Joint Optimization of Bit and Power Loading for Multicarrier Systems

Bedeer, Ebrahim; Dobre, Octavia A.; Ahmed, Mohamed H.; Baddour, Kareem E.

doi:10.1109/wcl.2013.052813.130085

Cited by 20 publications

(14 citation statements)

References 6 publications

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“…To prove Proposition 1(i), we first show that the achievable rate R(H, Q) can be asymptotically characterized by C MT and Q regardless of channel realization H. Combining (38) and (39), we obtain (37). With Remark 1, we can obtain an upper bound for the full CSIT capacity as detailed below.…”

Section: A Proof Of Propositionmentioning

confidence: 96%

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Transmitter Design for Uplink MIMO Systems With Antenna Correlation

Wang

Zhang

et al. 2015

IEEE Trans. Wireless Commun.

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We study the uplink transmission in multiple-input multiple-output (MIMO) systems with antenna correlation. We focus on schemes that require only channel covariance information at the transmitter (CCIT), which involves lower cost than full channel state information at the transmitter (CSIT). We start from mutual information analysis and show that a simple CCIT-based scheme, referred to as statistical water-filling (SWF), can perform close to the optimal full CSIT-based one in MIMO systems with more receive antennas than transmit ones. We then focus on the implementation of SWF in practically coded systems. An iterative linear minimum mean squared error (LMMSE) receiver is assumed and an extrinsic information transfer (EXIT) chart type curve matching technique is developed based onHadamard precoding techniques. Simulation results show that the proposed scheme can obtain significant performance improvement compared to the conventional equal power transmission. Finally, we show that the proposed scheme is also very efficient in multi-user uplink MIMO systems with distributed channel information. Index Terms-Uplink MIMO, antenna correlation, channel covariance information.1536-1276 (c) (S'05-M'10) received the B. Eng. degree in telecommunication engineering and the M. Eng. degree in information engineering, from Xidian University,

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Section: A Proof Of Propositionmentioning

confidence: 96%

“…In a MIMO channel with antenna correlation, information rates should be carefully allocated to different channel eigen-directions. Adaptive modulation is a standard approach for this purpose [37], [38]. Denote the number of bits carried by the symbol on the n-th eigen-direction by Q n , and its average over all eigen-directions byQ.…”

Section: Introductionmentioning

confidence: 99%

Transmitter Design for Uplink MIMO Systems With Antenna Correlation

Wang

Zhang

et al. 2015

IEEE Trans. Wireless Commun.

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“…Recently, MOOP has attracted researchers' attention due to its flexible and superior performance over single objective optimization approaches [10]. For most of the MOOP problems, due to the contradiction and incommensurability of the competing objective functions, it is not possible to find a single solution that optimizes all the objective functions simultaneously.…”

Section: Optimization Problem and Proposed Algorithmmentioning

confidence: 99%

Rate-interference tradeoff in OFDM-based cognitive radio networks

Bedeer

Dobre

Ahmed

et al. 2014

2014 IEEE Global Communications Conference

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Abstract-In cognitive radio (CR) networks, secondary users (SUs) are allowed to opportunistically access the primary users (PUs) spectrum to improve the spectrum utilization; however, this increases the interference levels at the PUs. In this paper, we consider an orthogonal frequency division multiplexing OFDM-based CR network and investigate the tradeoff between increasing the SU transmission rate (hence improving the spectrum utilization) and reducing the interference levels at the PUs. We formulate a new multiobjective optimization (MOOP) problem that jointly maximizes the SU transmission rate and minimizes its transmit power, while imposing interference thresholds to the PUs. Further, we propose an algorithm to strike a balance between the SU transmission rate and the interference levels to the PUs. The proposed algorithm considers the practical scenario of knowing partial channel state information (CSI) of the links between the SU transmitter and the PUs receivers. Simulation results illustrate the performance of the proposed algorithm and its superiority when compared to the work in the literature.

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“…MOPs are considered widely in recent literature (e.g. [23]- [28]). In detail, considering multicarrier systems, [23] proposed an algorithm to jointly maximize the throughput and minimize the transmission power while satisfying target constraints on the bit-error-rate (BER) per subcarrier and on the total transmit power.…”

Section: Introductionmentioning

confidence: 99%

Interference Efficiency: A New Metric to Analyze the Performance of Cognitive Radio Networks

Mili

Musavian

2017

IEEE Trans. Wireless Commun.

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In this paper, we develop and analyze a novel performance metric, called interference efficiency, which shows the number of transmitted bits per unit of interference energy imposed on the primary users (PUs) in an underlay cognitive radio network (CRN). Specifically, we develop a framework to maximize the interference efficiency of a CRN with multiple secondary users (SUs) while satisfying target constraints on the average interference power, total transmit power, and minimum ergodic rate for the SUs. In doing so, we formulate a multiobjective optimization problem (MOP) that aims to maximize ergodic sum rate of SUs and to minimize average interference power on the primary receiver. We solve the MOP by first transferring it into a single objective problem (SOP) using a weighted sum method. Considering different scenarios in terms of channel state information (CSI) availability to the SU transmitter, we investigate the effect of CSI on the performance and power allocation of the SUs. When full CSI is available, the formulated SOP is nonconvex and is solved using augmented penalty method (also known as the method of multiplier). When only statistical information of the channel gains between the SU transmitters and the PU receiver is available, the SOP is solved using Lagrangian optimization. Numerical results are conducted to corroborate our theoretical analysis.

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Joint Optimization of Bit and Power Loading for Multicarrier Systems

Cited by 20 publications

References 6 publications

Transmitter Design for Uplink MIMO Systems With Antenna Correlation

Transmitter Design for Uplink MIMO Systems With Antenna Correlation

Rate-interference tradeoff in OFDM-based cognitive radio networks

Interference Efficiency: A New Metric to Analyze the Performance of Cognitive Radio Networks

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