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Breaking Spectrum Gridlock with Cognitive Radios: An Information Theoretic Perspective
, 2008
"... Cognitive radios hold tremendous promise for increasing spectral efficiency in wireless systems. This paper surveys the fundamental capacity limits and associated transmission techniques for different wireless network design paradigms based on this promising technology. These paradigms are unified b ..."
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Cited by 247 (3 self)
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Cognitive radios hold tremendous promise for increasing spectral efficiency in wireless systems. This paper surveys the fundamental capacity limits and associated transmission techniques for different wireless network design paradigms based on this promising technology. These paradigms are unified by the definition of a cognitive radio as an intelligent wireless communication device that exploits side information about its environment to improve spectrum utilization. This side information typically comprises knowledge about the activity, channels, codebooks and/or messages of other nodes with which the cognitive node shares the spectrum. Based on the nature of the available side information as well as a priori rules about spectrum usage, cognitive radio systems seek to underlay, overlay or interweave the cognitive radios ’ signals with the transmissions of noncognitive nodes. We provide a comprehensive summary of the known capacity characterizations in terms of upper and lower bounds for each of these three approaches. The increase in system degrees of freedom obtained through cognitive radios is also illuminated. This information theoretic survey provides guidelines for the spectral efficiency gains possible through cognitive radios, as well as practical design ideas to mitigate the coexistence challenges in today’s crowded spectrum.
Achieving Linear Scaling with Interference Alignment
"... Abstract — Recent results have shown that interference alignment can achieve K/2 degrees of freedom in a Kuser interference channel with time or frequency varying channel coefficients. For fixed number of users K, the number of degrees of freedom characterizes the asymptotic behavior of the perform ..."
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Cited by 12 (2 self)
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Abstract — Recent results have shown that interference alignment can achieve K/2 degrees of freedom in a Kuser interference channel with time or frequency varying channel coefficients. For fixed number of users K, the number of degrees of freedom characterizes the asymptotic behavior of the performance in the high SNR limit but it does not answer the question of how the performance scales with K for any fixed SNR. In particular, it is unclear if a constant rate per user can be maintained as more users enter into the system. In this paper, we investigate the performance of the interference alignment scheme proposed in [5] for fixed SNR. We assume that the channel coefficients between the users are of the form r e jθ where r is fixed over the duration of communication and θ is a fast fading phase. We show that for any value of the SNR and K, the aggregate rate achieved by the interference alignment scheme of [5] is lower bounded by c1K log(1 + c2 SNR) where c1 and c2 are positive constants independent of both SNR and K. This result establishes the linear scaling of the interference alignment scheme for the considered random phase channel model. I.
On the Maximum SumRate of Cognitive MIMO Interference Channels
"... Abstract—In this paper, we address the problem of maximizing the ergodic sumrate of an Nuser cognitive MIMO Interference Channel (IC) formed by unlicensed (or secondary) users. We assume that N secondary users coexist in the same area and try to access the same set of frequency bands. In such a se ..."
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Abstract—In this paper, we address the problem of maximizing the ergodic sumrate of an Nuser cognitive MIMO Interference Channel (IC) formed by unlicensed (or secondary) users. We assume that N secondary users coexist in the same area and try to access the same set of frequency bands. In such a setup, we define a cognitive MIMO IC as an extension of a classical IC where each user has multiple antennas and multiple frequency bands for transmission. We further assume a typical cognitive radio scenario where the structure of interference signals is not known and interference cancelation is not possible. Therefore, interference is treated as Gaussian noise in this work. The problem of ergodic sumrate maximization reduces to the problem of finding the optimal power allocation for each user over each spatial channel in each frequency band. This problem belongs to the class of nonlinear nonconvex optimization problems and is hence challenging to solve analytically. We extend a reformulation and linearization (RLT) based branch and bound (BB) method to solve this problem. BB/RLT was recently proposed to solve the sumrate maximization problem of a single band MIMO IC with the guaranteed convergence to the global optimum. It should be noted that we are proposing an optimal power control scheme to perform power control simultaneously over spatial and spectral dimensions without any explicit interference cancelation or Interference Alignment (IA). We also present some interesting comparisons between the sumrates achievable by the proposed scheme and those by IA. Index Terms—Cognitive MIMO radio, interference channels, interference alignment, maximum sumrate, nonlinear nonconvex programming. I.
On the SumRate of MIMO Interference Channel
"... Abstract—The problem of maximizing the sumrate of a MIMO interference channel is investigated. Each receiver node is assumed to perform single user detection by treating interference from other users as Gaussian noise. It is assumed that all the users share a single frequency band and no precoding ..."
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Abstract—The problem of maximizing the sumrate of a MIMO interference channel is investigated. Each receiver node is assumed to perform single user detection by treating interference from other users as Gaussian noise. It is assumed that all the users share a single frequency band and no precoding is performed over time. The sumrate maximization in such a setup is a longstanding open problem due to its nonlinear nonconvex nature. The solution, to date, has only been approximated using the local optimization algorithms. In this paper, we couple the branch and bound strategy with the reformulation and linearization technique (BB/RLT) to develop a global optimization algorithm that finds a provably optimal solution. This problem is essentially an optimal power control problem over spatial channels and should not be confused with some recent developments such as Interference Alignment (IA) that typically require precoding over temporal, spectral or spatial dimensions. As a comparison with the state of the art, we compare the sumrate achievable in the current system with the one predicted by IA and draw some interesting conclusions. It should be noted however, that even though the sumrate achievable by IA can be predicted by assuming N/2 degrees of freedom in an Nuser interference channel, the feasibility of IA over a limited number of signaling dimensions is an open problem. Index Terms—MIMO interference channel, optimal sumrate, optimal power control, interference alignment, nonconvex nonlinear programming. I.
1 Degrees of Freedom Region for an Interference Network with General Message Demands
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