• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.18 no.1
• /
• pp.59-69
• /
• 2018

In this paper, we present a robust beamforming design to tackle the weighted sum-rate maximization (WSRM) problem in a multicell multiple-input multiple-output (MIMO) - non-orthogonal multipleaccess (NOMA) downlink system for 5G wireless communications. This work consider the imperfectchannel state information (CSI) at the base station (BS) by adding uncertainties to channel estimation matrices as the worst-case model i.e., singular value uncertainty model (SVUM). With this observation, the WSRM problem is formulated subject to the transmit power constraints at the BS. The objective problem is known as on-deterministic polynomial (NP) problem which is difficult to solve. We propose an robust beam forming design which establishes on majorization minimization (MM) technique to find the optimal transmit beam forming matrix, as well as efficiently solve the objective problem. In addition, we also propose a joint user clustering and power allocation (JUCPA) algorithm in which the best user pair is selected as a cluster to attain a higher sum-rate. Extensive numerical results are provided to show that the proposed robust beamforming design together with the proposed JUCPA algorithm significantly increases the performance in term of sum-rate as compared with the existing NOMA schemes and the conventional orthogonal multiple access (OMA) scheme.

• Journal of Advanced Navigation Technology
• /
• v.16 no.6
• /
• pp.988-996
• /
• 2012

Assuming perfect channel state information (CSI), the conventional interference alignment (IA) algorithm in the uplink cellular system suppresses inter-cell interference (ICI) by aligning ICI to a randomly selected reference vector. However, IA in practice relies on limited feedback between base stations and users, resulting in residual ICI. In this paper, we propose the optimization of the reference vector that minimizes the upper-bound of residual ICI power. Secondly, the iterative IA that designs the direction of transmit and receive filter is proposed to minimize the residual ICI as well as maximize the desired signals. Moreover, we propose the user scheduling method combined with proposed IA schemes which provides the multiuser diversity gain in multi-cell environments. Finally, the performance gain of the proposed IA algorithms compared with the existing IA are analyzed and demonstrated by simulation results.

• Journal of Broadcast Engineering
• /
• v.15 no.2
• /
• pp.173-181
• /
• 2010

In this paper, we propose a new resource allocation scheme for an OFDMA relay network with multicells. In the proposed scheme, by sharing the channel state information (CSI) between base stations, resources are allocated to users and relays to maximize the overall sum of the achievable rate under fairness constraints. In order to reduce the computational complexity, a resource allocation scheme is proposed by separating subcarrier allocation and power allocation into two parts. First of all, by considering inter-cell interference (ICI), a subcarrier is allocated to a user-relay pair, and power is allocated relays. Simulation results show that the proposed scheme achieves higher spectral efficiency per subcarrier than the static scheme and reduces the outage probability compared to the static and greedy schemes.