The joint power allocation (PA) issue is studied in multi-user three-cell systems under the degree-of-freedom (DoF) based transmission protocol. This protocol makes all the interferences received at each user orthogonal to the useful signal at the same user by Jafar's topological interference management through index coding, which is proved to offer full DoF. Under this protocol, we formulate the joint power allocations problem based on the objective of energy efficiency under the required quality-of-service constraint. Due to the highly complicated Lagrangian equation, the properties of Lambert function are widely exploited to solve the problem using a closed-form expression. It is discovered that the relationship among the optimal power coefficients are completely different from that of the well-known water-filling method. Simulations demonstrate the energy efficiency of the designed scheme.

In this letter, we propose two robust and distributed game-based algorithms, which are the modifications of two algorithms proposed in [1], to solve the joint base station selection and resource allocation problem with imperfect information in heterogeneous cellular networks (HCNs). In particular, we repeatedly sample the received payoffs in the exploitation stage of each algorithm to guarantee the convergence when the payoffs of some users (UEs) in [1] cannot accurately be acquired for some reasons. Then, we derive the rational sampling number and prove the convergence of the modified algorithms. Finally, simulation results demonstrate that two modified algorithms achieve good convergence performances and robustness in the incomplete information scheme.

Considering worse-case channel uncertainties, we investigate the robust energy efficient (EE) beamforming design problem in a K-user multiple-input-single-output (MISO) interference channel. Our objective is to maximize the worse-case sum EE under individual transmit power constraints. In general, this fractional programming problem is NP-hard for the optimal solution. To obtain an insight into the problem, we first transform the original problem into its lower bound problem with max-min and fractional form by exploiting the relationship between the user rate and the minimum mean square error (MMSE) and using the min-max inequality. To make it tractable, we transform the problem of fractional form into a subtractive form by using the Dinkelbach transformation, and then propose an iterative algorithm using Lagrangian duality, which leads to the locally optimal solution. Simulation results demonstrate that our proposed robust EE beamforming scheme outperforms the conventional algorithm.

In this letter, we focus on the subcarrier allocation problem for device-to-device (D2D) communication in cellular networks to improve the cellular energy efficiency (EE). Our goal is to maximize the weighted cellular EE and its solution is obtained by using a game-theoretic learning approach. Specifically, we propose a lower bound instead of the original optimization objective on the basis of the proven property that the gap goes to zero as the number of transmitting antennas increases. Moreover, we prove that an exact potential game applies to the subcarrier allocation problem and it exists the best Nash equilibrium (NE) which is the optimal solution to optimize the lower bound. To find the best NE point, a distributed learning algorithm is proposed and then is proved that it can converge to the best NE. Finally, numerical results verify the effectiveness of the proposed scheme.

This paper presents an overview of the advance of the China millimeter-wave multiple gigabit (CMMG) wireless local area network (WLAN) system which operates in the 45 GHz frequency band. The CMMG WLAN system adopts the multiple antennas technologies to support data rate up to 15Gbps. During the progress of CMMG WLAN standardization, some new key technologies were introduced to adapt the millimeter-wave characteristic, including the usage of the zero correlation zone (ZCZ) sequence, a novel lower density parity check code (LDPC)-based packet encoding, and multiple input multiple output (MIMO) single carrier transmission. Extensive numerical results and system prototype test are also given to validate the performance of the technologies adopted by CMMG WLAN system.

In this paper, we address the issue of interference alignment (IA) in a two-cell network and consider both inter-cell and intra-cell interferences. For cell one, a linear processing scheme is proposed to align the inter-cell interference to the same signal dimension space of intra-cell interference. For cell two, we propose a distributed interference alignment scheme to manage the interference from the nearby cell. We assume that the relay works in an amplify-and-forward (AF) mode with a half-duplex and MIMO relaying. We show that the composite desired and interfering signals aggregated over two time slots can be aligned such that the interfering signal is eliminated completely by applying a linear filter at the receiver. The precoding matrix of the relay is optimized jointly with the precoding matrix of the base station (BS). The number of data streams is optimized jointly for every user terminal (UT). The degree of freedom (DoF) performance of the proposed scheme as well as the conventional cooperation scheme are derived for multiple antennas at both base stations, relay station and user terminals. Simulation results show that the proposed alignment scheme can achieve a better DoF performance.

This paper considers a massive multiple-input-multiple-output (MIMO) relaying system with multi-pair single-antenna users. The relay node adopts maximum-ratio combining/maximum-ratio transmission (MRC/MRT) stratagem for reception/transmission. We analyze the spectral efficiency (SE) and power scaling laws with respect to the number of relay antennas and other system parameters. First, by using the law of large numbers, we derive the closed-form expression of the SE, based on which, it is shown that the SE per user increases with the number of relay antennas but decreases with the number of user pairs, both logarithmically. It is further discovered that the transmit power at the source users and the relay can be continuously reduced as the number of relay antennas becomes large while the SE can maintains a constant value, which also means that the energy efficiency gain can be obtained simultaneously. Moreover, it is proved that the number of served user pairs can grow proportionally over the number of relay antennas with arbitrary SE requirement and no extra power cost. All the analytical results are verified through the numerical simulations.

In this paper, the joint optimization issue of the cooperative precoder design is investigated for the transmission from the cooperative multi-point system to one mobile terminal. Based on the mean squared error minimization criterion, the problem is established for the cooperative precoder design. Unfortunately, this problem cannot be solved due to the block diagonal structure of the whole precoding matrix resulting from the fact that there is no data exchange among multiple base stations. In order to tackle this difficulty, the original problem is converted into an equivalent problem by stacking all of the nonzero entries in the block diagonal matrix into a long column vector. With the equivalent problem, the optimum solution is obtained in a closed-form expression by using the Lagrangian multiplier method. Numerical simulations illustrate the effectiveness of the proposed scheme in terms of bit error rate and spectral efficiency.