8 research outputs found
Transmission Schemes based on Sum Rate Analysis in Distributed Antenna Systems
In this paper, we study single cell multi-user downlink distributed antenna
systems (DAS) where antenna ports are geographically separated in a cell.
First, we derive an expression of the ergodic sum rate for the DAS in the
presence of pathloss. Then, we propose a transmission selection scheme based on
the derived expressions which does not require channel state information at the
transmitter. Utilizing the knowledge of distance information from a user to
each distributed antenna (DA) port, we consider the optimization of pairings of
DA ports and users to maximize the system performance. Based on the ergodic sum
rate expressions, the proposed scheme chooses the best mode maximizing the
ergodic sum rate among mode candidates. In our proposed scheme, the number of
mode candidates are greatly reduced compared to that of ideal mode selection.
In addition, we analyze the signal to noise ratio cross-over point for
different modes using the sum rate expressions. Through Monte Carlo
simulations, we show the accuracy of our derivations for the ergodic sum rate.
Moreover, simulation results with the pathloss modeling confirm that the
proposed scheme produces the average sum rate identical to the ideal mode
selection with significantly reduced candidates.Comment: 25 pages, 8 figures, submitted to IEEE Transactions on Wireless
Communications, May 201
Energy Efficient Power Allocation for Distributed Antenna System over Shadowed Nakagami Fading Channel
In this paper, the energy efficiency (EE) of downlink distributed antenna system (DAS) with multiple receive antennas is investigated over composite fading channel that takes the path loss, shadow fading and Nakagami-m fading into account. Our aim is to maximize EE which is defined as the ratio of the transmission rate to the total consumed power under the constraints of maximum transmit power of each remote antenna. According to the definition of EE and using the upper bound of average EE, the optimized objective function is provided. Based on this, utilizing Karush-Kuhn-Tucker (KKT) conditions and mathematical derivation, a suboptimal energy efficient power allocation (PA) scheme is developed, and closed-form PA coefficients are obtained. The developed scheme has the EE performance close to the existing optimal scheme. Moreover, it has relatively lower complexity than the existing scheme because only the statistic channel information and less iteration are required. Besides, it includes the scheme in composite Rayleigh channel as a special case. Simulation results show the effectiveness of the developed scheme
Optimal Energy-Efficient Power Allocation Scheme with Low Complexity for Distributed Antenna System
In this paper, by maximizing the energy efficiency (EE), an optimal power allocation scheme is developed for downlink distributed antenna system (DAS). Different from conventional optimal power allocation schemes that need iterative calculation, the developed scheme can provide closed-form power allocation and no iteration is required. Based on the definition of EE, the optimized objective function is firstly formulated, and then a computationally efficient algorithm is proposed to obtain the optimal number of active remote antennas and the corresponding power allocation. Using the optimal number, the multidimensional solution for the optimized function is transformed into searching one-dimensional solution. As a result, closed-form expression of power allocation coefficients is attained. Numerical results verify the effectiveness of the proposed scheme. The scheme can obtain the same EE as the conventional optimal scheme but with lower complexity, and it has more accuracy than the existing low-complexity scheme
Energy Efficiency Optimization for MIMO Distributed Antenna Systems
In this paper, we propose a transmit covariance optimization method to maximize the energy efficiency (EE) for a single-user distributed antenna system, where both the remote access units (RAUs) and the user are equipped with multiple antennas. Unlike previous related work, both the rate requirement and the RAU selection are taken into consideration. Here, the total circuit power consumption is related to the number of active RAUs. Given this setup, we first propose an optimal transmit covariance optimization method to solve the EE optimization problem under a fixed set of active RAUs. More specifically, we split this problem into three subproblems, namely, the rate maximization problem, the EE maximization problem without rate constraint, and the power minimization problem, and each subproblem can be efficiently solved. Then, a novel distance-based RAU selection method is proposed to determine the optimal set of active RAUs. Simulation results show that the performance of the proposed RAU selection is almost identical to the optimal exhaustive search method with significantly reduced computational complexity, and the performance of the proposed algorithm significantly outperforms the existing EE optimization methods