Alabbasi, AbdulRahman; Rezki, Zouheir; Shihada, Basem(IEEE Transactions on Wireless Communications, Institute of Electrical and Electronics Engineers (IEEE), 2014-12-31)[Article]
In this paper, two resource allocation schemes for energy efficient cognitive radio systems are proposed. Our design considers resource allocation approaches that adopt spectrum sharing combined with soft-sensing information, adaptive sensing thresholds, and adaptive power to achieve an energy efficient system. An energy per good-bit metric is considered as an energy efficient objective function. A multi-carrier system, such as, orthogonal frequency division multiplexing, is considered in the framework. The proposed resource allocation schemes, using different approaches, are designated as sub-optimal and optimal. The sub-optimal approach is attained by optimizing over a channel inversion power policy. The optimal approach utilizes the calculus of variation theory to optimize a problem of instantaneous objective function subject to average and instantaneous constraints with respect to functional optimization variables. In addition to the analytical results, selected numerical results are provided to quantify the impact of soft-sensing information and the optimal adaptive sensing threshold on the system performance.
Bouida, Zied; Ghrayeb, Ali A.; Qaraqe, Khalid A.; Alouini, Mohamed-Slim(IEEE Transactions on Wireless Communications, Institute of Electrical and Electronics Engineers (IEEE), 2014-10)[Article]
In this paper, we propose a number of adaptive transmission techniques in order to improve the performance of the secondary link in a spectrum sharing system. We first introduce the concept of minimum-selection maximum ratio transmission (MS-MRT) as an adaptive variation of the existing MRT (MRT) technique. While in MRT all available antennas are used for transmission, MS-MRT uses the minimum subset of antennas verifying both the interference constraint (IC) to the primary user and the bit error rate (BER) requirements. Similar to MRT, MS-MRT assumes that perfect channel state information (CSI) is available at the secondary transmitter (ST), which makes this scheme challenging from a practical point of view. To overcome this challenge, we propose another transmission technique based on orthogonal space-time block codes with transmit antenna selection (TAS). This technique uses the full-rate full-diversity Alamouti scheme in order to maximize the secondary's transmission rate. The performance of these techniques is analyzed in terms of the average spectral efficiency (ASE), average number of transmit antennas, average delay, average BER, and outage performance. In order to give the motivation behind these analytical results, the tradeoffs offered by the proposed schemes are summarized and then demonstrated through several numerical examples.
Sorour, Sameh; Douik, Ahmed S.; Valaee, Shahrokh; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim(IEEE Transactions on Wireless Communications, Institute of Electrical and Electronics Engineers (IEEE), 2014-09)[Article]
In this paper, we study the multicast completion and decoding delay minimization problems for instantly decodable network coding (IDNC) in the case of lossy feedback. When feedback loss events occur, the sender falls into uncertainties about packet reception at the different receivers, which forces it to perform partially blind selections of packet combinations in subsequent transmissions. To determine efficient selection policies that reduce the completion and decoding delays of IDNC in such an environment, we first extend the perfect feedback formulation in our previous works to the lossy feedback environment, by incorporating the uncertainties resulting from unheard feedback events in these formulations. For the completion delay problem, we use this formulation to identify the maximum likelihood state of the network in events of unheard feedback and employ it to design a partially blind graph update extension to the multicast IDNC algorithm in our earlier work. For the decoding delay problem, we derive an expression for the expected decoding delay increment for any arbitrary transmission. This expression is then used to find the optimal policy that reduces the decoding delay in such lossy feedback environment. Results show that our proposed solutions both outperform previously proposed approaches and achieve tolerable degradation even at relatively high feedback loss rates.
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