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...ooser QoS guarantees. Similarly, if D denotes the steady-state delay experienced in the buffer, then P (D ≥ dmax) ≈ e−θδdmax for large dmax, where δ is determined by the arrival and service processes =-=[9]-=-. Let {R[i], i = 1, 2, . . .} denote the discrete-time stationary and ergodic stochastic service process and S[t] ∑t i=1 R[i] be the time-accumulated process. Assume that the GärtnerEllis limit of ...

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...ried by a resource block can be modeled as a finite-state Markov chain (FSMC) with N states, the effective capacity of the kth femto-MS which is allocated by one unoccupied resource block is given by =-=[27]-=- E(k,1)C (θ) = − 1 θ log ( ρ{P(k)Φ(1)(θ)} ) (12) where P(k) is the transition probability matrix of the FSMC, ρ{·} is the spectral radius of the matrix and Φ(1)(θ) = This full text paper was peer revi...

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...ughput under such constraints, we employ the effective capacity as a performance metric [12]. Recently, effective capacity analysis of wireless systems has attracted much interest (see e.g., [13] and =-=[14]-=-). In [15], we studied the cognitive transmission under quality of service (QoS) constraints. In [16], by initially performing channel sensing over multiple frequency bands to detect the activities of...

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...ooser QoS guarantees. Similarly, if D denotes the steady-state delay experienced in the buffer, then P (D ≥ dmax) ≈ e−θδdmax for large dmax, where δ is determined by the arrival and service processes =-=[11]-=-. Therefore, effective capacity formulation provides the maximum constant arrival rates that can be supported by the time-varying wireless channel under the queue length constraint P (Q ≥ qmax) ≤ e −θ...

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... the spectrum handoff process using our proposed Markov model. Besides the general random channel selection scheme, different channel selection schemes have been proposed for various design goals [9] =-=[17]-=- [18]. These channel selection schemes can be easily adopted in our proposed three dimensional discrete-time Markov chain if we apply different state transition probabilities in the proposed analytica...

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...ooser QoS guarantees. Similarly, if D denotes the steady-state delay experienced in the buffer, then P (D ≥ dmax) ≈ e−θδdmax for large dmax, where δ is determined by the arrival and service processes =-=[7]-=-. The effective capacity is given by −Λ(−θ) θ = − lim t→∞ 1 θt loge E{e−θS[t]} (8) where S[t] = ∑t k=1 R[k] is the time-accumulated service process and {R[k], k = 1, 2, . . .} denote the discrete-time...

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...l hopping when a data transmission ends, or start another data transmission by exchanging RTS/CTS packets. 2.3 Network Assumptions In this chapter, we model each licensed channel as an ON-OFF process =-=[13]-=- [14]. As shown in Fig. 3, each rectangle represents a PU data packet being transmitted on a channel (i.e., the ON period) and the other blank areas represent the idle periods (i.e., the OFF period). ...

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... T l Xminðl;ð1’ÞMÞ g0 g ClgC ð1’ÞMl ð1’ÞMg C ð1’ÞM ð1’ÞM 0 @ 1 A ð16Þ as the average number of RBs without suffering interference in each subframe. By applying the results in [27], =-=[28]-=-, the effective capacity per subframe that the machine utilizes l RBs in each data subframe without suffering interference is ElCðÞ lE1CðlÞ: ð17Þ By substituting l in (17) by l$lC in (16), we can ...