during overload intervals. By using QoS reports and transmit queue monitoring, the ARAM system utilizes adaptive control of transmission attributes (channel and source rates). Since measures of congestion, QoS and channel variations involve observation over different time periods, the proposed adaptive control mechanism consists of four control strategies that are activated at different time scales: short (STC), short-to-medium (SMTC), medium (MTC) and long (LTC) term controls. Furthermore, in order to improve QoS of end-users, a signal-to-noise ratio (SNR) sensing technique is included to determine the channel state and correspondingly, set the appropriate forward error correction (FEC) rate to resolve the channel problems. The ARAM simulator is developed to show the benefits of employing the adaptive rate control mechanisms by comparing its performance with “no-control” case. The results show that the concept of source and channel rates adaptation offers a great potential in controlling the QoS and efficient link capacity utilization and system throughput, when traffic and channel conditions vary with time.

On the effects of adaptive forward error correction mechanism in direct broadcast satellite networks

In wireless networks where channel conditions vary over time, forward error correction (FEC), if properly employed, may be an eflective mechanism to sustain throughput. In this paper we present an adaptive FEC mechanism, developed as part of an Adaptive Resource Allocation and Management (ARAM) algorithm, for use in Direct Broadcast Satellite (DBS) networks. The algorithm performs admission control and dynamically adjusts traJfic source rate and FEC rate to sati& quality of services (QoS) requirements. To analyze its performance, we have simulated the adaptive algorithm with varying traficjlows and channel conditions. The traffic model includes a variable bit rate (VBR) source model that represents MPEG traflc jluctuations while the DBS channel model is based on A WGN. As measures of performance, the simulator quantifies throughput and dropped frames due to congestion during transmission as well as QoS variations due to channel (FEC) and source (MPEG compression) rate changes. To show the advantage of the adaptive FEC mechanism, we present the performance results when the fied FEC rates are employed. The results indicate significant throughput and/or quality gains are possible when the FEChource pairs adjusted properly.

Management of heterogeneous traffic loading in DBS networks

In the paper we present the Adaptive Resource Allocation and Management (ARAM) algorithms developed to manage a Direct Broadcast Satellite (DBS) system supporting heterogeneous traffic mixes and operating under dynamic channel conditions. This traffic mix includes both: (i) data traffic that operates as an available bit rate flow and, (ii) video traffic that generates a variable bit rate flow. Both types of traffic use the Internet Protocol (IP) so they can be efficiently multiplexed on the same link. The dynamic channel conditions reflect time variation error rates due to external effects such as rain or jamming. ARAM attempts to maximize the utilization of the available capacity on the forward DBS link while maintaining Quality of Service (QoS) in the presence of congestion int he network and channel degradation effects. To achieve these ends, it utilizes adaptive control of video compression rates, data transmission rates, and channel forward error correction rates. One of the major features of ARAM is the admission control algorithm used to determine the number of variable bit rate flows admitted for service. In order to maximize the resource utilization, assignment of the variable bit rate services based on their peak rate is avoided. Instead, a flexible utilization of the bandwidth requiring the estimation of statistical multiplexing gain is used enabling more services to share the DBS link. Therefore in this paper, we focus on the ARAM admission control algorithm and assess its impact on QoS and DBS link utilization.