Compute-and-Forward on a Multi-User Multi-Relay Channel

In this paper, we consider a system in which multiple users communicate with a destination with the help of multiple half-duplex relays. Based on the compute-and-forward scheme, each relay, instead of decoding the users' messages, decodes an integer-valued linear combination that relates the transmitted messages. Then, it forwards the linear combination towards the destination. Given these linear combinations, the destination may or may not recover the transmitted messages since the linear combinations are not always full rank. Therefore, we propose an algorithm where we optimize the precoding factor at the users such that the probability that the equations are full rank is increased and that the transmission rate is maximized. We show, through some numerical examples, the effectiveness of our algorithm and the advantage of performing precoding allocation at the users. Also, we show that this scheme can outperform standard relaying techniques in certain regimes

Evaluation, Modeling and Optimization of Coverage Enhancement Methods of NB-IoT

Narrowband Internet of Things (NB-IoT) is a new Low Power Wide Area Network (LPWAN) technology released by 3GPP. The primary goals of NB-IoT are improved coverage, massive capacity, low cost, and long battery life. In order to improve coverage, NB-IoT has promising solutions, such as increasing transmission repetitions, decreasing bandwidth, and adapting the Modulation and Coding Scheme (MCS). In this paper, we present an implementation of coverage enhancement features of NB-IoT in NS-3, an end-to-end network simulator. The resource allocation and link adaptation in NS-3 are modified to comply with the new features of NB-IoT. Using the developed simulation framework, the influence of the new features on network reliability and latency is evaluated. Furthermore, an optimal hybrid link adaptation strategy based on all three features is proposed. To achieve this, we formulate an optimization problem that has an objective function based on latency, and constraint based on the Signal to Noise Ratio (SNR). Then, we propose several algorithms to minimize latency and compare them with respect to accuracy and speed. The best hybrid solution is chosen and implemented in the NS-3 simulator by which the latency formulation is verified. The numerical results show that the proposed optimization algorithm for hybrid link adaptation is eight times faster than the exhaustive search approach and yields similar latency

Network coding for the multiple access relay channel

To cope with the growing demands of wireless applications and mobile internet, wireless communications is expected to provide high data rate. Cooperative communications has been presented to increase the throughput, the reliability and the robustness of the wireless system. Recently, network coding has been introduced to further increase the throughput. In contrast to the conventional network coding techniques where they are performed in the upper layer of the protocol stack, in this thesis we focus on network coding techniques which are performed in the physical layer for the multiaccess relay channel (MARC) system. In the first part of the thesis, we consider a two-user multiaccess relay channel where the relay implements decode-and-forward strategy. In this model, the users are allowed to simultaneously transmit their messages on the same channel. This is a form of physical-layer network coding where simultaneous transmissions are observed by the relay as a linear combination. For this transmission scheme, we discuss the design criteria and evaluate the achievable sum-rate. Also, we study the problem of allocating the resources optimally in order to maximize the achievable sum-rate. We show that by allowing the users to simultaneously transmit their messages on the same channel, one can afford a larger sum-rate compared to the case where the users transmit their messages on orthogonal channels. In the second part of the thesis, we further study the MARC model. Based on the compute-and-forward scheme, we establish three coding schemes that are of network coding spirit. In these schemes, the destination does not decode the information messages directly from its output, but uses it to recover two linearly independent integer-valued combinations that relate the transmitted messages. The three schemes differ essentially through the operations implemented by the relay. In the first one, the relay implements compute-and-forward. In the second one, the relay implements compress-and-forward and in the third one the relay implements amplify-and-forward. We show that the first scheme can outperform standard relaying techniques in certain regimes. Also, we show that the second and third schemes, while relying on feasible structured lattice codes, can at best achieve the same performance as regular compress-and-forward and amplify-and-forward, respectively. In the last part of the thesis, we consider the multi-user multi-relay network with compute-and-forward strategy. We propose an efficient algorithm to allocate the powers at the users and to find the integer coefficients of the linear combinations in such a way that the transmission rate is maximized and that the computed linear combinations are linearly independent.(FSA - Sciences de l) -- UCL, 201

Amplify-and-Forward on a Multiaccess Relay Channel With Computation at the Receiver

International audienceWe consider a communication system in which two sources communicate with a destination with the help of a common relay. We assume that the relay operates in half-duplex mode; and concentrate on the symmetric-rate case. We study and analyse the performance of a simple strategy in which the relay simply amplifies its output and retransmits it. However, unlike standard amplify-and-forward, the destination recovers the sent messages by computing and inverting two appropriate linear combinations of the sources' messages, obtained using what it gets from the sources and the relay. We discuss the design criteria and establish the sum-rate allowed by this strategy. Also, we consider, and solve, the problem of maximizing the sum-rate by properly optimizing the power values and the integer-valued coefficients of the recovered linear combinations. It should be emphasized that although the coding strategy described in this paper performs only as good as standard amplify-and-forward, it has the advantage of utilizing simpler linear codes; and, so, is more relevant in practical collaborative systems

Compress-and-Forward on a Multiaccess Relay Channel With Computation at the Receiver

International audienceWe study a system in which two sources communicate with a destination with the help of a half-duplex relay. We consider a decoding strategy, based on the compute-and-forward strategy, in which the destination decodes two integer-valued linear combinations that relate the transmitted codewords. In this strategy, the relay compresses its observation using Wyner- Ziv compression and then forwards it to the destination. The destination appropriately combines what it gets from the direct transmission and the relay. Then, using this combination, it computes two integer-valued linear combinations. We discuss the encoding/decoding strategy, and evaluate the achievable sumrate. Next, we consider the problem of allocating the powers and selecting the integer-valued coefficients of the recovered linear combinations in order to maximize the sum-rate. For the model under consideration, the optimization problem is NP hard. We propose an iterative algorithm to solve this problem using coordinate descent method. The results are illustrated through some numerical examples

Iterative sum-rate optimization for multiple access relay channels with a compute-and-forward relay

International audienceWe consider a multiple access relay channel (MARC), in which a relay, based on the recently proposed compute-and-forward protocol, helps two transmitters to communicate with a common destination. The relay decodes a linear combination of the received symbols instead of the individual symbols then forwards the new symbol to the destination. The destination recovers two linear equations from the decoded signals. The two equations relate the transmitted symbols with integer coefficients at different computational rates. We propose an iterative algorithm to optimize the integer coefficients and the power allocation at the transmitters alternatively, so that the sum-rate is maximized. In each iteration, the integer coefficients are updated by solving a mixed-integer quadratic programming (MIQP) problem with quadratic constraints, while the power allocation is updated by solving a series of geometric programs using a successive convex approximation method. The simulation results show that the compute-and-forward strategy and the proposed optimization method can offer substantial gain over the standard amplify-and-forward and decode-and-forward protocols for this model

Compress-and-Forward on a Multiaccess Relay Channel With Computation at the Receiver

Abstract-We study a system in which two sources communicate with a destination with the help of a half-duplex relay. We consider a decoding strategy, based on the compute-and-forward strategy, in which the destination decodes two integer-valued linear combinations that relate the transmitted codewords. In this strategy, the relay compresses its observation using WynerZiv compression and then forwards it to the destination. The destination appropriately combines what it gets from the direct transmission and the relay. Then, using this combination, it computes two integer-valued linear combinations. We discuss the encoding/decoding strategy, and evaluate the achievable sumrate. Next, we consider the problem of allocating the powers and selecting the integer-valued coefficients of the recovered linear combinations in order to maximize the sum-rate. For the model under consideration, the optimization problem is NP hard. We propose an iterative algorithm to solve this problem using coordinate descent method. The results are illustrated through some numerical examples

Resource Allocation for Multiple Access Relay Channel with a Compute-and-Forward Relay

International audienceAbstract--In this work1, we study a multiaccess relay channel (MARC). The system consists of two transmitters communicating with a destination with the help of a half-duplex relay. We extend and adapt the recently proposed lattice-based computeand- forward coding scheme to the model we study. This coding scheme can be seen as a form of some network-coding that is implemented at the relay through modulo-reduction. In this scheme, the destination decodes two linear equations with integer coefficients that relate the transmitted symbols at different computational rates. First, we discuss the design criteria, and derive the allowed computation rate. Then, we optimally allocate the different parameters by solving a series of geometric programs using successive convex approximation methods. The analysis shows that our coding scheme can offer substantial gain over the standard amplify-and-forward and decode-and-forward for this model. We illustrate our results through some numerical examples

Compute-and-forward on a multiaccess relay channel: Coding and symmetric-rate optimization

We consider a system in which two users communicate with a destination with the help of a half-duplex relay. Based on the compute-and-forward scheme, we develop and evaluate the performance of coding strategies that are of network coding spirit. In this framework, instead of decoding the users' information messages, the destination decodes two integer-valued linear combinations that relate the transmitted codewords. Two decoding schemes are considered. In the first one, the relay computes one of the linear combinations and then forwards it to the destination. The destination computes the other linear combination based on the direct transmissions. In the second one, accounting for the side information available at the destination through the direct links, the relay compresses what it gets using lattice-based Wyner-Ziv compression and conveys it to the destination. The destination then computes the two linear combinations, locally. For both coding schemes, we discuss the design criteria, and derive the allowed symmetric-rate. Next, we address the power allocation and the selection of the integer-valued coefficients to maximize the offered symmetric-rate; an iterative coordinate descent method is proposed. The analysis shows that the first scheme can outperform standard relaying techniques in certain regimes, and the second scheme, while relying on feasible structured lattice codes, can at best achieve the same performance as regular compress-and-forward for the multiaccess relay network model that we study. The results are illustrated through some numerical examples. © 2002-2012 IEEE

Codage Réseau pour Canal à Accès Multiple avec Relai

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