Showing papers on "Dirty paper coding published in 2005"

On the capacity of MIMO broadcast channels with partial side information

Abstract: In multiple-antenna broadcast channels, unlike point-to-point multiple-antenna channels, the multiuser capacity depends heavily on whether the transmitter knows the channel coefficients to each user. For instance, in a Gaussian broadcast channel with M transmit antennas and n single-antenna users, the sum rate capacity scales like Mloglogn for large n if perfect channel state information (CSI) is available at the transmitter, yet only logarithmically with M if it is not. In systems with large n, obtaining full CSI from all users may not be feasible. Since lack of CSI does not lead to multiuser gains, it is therefore of interest to investigate transmission schemes that employ only partial CSI. We propose a scheme that constructs M random beams and that transmits information to the users with the highest signal-to-noise-plus-interference ratios (SINRs), which can be made available to the transmitter with very little feedback. For fixed M and n increasing, the throughput of our scheme scales as MloglognN, where N is the number of receive antennas of each user. This is precisely the same scaling obtained with perfect CSI using dirty paper coding. We furthermore show that a linear increase in throughput with M can be obtained provided that M does not not grow faster than logn. We also study the fairness of our scheduling in a heterogeneous network and show that, when M is large enough, the system becomes interference dominated and the probability of transmitting to any user converges to 1/n, irrespective of its path loss. In fact, using M=/spl alpha/logn transmit antennas emerges as a desirable operating point, both in terms of providing linear scaling of the throughput with M as well as in guaranteeing fairness.

Sum power iterative water-filling for multi-antenna Gaussian broadcast channels

Abstract: In this correspondence, we consider the problem of maximizing sum rate of a multiple-antenna Gaussian broadcast channel (BC). It was recently found that dirty-paper coding is capacity achieving for this channel. In order to achieve capacity, the optimal transmission policy (i.e., the optimal transmit covariance structure) given the channel conditions and power constraint must be found. However, obtaining the optimal transmission policy when employing dirty-paper coding is a computationally complex nonconvex problem. We use duality to transform this problem into a well-structured convex multiple-access channel (MAC) problem. We exploit the structure of this problem and derive simple and fast iterative algorithms that provide the optimum transmission policies for the MAC, which can easily be mapped to the optimal BC policies.

Capacity and lattice strategies for canceling known interference

Abstract: We consider the generalized dirty-paper channel Y=X+S+N,E{X/sup 2/}/spl les/P/sub X/, where N is not necessarily Gaussian, and the interference S is known causally or noncausally to the transmitter. We derive worst case capacity formulas and strategies for "strong" or arbitrarily varying interference. In the causal side information (SI) case, we develop a capacity formula based on minimum noise entropy strategies. We then show that strategies associated with entropy-constrained quantizers provide lower and upper bounds on the capacity. At high signal-to-noise ratio (SNR) conditions, i.e., if N is weak relative to the power constraint P/sub X/, these bounds coincide, the optimum strategies take the form of scalar lattice quantizers, and the capacity loss due to not having S at the receiver is shown to be exactly the "shaping gain" 1/2log(2/spl pi/e/12)/spl ap/ 0.254 bit. We extend the schemes to obtain achievable rates at any SNR and to noncausal SI, by incorporating minimum mean-squared error (MMSE) scaling, and by using k-dimensional lattices. For Gaussian N, the capacity loss of this scheme is upper-bounded by 1/2log2/spl pi/eG(/spl Lambda/), where G(/spl Lambda/) is the normalized second moment of the lattice. With a proper choice of lattice, the loss goes to zero as the dimension k goes to infinity, in agreement with the results of Costa. These results provide an information-theoretic framework for the study of common communication problems such as precoding for intersymbol interference (ISI) channels and broadcast channels.

Dirty-paper coding versus TDMA for MIMO Broadcast channels

Abstract: We compare the capacity of dirty-paper coding (DPC) to that of time-division multiple access (TDMA) for a multiple-antenna (multiple-input multiple-output (MIMO)) Gaussian broadcast channel (BC) We find that the sum-rate capacity (achievable using DPC) of the multiple-antenna BC is at most min(M,K) times the largest single-user capacity (ie, the TDMA sum-rate) in the system, where M is the number of transmit antennas and K is the number of receivers This result is independent of the number of receive antennas and the channel gain matrix, and is valid at all signal-to-noise ratios (SNRs) We investigate the tightness of this bound in a time-varying channel (assuming perfect channel knowledge at receivers and transmitters) where the channel experiences uncorrelated Rayleigh fading and in some situations we find that the dirty paper gain is upper-bounded by the ratio of transmit-to-receive antennas We also show that min(M,K) upper-bounds the sum-rate gain of successive decoding over TDMA for the uplink channel, where M is the number of receive antennas at the base station and K is the number of transmitters

A close-to-capacity dirty paper coding scheme

Abstract: The "writing on dirty paper"-channel model offers an information-theoretic framework for precoding techniques for canceling arbitrary interference known at the transmitter. It indicates that lossless precoding is theoretically possible at any signal-to-noise ratio (SNR), and thus dirty-paper coding may serve as a basic building block in both single-user and multiuser communication systems. We design an end-to-end coding realization of a system materializing a significant portion of the promised gains. We employ multidimensional quantization based on trellis shaping at the transmitter. Coset decoding is implemented at the receiver using "virtual bits." Combined with iterative decoding of capacity-approaching codes we achieve an improvement of 2dB over the best scalar quantization scheme. Code design is done using the EXIT chart technique.

Optimality of zero-forcing beamforming with multiuser diversity

Abstract: In MIMO downlink channels, the capacity is achieved by dirty paper coding (DPQ). However, DPC is difficult to implement in practical systems. This work investigates if, for a large number of users, simpler schemes can achieve the same performance. Specifically, we show that a zero-forcing beamforming (ZFBF) strategy, while generally suboptimal, can achieve the same asymptotic sum-rate capacity as that of DPC, as the number of users goes to infinity. In proving this asymptotic result, we propose an algorithm for determining which users should be active in ZFBF transmission. These users are semi-orthogonal to one another, and when fairness among users is required, can be grouped for simultaneous transmissions to enhance the throughput of fair schedulers. We provide numerical results to confirm the optimality of ZFBF and to compare its performance with that of various MIMO downlink strategies.

Informed watermarking by means of orthogonal and quasi-orthogonal dirty paper coding

Abstract: A new dirty paper coding technique that is robust against the gain attack is presented. Such a robustness is obtained by adopting a set of (orthogonal) equi-energetic codewords and a correlation-based decoder. Due to the simple structure of orthogonal codes, we developed a simple yet powerful technique to embed the hidden message within the host signal. The proposed technique is an optimal one, in that the embedding distortion is minimized for a given robustness level, where robustness is measured through the maximum pairwise error probability in the presence of an additive Gaussian attack of given strength. The performance of the dirty coding algorithm is further improved by replacing orthogonal with quasi- orthogonal codes, namely, Gold sequences, and by concatenating them with an outer turbo code. To this aim, the inner decoder is modified to produce a soft estimate of the embedded message. Performance analysis is carried out by means of extensive simulations proving the validity of the novel watermarking scheme.

Carbon Copying Onto Dirty Paper

Abstract: A generalization of the problem of writing on dirty paper is considered in which one transmitter sends a common message to multiple receivers. Each receiver experiences on its link an additive interference (in addition to the additive noise), which is known noncausally to the transmitter but not to any of the receivers. Applications range from wireless multi-antenna multicasting to robust dirty paper coding. We develop results for memoryless channels in Gaussian and binary special cases. In most cases, we observe that the availability of side information at the transmitter increases capacity relative to systems without such side information, and that the lack of side information at the receivers decreases capacity relative to systems with such side information. For the noiseless binary case, we establish the capacity when there are two receivers. When there are many receivers, we show that the transmitter side information provides a vanishingly small benefit. When the interference is large and independent across the users, we show that time sharing is optimal. For the Gaussian case we present a coding scheme and establish its optimality in the high signal-to-interference-plus-noise limit when there are two receivers. When the interference is large and independent across users we show that time-sharing is again optimal. Connections to the problem of robust dirty paper coding are also discussed.

Limited feedback signaling for MIMO broadcast channels

Abstract: Recently, a number of techniques have been introduced to exploit multiuser diversity of a wireless multiple input multiple output (MIMO) broadcast channel (BC) that consists of a base station (BS) with t transmit antennas and K mobile stations (MS) with multiple antennas. However, prior works have ignored the rate overhead associated with feedback of MIMO BC channel state information (CSI), which is roughly K times larger than single-user MIMO CSI (i.e., it is O(tr) where r=/spl Sigma//sub k=1//sup K/r/sub k/ and r/sub k/ is the number of antennas at the kth MS). Considering the amount of feedback signaling, quantization is a necessity for effective feedback transmission as a form of partial CSI. In this paper, we propose the greedy multi-channel selection diversity (greedy MCSD) scheme bases on block MMSE QR decomposition with dirty paper coding (block MMSE-DP), where partial CSI is almost sufficient. The sum-rate performance of our novel scheme approaches extremely close to the sum capacity of MIMO BC as the number of users increases, whereas the feedback overhead is reduced by a factor of 2t/sup 3//L(t/sup 2/-t), in which L is the number of active channel vectors. Simulation results validate the expectation from the analysis.

Mimo air interface utilizing dirty paper coding

Abstract: A transceiver comprising a data processing module, a security processing module, a medium access control (MAC) module, a dirty-paper-coding (DPC) module, and a smart antenna processor The data processing module provides user data streams to the MAC module and channel state information to the smart antenna processor The security processing module generates security data and provides the security data to the MAC module The security module also provides security policy data to the smart antenna processor The MAC module determines data transmission rates for the user data streams and the security data In addition, the MAC module allocates the data streams and security data to transmission channels for transmission The DPC module encodes the security data onto the user data streams The smart antenna processor generates pre-coding coefficients used by the DPC module and transmits the security encoded data streams

Adaptive subcarrier and power allocation for multiuser MIMO-OFDM systems

Abstract: This paper addresses the optimal resource allocation problem for multiuser MIMO-OFDM systems. We apply an optimization algorithm to obtain a joint subcarrier and power allocation scheme based on orthogonal frequency division multiple access (OFDMA) combined with dirty paper coding (DPC) assuming instantaneous channel state information (CSI), which is called as DPC-OFDMA. The ultimate objective is to minimize the total transmit power subject to individual required data rates constraints. To reduce the complexity of the optimal solution, the analysis is considered in two stages. The first stage addresses subcarriers allocation, in which users are allowable to share subcarriers. The second stage employs DPC technology to deal with simultaneous transmissions of the users sharing the same subcarriers. An efficient algorithm to choose the best possible ordering for DPC and the optimal precoding design of each user are also involved. Simulation results show that DPC-OFDMA scheme has high spectral and power efficiency than conventional fixed schemes, where fixed power and subcarriers are allocated to each user.

Writing on Dirty Paper with Feedback

Abstract: “Writing on dirty paper” refers to the communication problem over a channel with both noise and interference, where the interference is known to the encoder non-causally and unknown to the decoder. This problem is regarded as a basic building block in both the single-user and multiuser communications, and it has been extensively investigated by Costa and other researchers. However, little is known in the case that the encoder can have access to feedback from the decoder. In this paper, we study the dirty-paper coding problem for feedback Gaussian channels without or with memory. We provide the most power efficient coding schemes for this problem, i.e., the schemes achieve lossless interference cancelation. These schemes are based on the Kalman filtering algorithm, extend the Schalkwijk-Kailath feedback codes, have low complexity and a doubly exponential reliability function, and reveal the interconnections among information, control, and estimation over dirty-paper channels with feedback. This research may be found useful to, for example, powerconstrained sensor network communication.

On the Sum Rate of Multi-Antenna Broadcast Channels with Channel Estimation Error

Abstract: For multiple antenna broadcast channels, perfect channel state information (CSI) at the basestation plays a critical role in achieving the sum rate advantage provided by the multiple antennas. For practical system implementation, the CSI is usually estimated from training sequences. In this paper, we study the effect of channel estimation error on the sum rate capacity of multiple antenna broadcast channels. A lower bound is derived based on the sum rate performance of the zero forcing dirty paper coding scheme under CSI estimation error. A cooperative upper bound is established from the capacity upper bound of a single user multiple-input multiple-output (MIMO) channel given the same channel imperfectness. We further analyze the asymptotic sum rate loss caused by channel estimation error. If we assume that the variance of the channel estimation error is fixed, imperfect CSI results in a sum rate ceiling for high SNR. For systems with orthogonal training sequences and minimum mean square error (MMSE) channel estimator, the asymptotic sum rate loss is about N bit per channel use where N is the number of transmit antennas. I. INTRODUCTION Techniques employing multiple antennas are important for wireless communication systems because they provide the possibility of a significant increase in system spectrum effi- ciency. In the last decade, lots of works have been done on point-to-point, i.e., single user, multiple-input multiple-output (MIMO) systems. Larger rate gains, however, are available when MIMO multi-user systems are considered. Recently, the sum rate capacity of the multiple antenna broadcast channel, which models the downlink in a MIMO cellular network, was solved (1), (2), (3), (4). These works show that perfect channel state information (CSI) at the basestation is critical for the system to achieve the sum rate advantage. With perfect CSI,

Differentiated Rate Sceduling for MIMO Broadcast Channels

Abstract: We consider the problem of differentiated rate scheduling for the fading MIMO Gaussian broadcast channel, in the sense that the rates required by different users must satisfy certain rational rate constraints. When full channel state information (CSI) is available at the transmitter, the problem can be readily solved using dirty paper coding (DPC) and con- vex optimization techniques on the dual multiple-access channel (MAC). However, since in many practical applications full CSI is not feasible, and since the computational complexity may be prohibitive when the number of users is large, we focus on two simple schemes that require very little CSI: time-division opportunistic (TO) beamforming where in different time-slots the transmitter performs opportunistic beamforing only to users requiring the same rate, and weighted opportunistic (WO) beamforing where the random beams are assigned to those users having the largest weighted SINR. In both cases we determine explicit schedules to guarantee the rate constraints and show that, in the limit of a large number of users, the throughput loss compared to the unconstrained sum-rate capacity tends to zero. As a side result, we show that, in this regime, the sum-rate of opportunistic beamforming converges to the optimal sum-rate achieved by DPC, which is a stronger result than the order-optimal results of (10, 13).

Method and apparatus for rate compatible dirty paper coding

Abstract: A medium access control (MAC) entity first computes an achievable rate region based on a total transmit power limit and a channel gain of each of a plurality of WTRUs. Next, the MAC entity selects an order of DPC among the WTRUs. A rate set for use in transmitting to the WTRUs is then selected, said rate set being within the computed achievable rate region. Then, based on the selected DPC order and rate set, a DPC entity performs DPC on a plurality of data streams intended for the plurality of WTRUs. If nested lattice-based DPC is utilized, rate compatibility is achieved by selecting proper nesting ratios corresponding to a desired data rate set. Otherwise, if binary-code based DPC is utilized, rate compatibility is achieved via selecting appropriate message input sizes for input to point-to-point coding units prior to performing DPC.

Structured Dirty Paper Coding with Known Interference Structure at Receiver

Abstract: The Tomlinson-Harashima precoding is well known for dirty paper coding implementation. Despite its simplicity, THP suffers from a significant performance loss in the low SNR region due to modulo operations. In this paper, we propose new dirty paper precoding scheme by taking advantage of the known modulation structure of interference (e.g., BPSK and QPSK signals). The new method, termed structured DPC (SDPC), outperforms the regular THP with modest changes to the transmitter and receiver. For BPSK and QPSK cases investigated, the SDPC only suffers power loss, which is up to 1.25 dB compared with non-interference case, while the regular THP-based scalar dirty paper coding has a typical 4-5 dB capacity loss in the same low SNR regions

Linear and Dirty‐Paper Techniques for the Multiuser MIMO Downlink

Abstract: Multi-input, multi-output (MIMO) communications systems have attracted considerable attention over the past decade, mostly for single-user, point-to-point scenarios. The multipleuser MIMO case has attracted less attention, and most of the research on this problem has focused on uplink communications. Only recently has the multi-user MIMO downlink been addressed, beginning with information-theoretic capacity results [1–5], and followed by practical implementations, including those based on linear techniques [6, 7] and non-linear precoding [8–11]. In this chapter we review these techniques and discuss some important open problems.

Adaptive Precoding for Wireless MIMO Broadcast Channels with Limited Feedback

Abstract: SUMMARY Recently, a number of techniques have been introduced to exploit multiuser diversity of a wireless multiple-input multiple-output (MIMO) broadcast channel (BC) that consists of a base station with t transmit antennas and K users with multiple antennas. However, prior works have ignored the rate overhead associated with feedback of MIMO BC channel state information at transmitter (CSIT), which is roughly K times larger than single-user MIMO CSIT (i.e., it is O(tr )w herer = � K=1 rk and rk is the number of antennas at the kth user). Considering the amount of feedback signaling, quantization is a necessity for effective feedback transmission as a form of partial CSIT. In this paper, we propose the greedy multi-channel selection diversity (greedy MCSD) scheme based on block MMSE QR decomposition with dirty paper coding (block MMSE-DP), where partial CSIT is almost sufficient. The sum-rate performance of our novel scheme approaches extremely close to the sum capacity of MIMO BC as the number of users increases, whereas the feedback overhead is reduced by a factor of 2t 3 /L(t 2 −t), in which L is the number of active channel vectors. Simulation results validate the expectation from the analysis. In addition, the proposed scheme is shown to be appropriate for reconfigurable

Adaptive transmitter optimization in multiuser multiantenna systems: theoretical limits, effect of delays, and performance enhancements

Abstract: The advances in programmable and reconfigurable radios have rendered feasible transmitter optimization schemes that can greatly improve the performance of multiple-antenna multiuser systems. Reconfigurable radio platforms are particularly suitable for implementation of transmitter optimization at the base station. We consider the downlink of a wireless system with multiple transmit antennas at the base station and a number of mobile terminals (i.e., users) each with a single receive antenna. Under an average transmit power constraint, we consider the maximum achievable sum data rates in the case of (1) zero-forcing (ZF) spatial prefilter, (2) modified zero-forcing (MZF) spatial prefilter, and (3) triangularization spatial prefilter coupled with dirty-paper coding (DPC) transmission scheme. We show that the triangularization with DPC approaches the closed-loop MIMO rates (upper bound) for higher SNRs. Further, the MZF solution performs very well for lower SNRs, while for higher SNRs, the rates for the ZF solution converge to the MZF rates. An important impediment that degrades the performance of such transmitter optimization schemes is the delay in channel state information (CSI). We characterize the fundamental limits of performance in the presence of delayed CSI and then propose performance enhancements using a linear MMSE predictor of the CSI that can be used in conjunction with transmitter optimization in multiple-antenna multiuser systems.

Throughput analysis in wideband MIMO broadcast channels with partial feedback

Abstract: It has been recently shown that opportunistic transmit beamforming using partial channel state information (CSI) achieves the same throughput scaling obtained from dirty paper coding for a broadcast channel with fixed number of transmit antennas and many receivers M. Sharif et al., (2005). In this paper, we study the generalization of this scheme to wideband broadcast channels. By using orthogonal frequency division multiplexing, an L-tap wideband channel can be decomposed to N parallel narrowband channels, where N is larger than L. Neighboring subchannels are therefore highly correlated, and it is intuitive to say that each group of neighboring subchannels (forming a cluster) can be characterized by one channel quality. We show in this paper that users need only feedback the best signal-to-noise-plus-interference ratio at the center of each cluster. Our results indicate that for cluster size of order N/L/spl radic/K, where K is the number of users, this feedback scheme maintains the same throughput scaling as when full CSI is known. Simulation results show that larger cluster sizes (N/2L) can also be implemented for a small throughput hit.

Performance of adaptive precoding for wireless MIMO broadcast channels with limited feedback

Abstract: The capacity region of multiple-input multiple- output (MIMO) broadcast channel (BC) has attracted consider- able attention recently. The greedy block MMSE QR decompo- sition with dirty paper coding (greedy block MMSE-DP) scheme is a solution to achieves extremely close to channel capacity with limited feedback of channel state information at transmitter (CSIT). In this paper, we analysis the performance and consider the reconfigurable implementation of greedy block MMSE-DP. Numerical results indicate that the greedy block MMSE-DP approach significantly outperforms the TDMA-MIMO approach in terms of the system throughput even when a large amount of quantization error is added to the feedback information (e.g., when signal-to-quantization-error ratio (SER) values are 14, 10, and 6 dB). The scheme is shown to be appropriate for reconfigurable implementation.

Scalar scheme for multiple user information embedding

Abstract: Multiple watermarking is concerned with embedding several messages into the same host signal, with different robustness and transparency requirements. This paper proposes two implementable scalar schemes for multiple user "dirty paper coding". The first - straightforward - approach consists of an independent superposition of two scalar dirty paper coding schemes. The second consists in the joint design of a scalar dirty paper coding. This joint approach is based on the ideal dirty paper coding scheme for broadcast channels with noncausal side information known to the transmitter. For this purpose, the "scalar Costa scheme" that has been originally conceived for one user is extended to two users. Performance evaluations, including bit error rates and capacity region curves are provided for both methods, illustrating the improvements brought by a joint design.

Sum-rate maximization and sum-power minimization for 2-user (2,2) downlink systems using generalized zero-forcing

Abstract: The paper analyzes a downlink system where a 2-antenna base station is sending independent signals to two 2-antenna mobile users simultaneously in the same physical (time and frequency) channel. To multiplex the signals in the spatial domain, we consider the use of orthogonal space-division multiplexing (OSDM), broadly known as generalized zero-forcing (GZF), that allows the users to be completely separated before decoding. The paper's main contribution is that we derive the optimal array processing solutions for both the sum-rate maximization problem, subject to a fixed transmit power constraint, and the sum-power minimization problem, subject to a fixed rate constraint. The capacity and signal-to-noise ratio (SNR) regions for the OSDM system are also derived, and results for dirty-paper coding (DPC) and time-division systems are provided for comparison.

Limited Feedback Precoding for Wireless MIMO Broadcast Channels

Abstract: Recently, a number of techniques have been introduced to exploit multiuser diversity of a wireless multiple input multiple output (MIMO) broadcast channel (BC) that consists of a base station (BS) with t transmit antennas and K mobile stations (MS) with multiple antennas. However, prior works have ignored the rate overhead associated with feedback of MIMO BC channel state information (CSI), which is roughly K times larger than single-user MIMO CSI (i.e., it is O(tr) where r = Kk=1 rk and rk is the number of antennas at the kth MS). Considering the amount of feedback signaling, quantization is a necessity for effective feedback transmission as a form of partial CSI. In this paper, we propose the greedy multi-channel selection diversity (greedy MCSD) scheme based on blockMMSE QR decomposition with dirty paper coding (block MMSE-DP), where partial CSI is almost sufficient. The sum-rate performance of our novel scheme approaches extremely close to the sum capacity of MIMO BC as the number of users increases, whereas the feedback overhead is reduced by a factor of 2t3/L(t2−t), in which L is the number of active channel vectors. Simulation results validate the expectation from the analysis.

Efficient scheduling of multi-user multi-antenna systems

Abstract: The capacity region of the Gaussian multi-antenna broadcast channel was characterized recently in [19]. It was shown that a scheme based on Dirty Paper Coding [2] achieves the full capacity region when the transmitter has perfect channel state information. However, this scheme potentially involves considerable amounts of feedback and complex algorithms for coding and user selection. This has led to a quest for practical transmission schemes and ways to reduce the amount of channel state information required. In particular, it has been shown that when the total number of users is large, the sum capacity can be closely approached by transmitting to a small subset of near-orthogonal users. In order to further quantify the latter observation, we study a Gaussian broadcast channel with two transmit antennas and K statistically identical, independent users each with a single receive antenna. We obtain an exact asymptotic characterization of the gap between the full sum capacity and the rate that can be achieved by transmitting to a suitably selected pair of users. Specifically, we consider various simple schemes for user-pair selection that take into account the channel norms as well as the relative orientation of the channel vectors. We conclude that a scheme that picks the strongest user and selects a second user to form the best pair, is asymptotically optimal, while also being attractive in terms of feedback and operational complexity.

A Dirty Paper Coding Approach Without Modulo Operation at the Receiver

Abstract: We consider a precoding scheme without modulo operation at the receiver for the Gaussian channel with Gaussian interference which is known causally at the transmitter. Modulo operation which is conventionally applied to the received signal for the sake of convenience in analysis causes information loss. In this paper, we investigate the gain in capacity by removing modulo operation at the receiver. We also propose an end-to-end communication scheme based on the proposed precoding scheme by concatenating the precoder with LDPC codes. Bit error rate curves also confirm the superiority of the precoding method without modulo operation at the receiver.

Adaptive transmitter optimization in multiuser multiantenna systems : Theoretical limits, effect of delays, and performance enhancements : Reconfigurable radio for future generations wireless systems

Abstract: The advances in programmable and reconfigurable radios have rendered feasible transmitter optimization schemes that can greatly improve the performance of multiple-antenna multiuser systems. Reconfigurable radio platforms are particularly suitable for implementation of transmitter optimization at the base station. We consider the downlink of a wireless system with multiple transmit antennas at the base station and a number of mobile terminals (i.e., users) each with a single receive antenna. Under an average transmit power constraint, we consider the maximum achievable sum data rates in the case of (1) zero-forcing (ZF) spatial prefilter, (2) modified zero-forcing (MZF) spatial prefilter, and (3) triangularization spatial prefilter coupled with dirty-paper coding (DPC) transmission scheme. We show that the triangularization with DPC approaches the closed-loop MIMO rates (upper bound) for higher SNRs. Further, the MZF solution performs very well for lower SNRs, while for higher SNRs, the rates for the ZF solution converge to the MZF rates. An important impediment that degrades the performance of such transmitter optimization schemes is the delay in channel state information (CSI). We characterize the fundamental limits of performance in the presence of delayed CSI and then propose performance enhancements using a linear MMSE predictor of the CSI that can be used in conjunction with transmitter optimization in multiple-antenna multiuser systems.

Fairscheduling andorthogonal linear precoding/decoding inbroadcast MIMO systems

Abstract: Inthedownlink ofamulti-user MIMO system over afading channel, thebasestation canassign theavailable spatial streams todifferent users bycapitalizing onmultiuser diversity orenforcing fairness constraints. Assuming linear precoding (beamforming) atthebasestation, theproblem amounts tothe joint design ofprecoding matrices andchannel awarescheduling, according tothecross-layer paradigm. Inthis paperweformulate thejoint optimization ofscheduling andlinear precoding within a physical layer-oriented framework, wheretheperformance metric isthetransmission rate. Moreover, we constraint the precoding scheme toensure interference-free Inthedownlink ofamulti-user system, thedeployment of anantenna array atthebasestation (oraccess point) allows thesimultaneous transmission tomultiple users withcontrolled interference. Inparticular ifthebasestation isequipped with NT transmitting antennas andisprovided withthechannel state information ofdifferent users (i.e., through afeedback link), uptoNT single-antenna terminals canbeserved si- multaneously byNTindependently encoded substreams. More generally, foramulti-user MIMOsystem, eachterminal hasan antenna array with, say, NR< NTantennas, andthusspatial multiplexing canassign uptoNRdata streams toeachuser outofthetotal amountofNTavailable spatial channels (1). Itisthenthetask ofascheduling algorithm toselect within eachtime-slot, saythetth, thesubset ofK(t) < NTusers to beserved andthenumberofspatial streams dk(t) < NRto begranted toeachterminal. Conventional design ofthetransmission strategy atthe physical layer (i.e., coding, beamforming andpoweralloca- tion) assumes that thescheduling step isperformed separately byhigher layers according toquality ofservice requirements andsystem parameters. Theoptimal transmission strategy, fromaninformation theoretic point ofview, employs joint encoding ofthesignal streams (Dirty paper coding) andlinear spatial filtering (2). Suboptimal andmorepractical algorithms that perform separate encoding ofdifferent streams havebeen proposed. Specifically, alinear precoding/ decoding algorithm thatforlarge signal-to-noise ratio maximizes thesum rate °This isaninvited paper tothespecial session on'Cross-layer scheduling forMIMO systems' whichisjointly organized bytheIST-NEWCOMand IST-ACE projects.

Writing on Fading Paper and Causal Transmitter CSI

Abstract: A wideband fading channel is considered with causal channel state information (CSI) at the transmitter and no receiver CSI. A simple orthogonal code with energy detection rule at the receiver (similar to [6]) is shown to achieve the capacity of this channel in the limit of large bandwidth. This code transmits energy only when the channel gain is large enough. In this limit, this capacity without any receiver CSI is the same as the capacity with full receiver CSI--a phenomenon also true for dirty paper coding. For Rayleigh fading, this capacity (per unit time) is proportional to the logarithm of the bandwidth. Our coding scheme is motivated from the Gel'fand-Pinsker [2,3] coding and dirty paper coding [4]. Nonetheless, for our case, only causal CSI is required at the transmitter in contrast with dirty-paper coding and Gel'fand-Pinsker coding, where non-causal CSI is required. Then we consider a general discrete channel with i.i.d. states. Each input has an associated cost and a zero cost input "0" exists. The channel state is assumed be to be known at the transmitter in a causal manner. Capacity per unit cost is found for this channel and a simple orthogonal code is shown to achieve this capacity. Later, a novel orthogonal coding scheme is proposed for the case of causal transmitter CSI and a condition for equivalence of capacity per unit cost for causal and non-causal transmitter CSI is derived. Finally, some connections are made to the case of non-causal transmitter CSI in [8].