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Parastoo Sadeghi

Publications and source records attributed to Parastoo Sadeghi.

115 records · Page 7Linked to original sources

Joint Optimization of Throughput and Packet Drop Rate for Delay Sensitive Applications in TDD Satellite Network Coded Systems

In this paper, we consider the issue of throughput and packet drop rate (PDR) optimization as two performance metrics for delay sensitive applications in network coded time division duplex (TDD) satellite systems with large round trip times (RTT). We adopt random linear network coding (RLNC) under two different scenarios, feedback-less and with feedback, and our goal is to jointly optimize the mean throughputs and PDRs of users in the system. For this purpose, we propose a systematic framework and start with formulating and optimizing these performance metrics for the single-user case. This framework enables us to analytically compare the performance metrics under different system parameters and settings. By comparing RLNC schemes under feedback-less and feedback scenarios for different RTTs, we show that the feedback-less schemes outperform the schemes with feedback in TDD systems with large RTTs. Then, we extend the study of feedback-less RLNC schemes to the multi-user broadcast case. Here, we consider a number of different broadcast scenarios and optimize the system parameters such that the best overall performance is achieved. Furthermore, the complicated interplay of the mean throughputs and PDRs of different users with different packet erasure conditions in each of the considered broadcast scenarios is discussed.

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Instantly Decodable versus Random Linear Network Coding: A Comparative Framework for Throughput and Decoding Delay Performance

This paper studies the tension between throughput and decoding delay performance of two widely-used network coding schemes: random linear network coding (RLNC) and instantly decodable network coding (IDNC). A single-hop broadcasting system model is considered that aims to deliver a block of packets to all receivers in the presence of packet erasures. For a fair and analytically tractable comparison between the two coding schemes, the transmission comprises two phases: a systematic transmission phase and a network coded transmission phase which is further divided into rounds. After the systematic transmission phase and given the same packet reception state, three quantitative metrics are proposed and derived in each scheme: 1) the absolute minimum number of transmissions in the first coded transmission round (assuming no erasures), 2) probability distribution of extra coded transmissions in a subsequent round (due to erasures), and 3) average packet decoding delay. This comparative study enables application-aware adaptive selection between IDNC and RLNC after systematic transmission phase. One contribution of this paper is to provide a deep and systematic understanding of the IDNC scheme, to propose the notion of packet diversity and an optimal IDNC encoding scheme for minimizing metric 1. This is generally NP-hard, but nevertheless required for characterizing and deriving all the three metrics. Analytical and numerical results show that there is no clear winner between RLNC and IDNC if one is concerned with both throughput and decoding delay performance. IDNC is more preferable than RLNC when the number of receivers is smaller than packet block size, and the case reverses when the number of receivers is much greater than the packet block size. In the middle regime, the choice can depend on the application and a specific instance of the problem.

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Using Distributed Rotations for a Low-Complexity Dynamic Decode-and-Forward Relay Protocol

In this paper, we propose to implement the dynamic decode-and-forward (DDF) protocol with distributed rotations. In addition to being the first minimum-delay implementation of the DDF protocol proposed for any number of relays, this technique allows to exploit cooperative diversity without inducing the high decoding complexity of a space-time code. The analysis of outage probabilities for different number of relays and rotations shows that the performance of this technique is close to optimal. Moreover, a lower-bound on the diversity-multiplexing gain tradeoff (DMT) is provided in the case of a single relay and two rotations. This lower-bound reaches the optimal DDF's DMT when the frame-length grows to infinity, which shows that even a small number of rotations is enough to obtain good performance.

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Towards a Low-Complexity Dynamic Decode-and-Forward Relay Protocol

The dynamic decode-and-forward (DDF) relaying protocol is a relatively new cooperative scheme which has been shown to achieve promising theoretical results in terms of diversity-multiplexing gain tradeoff and error rates. The case of a single relay has been extensively studied in the literature and several techniques to approach the optimum performance have been proposed. Until recently, however, a practical implementation for the case of several relays had been considered to be much more challenging. A rotation-based DDF technique, suitable for any number of relays, has been recently proposed which promises to overcome important implementation hurdles. This article provides an overview of the DDF protocol, describes different implementation techniques and compares their performance.

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On Coding for Cooperative Data Exchange

We consider the problem of data exchange by a group of closely-located wireless nodes. In this problem each node holds a set of packets and needs to obtain all the packets held by other nodes. Each of the nodes can broadcast the packets in its possession (or a combination thereof) via a noiseless broadcast channel of capacity one packet per channel use. The goal is to minimize the total number of transmissions needed to satisfy the demands of all the nodes, assuming that they can cooperate with each other and are fully aware of the packet sets available to other nodes. This problem arises in several practical settings, such as peer-to-peer systems and wireless data broadcast. In this paper, we establish upper and lower bounds on the optimal number of transmissions and present an efficient algorithm with provable performance guarantees. The effectiveness of our algorithms is established through numerical simulations.

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Design Guidelines for Training-based MIMO Systems with Feedback

In this paper, we study the optimal training and data transmission strategies for block fading multiple-input multiple-output (MIMO) systems with feedback. We consider both the channel gain feedback (CGF) system and the channel covariance feedback (CCF) system. Using an accurate capacity lower bound as a figure of merit, we investigate the optimization problems on the temporal power allocation to training and data transmission as well as the training length. For CGF systems without feedback delay, we prove that the optimal solutions coincide with those for non-feedback systems. Moreover, we show that these solutions stay nearly optimal even in the presence of feedback delay. This finding is important for practical MIMO training design. For CCF systems, the optimal training length can be less than the number of transmit antennas, which is verified through numerical analysis. Taking this fact into account, we propose a simple yet near optimal transmission strategy for CCF systems, and derive the optimal temporal power allocation over pilot and data transmission.

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Optimization of Information Rate Upper and Lower Bounds for Channels with Memory

We consider the problem of minimizing upper bounds and maximizing lower bounds on information rates of stationary and ergodic discrete-time channels with memory. The channels we consider can have a finite number of states, such as partial response channels, or they can have an infinite state-space, such as time-varying fading channels. We optimize recently-proposed information rate bounds for such channels, which make use of auxiliary finite-state machine channels (FSMCs). Our main contribution in this paper is to provide iterative expectation-maximization (EM) type algorithms to optimize the parameters of the auxiliary FSMC to tighten these bounds. We provide an explicit, iterative algorithm that improves the upper bound at each iteration. We also provide an effective method for iteratively optimizing the lower bound. To demonstrate the effectiveness of our algorithms, we provide several examples of partial response and fading channels, where the proposed optimization techniques significantly tighten the initial upper and lower bounds. Finally, we compare our results with an improved variation of the \emph{simplex} local optimization algorithm, called \emph{Soblex}. This comparison shows that our proposed algorithms are superior to the Soblex method, both in terms of robustness in finding the tightest bounds and in computational efficiency. Interestingly, from a channel coding/decoding perspective, optimizing the lower bound is related to increasing the achievable mismatched information rate, i.e., the information rate of a communication system where the decoder at the receiver is matched to the auxiliary channel, and not to the original channel.

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