Search

A spectrum-sharing scenario in a cognitive radio (CR) network where a secondary user (SU) shares a narrowband channel with N primary users (PUs) is considered. We investigate the SU ergodic capacity maximization problem under an average transmit power constraint on the SU and N individual peak interference power constraints at each primary-user receiver (PU-Rx) with various forms of imperfect channel-state information (CSI) available at the secondary-user transmitter (SU-Tx). For easy exposition, we first look at the case when the SU-Tx can obtain perfect knowledge of the CSI from the SU-Tx to the secondary-user receiver link, which is denoted as g(1), but can only access quantized CSI of the SU-Tx to PU-Rx links, which is denoted as g(0i), i = 1, ... , N, through a limited-feedback link of B = log(2) L b. For this scenario, a locally optimum quantized power allocation (codebook) is obtained with quantized g(0i), i = 1, ... , N information by using the Karush-Kuhn-Tucker (KKT) necessary optimality conditions to numerically solve the nonconvex SU capacity maximization problem. We derive asymptotic approximations for the SU ergodic capacity performance for the case when the number of feedback bits grows large (B -> infinity) and/or there is a large number of PUs (N -> infinity) that operate. For the interference-limited regime, where the average transmit power constraint is inactive, an alternative locally optimum scheme, called the quantized-rate allocation strategy, based on the quantized-ratio g(1)/max(i) g(0i) information, is proposed. Subsequently, we relax the strong assumption of full-CSI knowledge of g(1) at the SU-Tx to imperfect g(1) knowledge that is also available at the SU-Tx. Depending on the way the SU-Tx obtains the g(1) information, the following two different suboptimal quantized power codebooks are derived for the SU ergodic capacity maximization problem: 1) the power codebook with noisy g(1) estimates and quantized g(0i), i = 1, ... , N knowledge and 2) another power codebook with both quantized g(1) and g(0i), i = 1, ... , N information. We emphasize the fact that, although the proposed algorithms result in locally optimum or strictly suboptimal solutions, numerical results demonstrate that they are extremely efficient. The efficacy of the proposed asymptotic approximations is also illustrated through numerical simulation results. Refereed/Peer-reviewed

We consider a wideband spectrum sharing system where a secondary user can access a number of orthogonal frequency bands each licensed to a distinct primary user. We address the problem of optimum secondary transmit power allocation for its ergodic capacity maximization subject to an average sum (across the bands) transmit power constraint and individual average interference constraints on the primary users. The major contribution of our work lies in considering quantized channel state information (CSI)(for the vector channel space consisting of all secondary-to-secondary and secondary-to-primary channels) at the secondary transmitter as opposed to the prevalent assumption of full CSI in most existing work. It is assumed that a central entity called a cognitive radio network manager has access to the full CSI information from the secondary and primary receivers and designs (offline) an optimal power codebook based on the statistical information (channel distributions) of the channels and feeds back the index of the codebook to the secondary transmitter for every channel realization in real-time, via a delay-free noiseless limited feedback channel. A modified Generalized Lloyds-type algorithm (GLA) is designed for deriving the optimal power codebook, which is proved to be globally convergent and empirically consistent. An approximate quantized power allocation (AQPA) algorithm is presented, that performs very close to its GLA based counterpart for large number of feedback bits and is significantly faster. We also present an extension of the modified GLA based quantized power codebook design algorithm for the case when the feedback channel is noisy. Numerical studies illustrate that with only 3-4 bits of feedback per band, the modified GLA based algorithms provide secondary ergodic capacity very close to that achieved by full CSI and with only as little as 4 bits of feedback per band, AQPA provides a comparable performance, thus making it an attractive choice for practical implementation. School of Information Technology and Mathematical Sciences Refereed/Peer-reviewed

In this paper, we consider a wideband spectrum sharing system where a secondary user can share orthogonal frequency bands with a number of primary users, each licensed to use an individual band. We address the problem of ergodic capacity maximization of the secondary user subject to an average sum (across the bands) transmit power constraint on the secondary user and individual average interference constraints on the primary users. After studying optimal power allocation with full channel state information (CSI) at the secondary transmitter, we focus on designing optimal power allocation strategies for the quantized CSI case. It is assumed that a band manager has the full CSI of all secondary-to-secondary and secondary-to-primary channels, and designs (ofine) an optimal power code book based on statistical information of the channels and feeds back the index of the codebook to the secondary transmitter for every channel realization. A modified generalized Lloyd type algorithm (GLA) is designed for an optimal power code book. With the narrowband case (one secondary and one primary user) in mind, various properties of the quantized powers are derived. It is observed that only 2-3 bits of feedback with this codebook is sufficient to provide secondary capacities close to the full CSI case. Refereed/Peer-reviewed

In this paper, we address the optimal power allocation problem for minimizing the notion of information theoretic outage for an M parallel block-Rayleigh-fading channels using a finite rate power codebook (limited feedback). In contrast to the existing literature on outage minimization for MIMO systems with limited feedback, we derive effective approximations to the channel quantization regions in order to design a number of low-complexity power allocation algorithms for various ranges of average power constraints. Unlike previous work, we show that it is not generally optimal to allocate same power to all channels, and that this is only asymptotically optimal at high average power (average SNR). We also derive a suitable Gaussian approximation based power allocation scheme for large number of parallel channels which has important practical applications in multi-carrier systems such as OFDM. Extensive numerical results illustrate that only a few bits of feedback (for M = 4 or M = 6) closes the gap substantially in outage performance with the full instantaneous channel information at the transmitter. For large number of channels, less than 1 bit of (broadcast) feedback per channel can achieve the same outage probability (10(-4)) with approximately only a 2.5 dB average power (or average SNR) gap. Refereed/Peer-reviewed