Runhua Chen

Broadband wireless access with WiMax/802.16: current performance benchmarks and future potential

The IEEE 802.16 family of standards and its associated industry consortium, WiMax, promise to deliver high data rates over large areas to a large number of users in the near future. This exciting addition to current broadband options such as DSL, cable, and WiFi promises to rapidly provide broadband access to locations in the worlds rural and developing areas where broadband is currently unavailable, as well as competing for urban market share. WiMaxs competitiveness in the marketplace largely depends on the actual data rates and ranges that are achieved, but this has been difficult to judge due to the large number of possible options and competing marketing claims. This article first provides a tutorial overview of 802.16. Then, based on extensive recent studies, this article presents the realistic attainable throughput and performance of expected WiMax compatible systems based on the 802.16d standard approved in June 2004 (now named 802.16-2004). We also suggest future enhancements to the standard that could at least quadruple the achievable data rate, while also increasing the robustness and coverage, with only moderate complexity increases

Networked MIMO with clustered linear precoding

A clustered base transceiver station (BTS) coordination strategy is proposed for a large cellular MIMO network, which includes full intra-cluster coordination-to enhance the sum rate-and limited inter-cluster coordination-to reduce interference for the cluster edge users. Multi-cell block diagonalization is used to coordinate the transmissions across multiple BTSs in the same cluster. To satisfy per-BTS power constraints, three combined precoder and power allocation algorithms are proposed with different performance and complexity tradeoffs. For inter-cluster coordination, the coordination area is chosen to balance fairness for edge users and the achievable sum rate. It is shown that a small cluster size (about 7 cells) is sufficient to obtain most of the sum rate benefits from clustered coordination while greatly relieving channel feedback requirement. Simulations show that the proposed coordination strategy efficiently reduces interference and provides a considerable sum rate gain for cellular MIMO networks.

Low complexity user selection algorithms for multiuser MIMO systems with block diagonalization

Block diagonalization (BD) is a preceding technique that eliminates inter-user interference in downlink multiuser multiple-input multiple-output (MIMO) systems. With the assumptions that all users have the same number of receive antennas and utilize all receive antennas when scheduled for transmission, the number of simultaneously supportable users with BD is limited by the ratio of the number of basestation transmit antennas to the number of user receive antennas. In a downlink MIMO system with a large number of users, the basestation may select a subset of users to serve in order to maximize the total throughput The brute-force search for the optimal user set, however, is computationally prohibitive. We propose two low-complexity suboptimal user selection algorithms for multiuser MIMO systems with BD. Both algorithms aim to select a subset of users such that the total throughput is nearly maximized. The first user selection algorithm greedily maximizes the total throughput, whereas the criterion of the second algorithm is based on the channel energy. We show that both algorithms have linear complexity in the total number of users and achieve around 95% of the total throughput of the complete search method in simulations

Transmit Selection Diversity for Unitary Precoded Multiuser Spatial Multiplexing Systems With Linear Receivers

Multiuser spatial multiplexing is a downlink transmission technique that uses linear transmit precoding to multiplex multiple users and precancel interuser interference. In such a system, the spatial degrees of freedom are used for interference mitigation and generally come at the expense of diversity gain. This paper proposes two precoding methods that use extra transmit antennas, beyond the minimum required, to provide additional degrees of diversity. The approach taken is to solve for a unitary transmit precoder, under a zero interuser interference constraint, that minimizes an upper bound on the symbol error rate (SER) for each user. Solutions where all transmit antennas are employed, as well as subsets of antennas (to reduce analog components), are described. Numerical results confirm a dramatic improvement in terms of SER and mutual information over single-user multiple-input multiple-output (MIMO) methods and static allocation methods. For example, the proposed techniques achieve a signal-to-noise ratio (SNR) improvement of 6-10 dB at an uncoded SER of 10-3, with only one extra transmit antenna

Low Complexity User Selection Algorithms for Multiuser MIMO Systems with Block Diagonalization

Block diagonalization (BD) is a precoding technique that eliminates interuser interference in downlink multiuser multiple-input multiple-output (MIMO) systems. With the assumptions that all users have the same number of receive antennas and utilize all receive antennas when scheduled for transmission, the number of simultaneously supportable users with BD is limited by the ratio of the number of base station transmit antennas to the number of user receive antennas. In a downlink MIMO system with a large number of users, the base station may select a subset of users to serve in order to maximize the total throughput. The brute-force search for the optimal user set, however, is computationally prohibitive. We propose two low-complexity suboptimal user selection algorithms for multiuser MIMO systems with BD. Both algorithms aim to select a subset of users such that the total throughput is nearly maximized. The first user selection algorithm greedily maximizes the total throughput, whereas the criterion of the second algorithm is based on the channel energy. We show that both algorithms have linear complexity in the total number of users and achieve around 95% of the total throughput of the complete search method in simulations

Multimode Transmission for Multiuser MIMO Systems With Block Diagonalization

A low-complexity multimode transmission technique for downlink multiuser multiple-input-multiple-output (MIMO) systems with block diagonalization (BD) is proposed. The proposed technique adaptively configures the number of data streams for each user by adjusting its number of active receive antenna and switching between single-stream beamforming and multistream spatial multiplexing, as a means to exploit the multimode switching diversity. We consider a highly loaded system where there are a large number of users, hence a subset of users need to be selected. Joint user and antenna selection has been proposed as a multiuser multimode switching technique, where the optimal subset of receive antennas and users are chosen to maximize the sum throughput. The brute-force search, however, is prohibitively complicated. In this paper, two low-complexity near-optimal user/antenna selection algorithms are developed. The first algorithm aims at maximizing a capacity lower bound, derived in terms of the sum Frobenius norm of the channel, while the second algorithm greedily maximizes the sum capacity. We analytically evaluate the complexity of the proposed algorithms and show that it is orders of magnitude lower than that of the exhaustive search. Simulation results demonstrate that the proposed algorithms achieve up to 98% of the sum throughput of the exhaustive search, for most system configurations, while the complexity is substantially reduced.

Uplink Power Control in Multi-Cell Spatial Multiplexing Wireless Systems

This paper proposes a power control strategy for the uplink of cellular MIMO spatial multiplexing systems, with a linear MMSE receiver applied at the base station and a single active user per time instant. A fixed per-stream SINR target is employed that allows guaranteed QoS for delay-sensitive applications. A straightforward application of single antenna power control is not possible in the MIMO context due to coordination between receive antennas and nonlinear dependence between interference and eigenspaces of the channel matrices. Two schemes are proposed to solve the problem. The first equally allocates power to all transmit antennas. Deriving an SINR lower bound based on an eigenvalue approximation of the composite interference, allows application of the conventional single antenna power control framework to solve this problem. To improve the feasibility performance, a second scheme is proposed that adaptively allocates power on the transmit antennas, where an iterative algorithm based on game theory is used to sequentially update each users power distribution. The optimal solution with full channel knowledge, and a practical near-optimal solution requiring only partial channel knowledge, are both derived. Numerical results show that power control, compared to supposedly optimal waterfilling strategies, actually achieves higher throughput at the low SINRs typical in cellular systems, with significantly lower overhead and complexity. Due to its better exploitation of spatial diversity and reduced transmit power (and hence reduced interference), adaptive power allocation increases the achievable SINR by an order of magnitude over equal power allocation, resulting in far better coverage.

Coordinated Multi-cell MIMO Systems with Cellular Block Diagonalization

A clustered base transceiver station (BTS) coordination strategy is proposed to realize the gains of multiuser MIMO communication in interference-limited cellular systems. In the proposed coordination strategy, users are divided into two groups: a full intra-cluster coordination group to enhance the sum rate gain and a limited inter-cluster coordination group to reduce interference for the cluster edge users. Multi-cell block diagonalization is used to coordinate the transmissions across multiple BTSs in the same cluster. Because of the per-BTS power constraints, three combined precoder and power allocation algorithms are considered in this paper with different performance complexity tradeoffs. Simulations show that the proposed coordination strategy improves the sum rate over conventional systems and reduces the impact of interference for the cluster-edge users.

Efficient Transmit Antenna Selection for Multiuser MIMO Systems with Block Diagonalization

Block diagonalization is a preceding technique for multiuser MIMO systems that pre-cancels inter-user interference at the transmitter side. When there are a large number of base station antennas but a limited number of RF amplifiers, the system performance can be significantly improved by switching a subset of antennas to the RF chains and exploiting antenna selection diversity. The optimal antenna subset can be obtained by exhaustively searching over all possible antenna combinations. This brute-force search, however, is prohibitively complicated and impractical. To reduce the complexity, in this paper we propose several low-complexity suboptimal transmit selection algorithms that minimize a symbol error rate (SER) upper bound or maximize a capacity lower bound. Simulation results show that our proposed algorithms perform very close to the optimal exhaustive search, while the complexity is much lower.

Transmit selection diversity for multiuser spatial multiplexing systems

Multiuser spatial multiplexing uses precoding to support multiple users in multi-antenna wireless channels. In this paper, two transmit diversity techniques are proposed that use extra transmit antennas to obtain additional diversity. In one solution, an eigenmode selection technique is proposed to achieve higher diversity gain by optimally matching the data streams to eigenmodes with superior channel conditions. In the other solution, a multiuser antenna selection algorithm is proposed that achieves good performance with fewer RF chains and lower system cost. Selection criteria for single-user spatial multiplexing are extended to the multiuser scenario in the context of unitary downlink precoding, and a novel selection algorithm that is near optimal in terms of symbol error rate (SER) is proposed. Simulation results show dramatic SNR reductions of 6-10 dB at an uncoded SER of 10/sup -3/ with only one extra antenna.