Showing papers by "David Gesbert published in 2006"

Space-Time Wireless Systems: From Array Processing to MIMO Communications

Abstract: One of the most promising technologies to resolve the bottlenecks in traffic capacity of future wireless networks is multiple-input multiple-output (MIMO) communications and space-time processing. MIMO wireless technology has progressed from the stage of fundamental research to commercially available products within a decade. With over sixty contributors from the field, this book provides an extensive overview of the state-of-the-art in MIMO communications, ranging from its roots in antenna array processing to advanced cellular communication systems. A balanced treatment of three key areas---information theory, algorithms and systems studies, and implementation issues---has been assembled by four editors with a broad range of academic and industry experience. This comprehensive reference will appeal to practitioners, researchers, and graduate students in wireless communications.

Optimal Power Allocation and Scheduling for Two-Cell Capacity Maximization

Abstract: We consider the problem of optimally allocating the base station transmit power in two neighboring cells for a TDMA wireless cellular system, to maximize the total system throughput under interference and noise impairments. Employing dynamic reuse of spectral resources, we impose a peak power constraint at each base station and allow for coordination between the base stations. By an analytical derivation we find that the optimal power allocation then has a remarkably simple nature: Depending on the noise and channel gains, transmit at full power only at base station 1 or base station 2, or both. Utilizing the optimal power allocation we study optimal link adaptation, and compare to adaptive transmission without power control. Results show that allowing for power control significantly increases the overall capacity for an average user pair, in addition to considerable power savings. Furthermore, we investigate power adaptation in combination with scheduling of users in a time slotted system. Specifically, the capacity-optimal single-cell scheduler [1] is generalized to the two-cell case. Thus, both power allocation and multiuser diversity are exploited to give substantial network capacity gains.

Multiuser Diversity - Multiplexing Tradeoff in MIMO Broadcast Channels with Limited Feedback

Abstract: We consider joint scheduling and beamforming in a broadcast channel with multiple antennas at the transmitter and a single antenna at the mobile receiver Perfect channel knowledge is assumed to be available at the receiver while the transmitter is provided with partial channel state information (CSIT) through a limited rate feedback channel Each user feeds back quantized information regarding the channel vector direction (from a codebook) and a quantized (scalar) channel quality indicator We identify the tradeoff between multiuser diversity and spatial multiplexing gain given a limited amount of feedback bits Scaling laws of the above parameters are derived in order to achieve a target rate performance Our results reveal useful design guidelines for the split of feedback bits for channel quantization and channel quality

Transmit Correlation-aided Scheduling in Multiuser MIMO Networks

Abstract: The problem of joint scheduling and beamforming for a multiuser multiple-input multiple-output (MIMO) network with partial channel state information at the transmitter (CSIT) is addressed here. Unlike most previous work that rely on full instantaneous CSIT and require inacceptable overhead feedback to the transmitter, we point out here that useful information relevant to the scheduler lies untapped in the long term statistical information of the user's channels. We show how statistical CSIT can be efficiently combined with partial instantaneous CSIT to derive a scheduling rule for the downlink of multiuser MIMO systems.

Precoding of space-time block coded signals for joint transmit-receive correlated MIMO channels

Abstract: A memoryless linear precoder is designed for orthogonal space-time block codes (OSTBC) for improved performance over block-fading flat correlated Rayleigh fading multiple-input multiple-output (MIMO) channels. Original features of the proposed technique include 1) the precoder can handle both transmit and receive correlation, and 2) the precoder handles any arbitrary joint correlation structure, including the so-called Kronecker (non-Kronecker) correlation models. The precoder is designed to minimize a symbol error-based metric as function of the joint slowly-varying channel correlation coefficients, which are supposed to be known to the transmitter. Several useful properties of the optimal precoder are given, evidencing the impact of receive correlation on transmitter optimization in certain situations. An iterative fast-converging numerical optimization algorithm is proposed. Monte Carlo simulations over fading channels are used to validate our claims.

Maximizing the Capacity of Large Wireless Networks: Optimal and Distributed Solutions

Abstract: We analyze the sum capacity of multicell wireless networks with full resource reuse and channel-driven opportunistic scheduling in each cell. We address the problem of finding the co-channel (throughout the network) user assignment that results in the optimal joint multicell capacity, under a resource-fair constraint and a standard power control strategy. This problem in principle requires processing the complete co-channel gain information, and thus, has so far been justly considered unpractical due to complexity and channel gain signaling overhead. However, we expose here the following key result: The multicell optimal user scheduling problem admits a remarkably simple and fully distributed solution for large networks. This result is proved analytically for an idealized network. From this constructive proof, we propose a practical algorithm that is shown to achieve near maximum capacity for realistic cases of simulated networks of even small sizes.

Low Complexity Scheduling and Beamforming for Multiuser MIMO Systems

Abstract: The problem of joint scheduling and beam-forming for a multiple antenna broadcast channel with partial channel state information at the transmitter (CSIT) is considered. We show how long-term statistical channel knowledge can be efficiently combined with instantaneous low-rate feedback for user selection and linear beamforming. A low complexity algorithm based on an estimate (bound) of the multiuser interference is proposed. Our scheme is shown to exhibit significant throughput gain over opportunistic techniques, approaching the sum rate of full CSIT for small angle spreads.

Transmit correlation-aided opportunistic beamforming and scheduling

Abstract: The problem of multiuser scheduling and beamforming with partial channel state information at the transmitter (CSIT) is considered here in the particular context of opportunistic beamforming. We consider a random multiuser beamforming scheme and show how long-term statistical information of users' channels can be efficiently combined with short-term SINR feedback to increase system performance substantially over a conventional opportunistic beamforming scheme. We propose a channel estimation method to be used by the transmitter which exploits the second-order channel statistics, the fading statistics and the information contained in the instantaneous SINR feedback of random opportunistic beamforming. This coarse (low feedback-based) channel estimate is shown to be particularly valuable for the purpose of user selection, as well as for the precoding matrix design.

Cooperative Spatial Multiplexing with Hybrid Channel Knowledge

Abstract: We explore the concept of cooperative spatial multiplexing for use in MIMO multicell networks. One key application of this is the transmission of possibly correlated symbol streams jointly by several multiple-antenna access points toward multiple single antenna user terminals located in neighboring cells. To augment the realism of this setting, we consider different levels of channel state information at the transmitter (CSIT). In one case, we further introduce a constraint on hybrid channel state information (HCSI) in which any given transmitter knows its own CSI perfectly while it only has statistical information about other transmitters' channels. This yield a game situation in which each cooperating transmitter makes a guess about the behavior of the other transmitter. We show different transmission strategies under this setting and compare them with fully cooperative (full CSI) and non cooperative schemes. Our results show a substantial cooperation gain despite the lack of instantaneous information

Precoding for Distributed Space-Time Codes in Cooperative Diversity-Based Downlink

Abstract: In this paper, we investigate the cooperative diversity concept for use in MIMO multi-cell networks. We show that, in such networks, cooperative diversity processing must be optimized to account for the variability of channel conditions across the cooperative devices. This can be done via distributed precoding and, in mobile networks, it is based realistically on channel statistics. The cooperative MIMO correlation matrix admits a special structure which is used to optimize the precoder. We investigate algorithms for exact error-rate and low-complexity approximated optimization. Gains are evaluated in multi-cell scenarios with collaborating base stations.

A simple greedy scheme for multicell capacity maximization

Abstract: We study joint optimization of transmit power and scheduling in a multicell wireless network. Despite promising significant gains, this problem is known to be NP-hard and thus difficult to tackle in practice. However, we show that this problem lends itself to analysis for large wireless networks which allows simpler modeling of inter-cell interference. We introduce a low complexity greedy algorithm that is efficient for large networks. As the number of users per cell increases, the solution converges to all cells being active and employing maximum SINR scheduling, which can be implemented in a distributed manner. Using simulation parameters equivalent to those used in realistic wireless networks we show that the scheme, though simple, exhibits substantial gains over existing resource allocation schemes.

Receiver-Enhanced Cooperative Spatial Multiplexing with Hybrid Channel Knowledge

Abstract: This paper explores the idea of cooperative spatial multiplexing for use in MIMO multicell networks. We imagine applying this cooperation for several multiple antenna access-points to jointly transmit streams towards multiple single-antenna user terminals in neighbouring cells. We make the setting more realistic by introducing a constraint on the hybrid channel state information (HCSI), assuming that each transmitter has full CSI for its own channel, but only statistical information about other transmitters’ channels. Each cooperating transmitter then makes guesses about the behaviour of the other transmitters, using the statistical CSI. We show two of several possible transmission strategies under this setting, and include simple optimization at the receiver to improve performance. Comparisons are made with fully cooperative (full CSI) and non-cooperative schemes. Simulation results show a substantial cooperation gain despite the lack of instantaneous information.

QRP07-1: Throughput Guarantees for Wireless Networks with Opportunistic Scheduling

Abstract: In this paper we analyze achievable throughput guarantees in wireless time-division multiplexing (TDM) networks. Approximations of the throughput guarantee violation probability (TGVP) for users communicating in time-slotted systems are obtained for any scheduling algorithm with a given mean and variance of the number of bits transmitted in a time- slot and a distribution for the number of time-slots allocated to a user within a time-window. We investigate the corresponding TGVPs for three scheduling algorithms, namely (i) Round Robin Scheduling, (ii) Maximum Carrier-to-Noise Ratio Scheduling, and (iii) Opportunistic Round Robin Scheduling, when the users' channels are independently and identically distributed.

Transmitting over Ill-conditioned MIMO channels: from spatial to constellation multiplexing

Abstract: This chapter addresses the problem of multiplexing multiple data streams in a multiple input multiple output (MIMO) system in the presence of channel matrix ill-conditioning brought by fading correlation and/or a Rice component. Conventional multiplexing schemes based on the separation of the stream’s spatial signatures (commonly referred to as spatial multiplexing—SM, V-BLAST architecture) rely on the linear independence between the channel responses corresponding to each transmit antenna. Consequently, such schemes suffer considerably from effects bringing ill conditioning in the MIMO channel matrix, such as fading correlation and Rice components. In an attempt to robustify SM schemes for deployment in a wide range or propagation terrains, we investigate the use of so-called constellation multiplexing (CM) whereby distinct M-QAM streams are superposed to form a higher-order QAM constellation with rate equivalent to the sum of rates of all original streams. CM schemes do not rely on MIMO channel full rankness to function properly. We thus seek an approach that allows bridging SM and CM schemes. We show that this can be realized in the form of a linear diagonal precoder. This in turn yields an adaptive rate-preserving MIMO multiplexing algorithm that can operate smoothly at any degree of correlation or Ricean factor. Conventional SM and CM schemes are shown to be particular cases of the presented family of schemes.

Maximizing the Capacity of Wireless Networks using Multi-Cell Access Schemes

Abstract: We propose a novel method for improving wireless network capacity by resorting to a so-called "multi-cell access" (MCA) scheme. An MCA scheme is reminiscent of the conventional multiple access problem in multi-user networks. However, in an MCA scheme cells (rather than users) compete for access. Furthermore, an example of such a scheme is introduced whereby a cell obtains a credit that is a function of the channel gain of its scheduled user, and it is allowed to transmit with a probability that is computed based on the credit value. The network capacity under this scheme is analyzed and we propose an optimization method in the case where the probability distribution for access is binary.

Throughput guarantees for opportunistic scheduling algorithms: A comparative study

Abstract: In this paper we analyze achievable throughput guarantees for different opportunistic scheduling algorithms operating in wireless time-division multiplexing networks. We consider a scenario where the average carrier-to-noise ratios of the users' channels are different from user to user. An approximation of the throughput guarantee violation probability for users communicating in time-slotted systems are obtained for any scheduling algorithm with a given mean and variance of the number of bits transmitted in a time-slot, and a given distribution for the number of time-slots allocated to a user within a time window. We investigate the corresponding throughput guarantees for three different scheduling algorithms: (i) Maximum Carrier- to-Noise Ratio Scheduling, (ii) Normalized Carrier-to-Noise Ratio Scheduling, and (iii) Opportunistic Round Robin Scheduling.

Probabilistic access functions for multi-cell wireless schemes

Abstract: In recently introduced “multi-cell access” schemes, cells (rather than users) compete for the spectral resource. In a previous paper [1], a framework for such a scheme was proposed, using only local channel information. In the framework each cell competes for access through a credit that is a function of the signal to noise ratio of its scheduled user. Access is then given to a cell with a probability dependent on the access function. In [1] an ad-hoc choice of function was formulated. In this work we investigate which access function actually optimizes the system capacity, utilizing a numerical optimization procedure. We obtain a surprsingly simple solution which also corroborates previous results. For a realistic path loss model we find that our multicell distributed access scheme gives a 19% gain compared to having all cells on, and more than a 50% increase in system capacity compared to keeping a traditional static spectral reuse scheme.

A Simple Greedy Scheme for

Abstract: o We study joint optimization of transmit power and scheduling in a multicell wireless network. Despite promising signicant gains, this problem is known to be NP-hard and thus difcult to tackle in practice. However, we show that this problem lends itself to analysis for large wireless networks which allows simpler modeling of inter-cell interference. We introduce a low complexity greedy algorithm that is efcient for large networks. As the number of users per cell increases, the solution converges to all cells being active and employing maximum SINR scheduling, which can be implemented in a distributed manner. Using simulation parameters equivalent to those used in realistic wireless networks we show that the scheme, though simple, exhibits substantial gains over existing resource allocation schemes.