Achievable Rates and Scaling Laws of Power-Constrained Wireless Sensory Relay Networks

Dept. of Electr. Eng., Arizona State Univ., Tempe, AZ
IEEE Transactions on Information Theory (Impact Factor: 2.33). 10/2006; 52(9):4084 - 4104. DOI: 10.1109/TIT.2006.880029
Source: DBLP


A wireless sensory relay network consists of one source node, one destination node and multiple intermediate relay nodes. In this paper, we study the achievable rates and the scaling laws of power-constrained wireless relay networks in the wideband regime, assuming that relay nodes have no a priori knowledge of channel-state information (CSI) for both the backward channels and the forward channels. We examine the achievable rates in the joint asymptotic regime of the number of relay nodes n, the channel coherence interval L, and the bandwidth W (or the SNR per link rho). We first study narrowband relay networks in the low SNR regime. We investigate a relaying scheme, namely amplify-and-forward (AF) with network training, in which the source node and the destination node broadcast training symbols and each relay node carries out channel estimation and then applies AF relaying to relay information. We provide an equivalent source-to-destination channel model, and characterize the corresponding achievable rate. Our findings show that when rhoL, proportional to the transmission energy in each fading block, is bounded below, the achievable rate has the same scaling order as in coherent relaying, thus enabling us to characterize the scaling law of the relay networks in the low SNR regime. We then generalize the study to power-constrained wideband relay networks, where frequency-selective fading is taken into account. Again, the focus is on the achievable rates by using AF with network training for information relaying. In particular, we examine the scaling behavior of the achievable rates corresponding to two power allocation policies across the frequency subbands at relay nodes, namely, a simple equal power allocation policy and the optimal power allocation policy. We identify the conditions under which the scaling law of the wideband relay networks can be achieved by both power allocation policies. Somewhat surprising, our findings indicate that these two power allocati-
on policies result in achievable rates of the same scaling order, and the scaling law can be characterized under the condition that L/W, proportional to the energy per fading block per subband, is bounded below, and that W is sublinear in n

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    • "in the slow-fading scenario, once a channel is in deep fade, channel coding may not help to increase the reliability of the transmission. If available, cooperative transmission can dramatically improve the performance by creating diversity using the antennas available at the other nodes of the network [17]. However, many applications do not have access to such helpers in the network to improve reliability. "
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    ABSTRACT: In this paper, we revisit the design of Raptor codes for binary input additive white Gaussian noise (BI-AWGN) channels, where we are interested in very low signal to noise ratios (SNRs). A linear programming degree distribution optimization problem is defined for Raptor codes in the low SNR regime through several approximations. We also provide an exact expression for the polynomial representation of the degree distribution with infinite maximum degree in the low SNR regime, which enables us to calculate the exact value of the fractions of output nodes of small degrees. A more practical degree distribution design is also proposed for Raptor codes in the low SNR regime, where we include the rate efficiency and the decoding complexity in the optimization problem, and an upper bound on the maximum rate efficiency is derived for given design parameters. Simulation results show that the Raptor code with the designed degree distributions can approach rate efficiencies larger than 0.95 in the low SNR regime.
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    • "Michalopoulos and Karagiannidis [6] investigated the relay selection problem in the Rayleigh fading environment . The achievable data rate in CC networks was studied in [7], [8]. In addition, the relay selection and power allocation in CC networks were investigated in [9], [10], but the network lifetime was not considered in these papers. "
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    ABSTRACT: In cognitive radio cooperative communication (CR-CC) systems, the achievable data rate can be improved by increasing the transmission power. However, the increase in power consumption may cause the interference with primary users and reduce the network lifetime. Most previous work on CR-CC did not take into account the tradeoff between the achievable data rate and network lifetime. To fill this gap, this paper proposes an energy-efficient joint relay selection and power allocation scheme in which the state of a relay is characterized by the channel condition of all related links and its residual energy. The CR-CC system is formulated as a multi-armed restless bandit problem where the optimal policy is decided in a distributed way. The solution to the restless bandit formulation is obtained through a first-order relaxation method and a primal-dual priority-index heuristic, which can reduce dramatically the on-line computation and implementation complexity. According to the obtained index, each relay can determine whether to provide relaying or not and also can control the corresponding transmission power. Extensive simulation experiments are conducted to investigate the effectiveness of the proposed scheme. The results demonstrate that the power consumption is reduced significantly and the network lifetime is increased more than 40%.
    IEEE Journal on Selected Areas in Communications 11/2013; 31(11):2442-2452. DOI:10.1109/JSAC.2013.131129 · 3.45 Impact Factor
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    • "However, they assume differential demodulation which avoids the need for channel estimation. In [12], Wang et al. aim to optimize the training and data powers with average received signal-to-noise ratio (SNR) as their objective function. Their transmission scenario is mainly limited to a multi-hop scenario where there is no direct link 1536-1276/09$25.00 "
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    ABSTRACT: Cooperative communication techniques promise the advantages of multi-input multi-output (MIMO) communications for wireless scenarios with single-antenna terminals. A main assumption in majority of the research work on cooperative communications is the availability of channel state information at the receiver. In practice, knowledge of the channel is obtained by sending known training (pilot) symbols to the receiver. In this paper, we study the effect of training on the performance of an amplify-and-forward cooperative relaying system with pilot-assisted channel estimator over quasi-static Rayleigh fading channels. We consider average received signal-to-noise ratio at the destination node as the objective function and formulate optimization problems for a single-relay scenario under total network power (TNP) and individual node power (INP) constraints. We aim to answer the following fundamental questions: Q1) How should overall transmit power be shared between training and data transmission periods?; Q2) How should training power be allocated to broadcasting and relaying phases?; Q3) How should data power be allocated to broadcasting and relaying phases? Our simulation results demonstrate that optimized schemes significantly outperform the original schemes with equal power allocation. Depending on the relay location, performance gains up to 5.5 dB and 2.8 dB are observed, respectively, under TNP and INP constraints.
    IEEE Transactions on Wireless Communications 10/2009; 8(9-8):4773 - 4783. DOI:10.1109/TWC.2009.081382 · 2.50 Impact Factor
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