VARIABLE-RATE MULTIUSER DIVERSITY IN CORRELATED MIMO CHANNEL VIA VIRTUAL CHANNEL REPRESENTATION

This paper studies the multiuser diversity with constellation selection based on a virtual representation of realistic Multiple Input Multiple Output （MIMO） correlated channels. To realize multiuser diversity in slow fading channels, random beamforming is adopted. Random beamforming matrix exploiting virtual channel representation is constructed, which can match the channel matrix of the desired user better. Sirnultaneously, adaptive coded modulation is applied to each sub-channel of the selected user to improve the system performance further.

User selection strategies for multiuser MIMO systems with block diagonalization

Block diagonalization （BD） is an efficient precoding technique that eliminates inter-user interference in downlink multiple-input multiple-output （MIMO） systems. User selection strategies applied to multiuser MIMO systems with BD are investigated in this article. To enhance the capacity of multiuser MIMO systems, an equivalent capacity maximum （ECM） user selection strategy is proposed with low computational complexity. Considering both the factors of channel correlations and channel conditions, the proposed strategy can select a group of users to serve for maximizing the total throughput. Simulation results indicate that, for various channel conditions, proposed ECM strategy gains a better performance compared with traditional user selection strategies, and achieves a near optimal throughput as the exhaustive search.

Fairness based resource allocation for multiuser MISO-OFDMA systems with beamforming

Resource allocation problem in multiuser multiple input single output-orthogonal frequency division multiple access （MISO-OFDMA） systems with downlink beamforming for frequency selective fading channels is studied. The article aims at maximizing system throughput with the constraints of total power and bit error rate （BER） while supporting fairness among users. The downlink proportional fairness （PF） scheduling problem is reformulated as a maximization of the sum of logarithmic user data rate. From necessary conditions on optimality obtained analytically by Karush-Kuhn-Tucker （KKT） condition, an efficient user selection and resource allocation algorithm is proposed. The computer simulations reveal that the proposed algorithm achieves tradeoff between system throughput and fairness among users.

Joint beamforming and scheduling in the downlink of cognitive radio networks

Cognitive radio has been recently proposed as a promising technology to improve the spectrum utilization. In this paper, we consider a system where a licensed radio spectrum is shared by a primary network and a secondary network. Based on the subspace theory, a novel low-complexity algorithm for secondary user selection has been proposed. On the basis of the scheduling scheme, we jointly consider transmit beamforming, scheduling and power allocation, and subsequently present a complete set of solution for secondary network downlink. Simulation results has shown that our proposed scheme not only can limit the introduced interference at primary users within the tolerable range, but also can achieve high sum-rate throughput of secondary network, simultaneously. Furthermore, as is proved by simulation results, our scheme is very robust due to the fact that only a little tolerable performance drop is introduced when simple but nonoptimal equal power allocation is adopted.

Zero-forcing dirty paper coding aided physical-layer network coding for MIMO two-way relaying channels with multiple users

This article considers the two-way multiple-input multiple-output（MIMO） relaying channels with multiple users,in which multiple users are served simultaneously by the base station（BS） with the assistance of the relay.The transmission consists of only two phases,doubling the system throughout over traditional one-way half-duplex transmission.A zero-forcing dirty paper coding（ZFDPC） aided physical-layer network coding（PNC） scheme is proposed in this article and the achievable capacity of the ZFDPC aided PNC scheme is derived.Simulation results show that the proposed scheme outperforms the previous decode-and-forward（DF） and zero-forcing beamforming（ZFBF） aided PNC scheme due to more degrees of freedoms and the advantage of PNC.Moreover,we analyze the effect of the imperfect channel state information（CSI） from RS to users at BS side to show the robustness of the proposed ZFDPC aided PNC scheme.

Partial channel information feedback mechanism for FFR-based multi-channel systems

This article puts forward a partial channel state information （CSI） feedback scheme for fractional frequency reuse （FFR）-based orthogonal frequency division multiple access （OFDMA） systems. Efficient CSI feedback strategy plays an important role in opportunistic scheduling because base station （BS） can employ adaptive modulation and coding （AMC） technique to adaptively change transmission rates according to CSI feedback, and therefore the spectrum efficiency can be improved significantly. On the other hand, FFR is a simple but effective technique to improve the throughput of users at cell edge. To exploit opportunistic scheduling in FFR-based OFDMA systems, both users and spectrum are divided into multiple groups in this article, and specific feedback pattern is designed for each user group on each spectrum sub-band. Simulations results prove that the proposed algorithm can reduce the feedback load significantly, while maintain nearly the same performance as the system with full feedback.

Max-utility subcarrier allocation for heterogeneous services in wireless OFDM system

In future wireless network, one user will require multiple homogeneous or heterogeneous services simultaneously. Then, the scheduling algorithm is not only responsible for assigning a resource block to different users but also sharing the assigned resource block among multiple services for one user. Most of the traditional scheduling algorithms are designed to serve one service per user, and cannot be applied directly to this scenario because of the fairness criterion. This article focuses on adaptive resource allocation for multiple services per user at the downlink of orthogonal frequency division multiplexing （OFDM） based system. This article addresses this integrative resource scheduling problem based on utility function. First, the optimal algorithm for dynamic subcarrier allocation and share is deduced for homogeneous best-effort service system. Then the algorithm is extended to heterogeneous services system by classifying the delay sensitive service according to the head-of-line packet delay. The design goal is to maximize aggregate utility function to exploit multiuser diversity gain to the greatest extent even as guaranteeing quality of service （QoS） for delay sensitive service.