Consider the multiple-input multiple-output (MIMO) interfering broadcast channel whereby multiple base stations in a cellular network simultaneously transmit signals to a group of users in their own cells while causin...
详细信息
Consider the multiple-input multiple-output (MIMO) interfering broadcast channel whereby multiple base stations in a cellular network simultaneously transmit signals to a group of users in their own cells while causing interference to each other. The basic problem is to design linear beamformers that can maximize the system throughput. In this paper, we propose a linear transceiver design algorithm for weighted sum-rate maximization that is based on iterative minimization of weighted mean-square error (MSE). The proposed algorithm only needs local channel knowledge and converges to a stationary point of the weighted sumrate maximization problem. Furthermore, the algorithm and its convergence can be extended to a general class of sum-utility maximization problem. The effectiveness of the proposed algorithm is validated by numerical experiments.
Simultaneous wireless information and power transfer (SWIPT) is a promising technique to transfer information and energy signals at the same time and frequency utilizing the multi-input multioutput (MIMO) beamforming....
详细信息
Simultaneous wireless information and power transfer (SWIPT) is a promising technique to transfer information and energy signals at the same time and frequency utilizing the multi-input multioutput (MIMO) beamforming. In this correspondence, the SWIPT MIMO technique is realized in themulticell cooperative transmission environment, namely, network-MIMO where the signals fromdifferent base-stations (BSs) to all the mobile users can be jointly designed based on the perfect knowledge of the downlink channels and transmit messages. To develop an efficient precoding matrix, we adopt the weighted minimum mean squared error criterion that can be generally applied to the sum-utility maximization of each receiver's information rate. In the SWIPT network-MIMO, a number of constraints arise including the power constraint at each BS, namely, the per-BS power constraints and the energy constraint at the energy harvesting users, which makes the problem challenging. A main contribution of the paper is to propose a simple bisection-based algorithm that finds a solution. The efficiency of the proposed algorithm is verified via computer simulation results.
Mobile edge computing (MEC) has emerged as an attractive solution by executing computation-intensive services at a powerful edge server instead of mobiles. Two types of data are necessary to this end. One is user-spec...
详细信息
Mobile edge computing (MEC) has emerged as an attractive solution by executing computation-intensive services at a powerful edge server instead of mobiles. Two types of data are necessary to this end. One is user-specific data acquired from mobiles, called computation offloading (CO). The other is service-specific data downloaded from a central cloud, called service caching (SC). It is noteworthy that CO and SC decisions are coupled when each user's service preference (SP) is personalized. Specifically, noting that the optimal SC is to cache services likely to be requested more frequently, the resultant SC tends to be biased to the SP of the user whose offloading rate is high. On the other hand, such an SC decision causes longer computing latency of users with a relatively low offloading rate, which ultimately limits a CO decision for agile MEC services. This work tackles this issue from a sum-utility maximization perspective under radio-resource and computation-latency constraints. The average computation latency is first derived in closed-form by modeling a computation as a stochastic process following a hyper-exponential distribution. Based on it, we first consider the case for homogeneous SP where CO and SC decisions are decoupled. Thus, SC can be deterministically controlled using the homogeneous SP, while CO decision is independently determined, lying between water-filling and channel-inversion allocations. Next, we design a joint CO-and-SC policy for heterogeneous SP. CO and SC decisions are iteratively optimized with the other fixed by leveraging the homogeneous SP's result. The optimal stopping rules are derived, guaranteeing the sum-utility enhancement. The proposed algorithm's effectiveness is verified by simulations that the proposed CO-and-SC design for heterogenous SP always outperforms that for homogeneous SP.
We study the distributed optimization of transmit strategies in a multiple-input, single-output (MISO) interference channel (IFC). Existing distributed algorithms rely on strictly synchronized update steps by the indi...
详细信息
We study the distributed optimization of transmit strategies in a multiple-input, single-output (MISO) interference channel (IFC). Existing distributed algorithms rely on strictly synchronized update steps by the individual users. They require a global synchronization mechanism and potentially suffer from the synchronization penalty caused by e. g., backhaul communication delays and fixed update sequences. We establish a general optimization framework that allows asynchronous update steps. The users perform their computations at arbitrary instants of time and do not wait for information that has been sent to them. Based on certain bounds on the amount of asynchronism that is present in the execution of the algorithm, we are able to characterize its convergence. As illustrated by our numerical results, the proposed algorithm is not excessively slowed down by neither communication delays, nor by specific update orders, and thus enables faster convergence to (local) optimal solution.
In this paper, we address the problem of joint scheduling and resource allocation in the downlink of an orthogonal frequency division multiple access (OFDMA)-based wireless network when the per-user SNR is known only ...
详细信息
ISBN:
(纸本)9781424493326
In this paper, we address the problem of joint scheduling and resource allocation in the downlink of an orthogonal frequency division multiple access (OFDMA)-based wireless network when the per-user SNR is known only in distribution. In particular, we consider sum-utility maximization over user schedules, powers, and code rates, subject to an instantaneous sum-power constraint. We consider both a "continuous" scenario where, during a time-slot, each OFDMA subchannel can be time-shared among multiple users and/or code rates, and a "discrete" scenario where no time-sharing is allowed. For the non-convex optimization problem arising in the continuous case, we propose an efficient exact solution. For the mixed-integer optimization problem arising in the discrete case, we propose a polynomial-complexity approximate solution and derive a bound on its optimality gap. We also provide a numerical study of goodput maximization for the SNR distribution that results from the use of pilot-aided MMSE channel estimation.
暂无评论