“…have been proposed for transmit power minimization such as in [12], [14]. In this paper, without loss of generality, we use the Bandwidth Assignment Based on SNR (BABS) algorithm to compute the number of subchannels per user and the Amplitude-Craving Greedy (ACG) algorithm for subchannel assignment.…”
Abstract-With Cell DTx, a base station can dynamically be switched to sleep mode during very short periods (inferior to frame duration) in order to reduce its energy consumption. In this paper, we study the problem of energy consumption minimization with Cell DTx for the downlink of an Orthogonal Frequency Division Multiple Access (OFDMA) base station. We show that this problem can be rewritten as a convex problem. Then, we derive interpretable expressions for the transmit power and sleep mode duration which minimize the energy consumption. Besides, we show that resource allocation algorithms already proposed for transmit power minimization have near optimal performance. Simulation results show that up to 38% of base station energy consumption can be saved with Cell DTx.
“…have been proposed for transmit power minimization such as in [12], [14]. In this paper, without loss of generality, we use the Bandwidth Assignment Based on SNR (BABS) algorithm to compute the number of subchannels per user and the Amplitude-Craving Greedy (ACG) algorithm for subchannel assignment.…”
Abstract-With Cell DTx, a base station can dynamically be switched to sleep mode during very short periods (inferior to frame duration) in order to reduce its energy consumption. In this paper, we study the problem of energy consumption minimization with Cell DTx for the downlink of an Orthogonal Frequency Division Multiple Access (OFDMA) base station. We show that this problem can be rewritten as a convex problem. Then, we derive interpretable expressions for the transmit power and sleep mode duration which minimize the energy consumption. Besides, we show that resource allocation algorithms already proposed for transmit power minimization have near optimal performance. Simulation results show that up to 38% of base station energy consumption can be saved with Cell DTx.
“…For (7), we apply the relaxation technique to convert binary variables into continuous ones. Then we use Lagrange dual function which has been widely utilized for solving OFDMA-based resource allocation problems [6], [22].…”
Section: Proposed Algorithmmentioning
confidence: 99%
“…Now, by considering y ks,n = α ks,n P ks,n , the total rate of OFDMA can be rewritten as [6], [22], R OFDMA ks,n (α, y) = α ks,n log 2 (1 + y ks,n h ks,n α ks,n σ 2 ).…”
Section: B Dual Approach For Ofdma-based Resource Allocationmentioning
confidence: 99%
“…To solve the convex problem (18), the iterative algorithm based on the dual function can be applied with a low computational complexity as demonstrated in [6], [22] which is summarized in Algorithm 2.…”
“…OFDMA uplink and downlink have been considered by several authors, and many solutions have been proposed [11][12][13][14][15][16][17][18]. In general, there are three different approaches to solve such a mixed integer programming problem: The exhaustive search checks all possible subcarrier assignments [16,18], relaxing of constraints transforms integers into real valued variables [11,14] and dual decomposition searches for the optimal CA in the dual domain [16,17]. Yin and Lui [13] showed that the subcarrier allocation for the OFDMA downlink can be solved efficiently by the Hungarian algorithm.…”
Within this article, the resource allocation problem for the multiple-access relay channel with orthogonal channel access is analysed. We propose a centralised optimisation framework that maximises the achievable sum rate of the network and that can be applied to a wide range of scenarios. We analyse different approaches to tackle the problem with individual transmit power constraints such as relaxing of constraints and splitting of the joint problem into a carrier allocation and individual power allocations. The carrier allocation deals with the exclusive assignment of subcarriers to different users, and the power allocation addresses the distribution of available power over assigned subcarriers. Several approaches are proposed for amplify and forward, decode and forward, and compress and forward strategies, and the performance as well as computational effort is evaluated by simulations. The obtained results suggest that the proposed algorithms can perform close to optimal.
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