Parvathanathan Subrahmanya

First Order Adaptive IIR Filter for CQI Prediction in HSDPA

In this work, we consider channel quality indicator (CQI) prediction for High Speed Downlink Packet Access (HSDPA). In HSDPA systems, there is a delay of about 3 subframe associated with the application of CQI feedback. Traditional FIR filter based predictors such as Least-Mean-Squares (LMS) and Recursive-Least-Squares (RLS) typically come with high computational complexity. We consider a first order adaptive IIR alternative with substantially lower complexity while attaining the same level of accuracy. By minimizing the mean squared error (MSE), we derive an exact gradient descent algorithm as well as two pseudolinear regression algorithms. The convergence rates and the convergence conditions are then established. Simulation results show that the proposed adaptive IIR filters combat both feedback delay as well as estimation error and provide up to 25\% HSDPA throughput improvement.

Throughput Optimization in High Speed Downlink Packet Access (HSDPA)

In this paper, we investigate throughput optimization in High Speed Downlink Packet Access (HSDPA). Specifically, we propose offline and online algorithms for adjusting the Channel Quality Indicator (CQI) used by the network to schedule data transmission. In the offline algorithm, a given target BLER is achieved by adjusting CQI based on ACK/NAK history. By sweeping through different target BLERs, we can find the throughput optimal BLER offline. This algorithm could be used not only to optimize throughput but also to enable fair resource allocation among mobile users in HSDPA. In the online algorithm, the CQI offset is adapted using an estimated short term throughput gradient without specifying a target BLER. An adaptive stepsize mechanism is proposed to track temporal variation of the environment. We investigate convergence behavior of both algorithms. Simulation results show that the proposed offline algorithm can achieve the given target BLER with good accuracy. Both algorithms yield up to 30% HSDPA throughput improvement over that with 10% target BLER.

CQI algorithm design in MIMO systems with maximum likelihood detectors

Abstract In this paper, we investigate throughput optimization in 2 × 2 multi-input multi-output (MIMO) systems using channel quality indicator (CQI) based scheduling. Existing MIMO CQI algorithms are mostly designed for sub-optimal linear symbol detectors such as minimum mean square error (MMSE). We consider in this paper how to select CQIs for both streams in order to maximize the total throughput when the non-linear optimal symbol detection technique, maximum likelihood (ML) detector, is employed. Specifically, we formulate a simple yet accurate mathematical model for throughput maximization in a 2 × 2 MIMO channel using an ML detector. We make use of constellation constrained capacity to characterize the feasible rate region of such MIMO systems. Based on the information-theoretic analysis, a novel CQI algorithm for 2 × 2 MIMO transmission is proposed. Numerical results indicate that the proposed CQI algorithm yields up to 4% throughput improvement over the CQI algorithm optimized for MMSE detectors in High Speed Downlink Packet Access (HSDPA).

Energy-Efficient Power and LNA Control for Wireless Multi-Channel Communication

Simultaneous communications over parallel channels is a prominent scheme in modern wireless system. Intuitive multi-channel solution allocates one independent RF chain (including LNA, low-noise amplifier) to each separate channel, causing high implementation cost. Alternatively, low-cost RF uses one single LNA to cover all parallel channels and save implementation cost. Nevertheless, such structure introduces challenges in the control of shared LNA gain (as well as channel power allocation), especially when adapting to independent fadings across parallel channels. Under shared-LNA strucutre, and to maximize energy efficiency, this paper proposes a sub-gradient framework that optimizes both shared-LNA gain and channel power values under multiple system constraints, including Tx power, ADC saturation, baseband SNR, and LNA gain. We discuss algorithm properties including convergence performance, step size selection, and solution accuracy. Simulation results confirm that, optimized energy efficiency through our algorithm can outperform intuitive strategies by 20% to 160%. Finally, impacts of various system parameters are studied as well.

An Overview of High-speed Packet Data Transport in CDMA Systems

Rapid growth of data services in wireless communication systems requires an efficient means for high speed data transport. Modern CDMA systems have evolved to support this need. This paper presents an overview of the key techniques for improving high speed data transport in the following standards: 1xEV-DO (IS-856 Rev A), 1xEV-DV (cdma2000 Rev D), and HSDPA & EUL (WCDMA FDD Release 6). The emphasis is on identifying the common themes for high speed data transport in all these systems: adaptive modulation and coding, incremental redundancy and hybrid ARQ, smart scheduling to exploit channel variations, limited downlink macro-diversity aided by fast sector switching, and the use of shared channels to improve perceived latency.