Showing papers on "Dirty paper coding published in 2008"

Degrees of Freedom Region of the MIMO $X$ Channel

Abstract: We provide achievability as well as converse results for the degrees of freedom region of a multiple-input multiple-output (MIMO) X channel, i.e., a system with two transmitters, two receivers, each equipped with multiple antennas, where independent messages need to be conveyed over fixed channels from each transmitter to each receiver. The inner and outer bounds on the degrees of freedom region are tight whenever integer degrees of freedom are optimal for each message. With M = 1 antennas at each node, we find that the total (sum rate) degrees of freedom are bounded above and below as 1 les eta*x les 4/3. If M > 1 and channel matrices are nondegenerate then the precise degrees of freedom eta*x = (4/3)M. Thus, the MIMO X channel has noninteger degrees of freedom when M is not a multiple of 3. Simple zero forcing without dirty paper encoding or successive decoding, suffices to achieve the (4/3)M degrees of freedom. If the channels vary with time/frequency then the channel with single antennas (M = 1) at all nodes has exactly 4/3 degrees of freedom. The key idea for the achievability of the degrees of freedom is interference alignment-i.e., signal spaces are aligned at receivers where they constitute interference while they are separable at receivers where they are desired. We also explore the increase in degrees of freedom when some of the messages are made available to a transmitter or receiver in the manner of cognitive radio.

MIMO Relaying With Linear Processing for Multiuser Transmission in Fixed Relay Networks

Abstract: In this paper, a novel relaying strategy that uses multiple-input multiple-output (MIMO) fixed relays with linear processing to support multiuser transmission in cellular networks is proposed. The fixed relay processes the received signal with linear operations and forwards the processed signal to multiple users creating a multiuser MIMO relay. This paper proposes upper and lower bounds on the achievable sum rate for this architecture assuming zero-forcing dirty paper coding at the base station, neglecting the direct links from the base station to the users, and with certain structure in the relay. These bounds are used to motivate an implementable multiuser precoding strategy that combines Tomlinson-Harashima precoding at the base station and linear signal processing at the relay, adaptive stream selection, and QAM modulation. Reduced complexity algorithms based on the sum rate lower bounds are used to select a subset of users. We compare the sum rates achieved by the proposed system architecture and algorithms with the sum rate upper bound and the sum rate achieved by the decode-and-forward relaying.

The capacity gain from intercell scheduling in multi-antenna systems

Abstract: The capacity and robustness of cellular MIMO systems is very sensitive to other-cell interference which will in practice necessitate network level interference reduction strategies. As an alternative to traditional static frequency reuse patterns, this paper investigates intercell scheduling among neighboring base stations. We show analytically that cooperatively scheduled transmission, which is well within the capability of present systems, can achieve an expanded multiuser diversity gain in terms of ergodic capacity as well as almost the same amount of interference reduction as conventional frequency reuse. This capacity gain over conventional frequency reuse is O (M t square-root of log Ns) for dirty paper coding and O (min (Mr, Mt) square-root of log Ns) for time division, where Ns is the number of cooperating base stations employing opportunistic scheduling in an M t x M r MIMO system. From a theoretical standpoint, an interesting aspect of this analysis comes from an altered view of multiuser diversity in the context of a multi-cell system. Previously, multiuser diversity capacity gain has been known to grow as O(log log K), from selecting the maximum of K exponentially-distributed powers. Because multicell considerations such as the positions of the users, lognormal shadowing, and pathless affect the multiuser diversity gain, we find instead that the gain is O(square-root of 2logic K), from selecting the maximum of a compound Iognormal-exponential distribution. Finding the maximum of such a distribution is an additional contribution of the paper.

On the capacity of cognitive relay assisted Gaussian interference channel

Abstract: This paper studies a two source, two destination Gaussian interference channel in the presence of a cognitive relay. The cognitive relay has access to the messages transmitted by both the sources and assists them in communicating the messages successfully to their respective destinations. An achievable rate region for the system is derived by combining the Han-Kobayashi coding scheme for the general interference channel with dirty paper coding. The paper also derives outer bounds on the capacity region and obtains the degrees of freedom of the system.

User Selection With Zero-Forcing Beamforming Achieves the Asymptotically Optimal Sum Rate

Abstract: In this paper, we propose a generalized greedy (G-greedy) algorithm based on zero-forcing beamforming (ZFBF) for the multiple-input multiple-output (MIMO) broadcast channel. This algorithm serves as a general mathematical framework that includes a number of existing greedy user selection methods as its realizations. As previous results only give the scaling law of the sum rate of dirty paper coding (DPC), with the help of the G-greedy structure, we are able to obtain the exact limit of the DPC sum rate for a large number of users. We also prove that the difference between the sum rates obtained by G-greedy user selection and by DPC goes to zero as the number of users increases. In addition to this, we investigate one particular greedy user selection scheme called sequential water-filling (SWF). For this algorithm, a complexity reduction is achieved by an iterative procedure based on an LQ decomposition, which converts the calculation of the Moore-Penrose matrix inverse to one vector-matrix multiplication. A sufficient condition is given to prune the search space of this algorithm that results in further complexity reduction. With the help of the G-greedy algorithm, we prove that SWF achieves the full DPC sum rate for a large number of users. For a moderate number of users, simulation demonstrates that, compared with other user selection algorithms, SWF achieves a higher sum rate that is close to the maximal sum rate achievable by ZFBF with the same order of complexity.

Multiaccess channels with state known to some encoders and independent messages

Abstract: We consider a state-dependent multiaccess channel (MAC) with state noncausally known to some encoders. For simplicity of exposition, we focus on a two-encoder model in which one of the encoders has noncausal access to the channel state. The results can in principle be extended to any number of encoders with a subset of them being informed. We derive an inner bound for the capacity region in the general discrete memoryless case and specialize to a binary noiseless case. In binary noiseless case, we compare the inner bounds with trivial outer bounds obtained by providing the channel state to the decoder. In the case of maximum entropy channel state, we obtain the capacity region for binary noiseless MAC with one informed encoder. For a Gaussian state-dependent MAC with one encoder being informed of the channel state, we present an inner bound by applying a slightly generalized dirty paper coding (GDPC) at the informed encoder and a trivial outer bound by providing channel state to the decoder also. In particular, if the channel input is negatively correlated with the channel state in the random coding distribution, then GDPC can be interpreted as partial state cancellation followed by standard dirty paper coding. The uninformed encoders benefit from the state cancellation in terms of achievable rates, however, it seems that GDPC cannot completely eliminate the effect of the channel state on the achievable rate region, in contrast to the case of all encoders being informed. In the case of infinite state variance, we provide an inner bound and also provide a nontrivial outer bound for this case which is better than the trivial outer bound.

On the Achievable Rate Regions for Interference Channels With Degraded Message Sets

Abstract: The interference channel with degraded message sets (IC-DMS) refers to a communication model, in which two senders attempt to communicate with their respective receivers simultaneously through a common medium, and one sender has complete and a priori (noncausal) knowledge about the message being transmitted by the other. A coding scheme that collectively has advantages of cooperative coding, collaborative coding, and dirty paper coding, is developed for such a channel. With resorting to this coding scheme, achievable rate regions of the IC-DMS in both discrete memoryless and Gaussian cases are derived. The derived achievable rate regions generally include several previously known rate regions as special cases. A numerical example for the Gaussian case further demonstrates that the derived achievable rate region offers considerable improvements over these existing results in the high-interference-gain regime.

Apparatus and method for interference cancellation in multi-antenna system

Abstract: An apparatus and a method for interference cancellation in a transmitting end of a multi-antenna system are provided. A precode is generated which maximizes a diversity gain of one or more receive antennas using channel information of the receive antennas to be serviced. Transmit powers of the receive antennas are updated by taking into account a power loss and a shaping loss according to a dirty paper coding. Transmit signals are precoded by updating the precode according to the updated transmit powers. The dirty paper coding is performed on the precoded transmit signals to be transmitted to the receive antennas.

Block diagonal geometric mean decomposition (BD-GMD) for MIMO broadcast channels

Abstract: In recent years, the research on multiple-input multiple-output (MIMO) broadcast channels has attracted much interest, especially since the discovery of the broadcast channel capacity achievable through the use of dirty paper coding (DPC). In this paper, we propose a new matrix decomposition, called the block diagonal geometric mean decomposition (BD-GMD), and develop transceiver designs that combine DPC with BD- GMD for MIMO broadcast channels. We also extend the BD- GMD to the block diagonal uniform channel decomposition (BD- UCD) with which the MIMO broadcast channel capacity can be achieved. Our proposed schemes decompose each user's MIMO channel into parallel subchannels with identical SNRs/SINRs, thus equal-rate coding can be applied across the subchannels of each user. Numerical simulations show that the proposed schemes demonstrate superior performance over conventional schemes.

Broadcast in MIMO Systems Based on a Generalized QR Decomposition: Signaling and Performance Analysis

Abstract: A simple signaling method for broadcast channels with multiple-transmit multiple-receive antennas is proposed. In this method, for each user, the direction in which the user has the maximum gain is determined. The best user in terms of the largest gain is selected. The corresponding direction is used as the modulation vector (MV) for the data stream transmitted to the selected user. The algorithm proceeds in a recursive manner where in each step, the search for the best direction is performed in the null space of the previously selected MVs. It is demonstrated that with the proposed method, each selected MV has no interference on the previously selected MVs. Dirty-paper coding is used to cancel the remaining interference. For the case that each receiver has one antenna, the presented scheme coincides with the known scheme based on Gram-Schmidt orthogonalization (QR decomposition). To analyze the performance of the scheme, an upper bound on the cumulative distribution function (CDF) of each subchannel is derived which is used to establish the diversity order and the asymptotic sum-rate of the scheme. It is shown that using fixed rate codebooks, the diversity order of the jth data stream, 1 les j les M, is equal to N(M - j + 1)(K - j + 1), where M, N, and K indicate the number of transmit antennas, the number of receive antennas, and the number of users, respectively. Furthermore, it is proven that the throughput of this scheme scales as M log log(K) and asymptotically (K rarr infin) tends to the sum-capacity of the multiple-input multiple-output (MIMO) broadcast channel. The simulation results indicate that the achieved sum-rate is close to the sum-capacity of the underlying broadcast channel.

Multiuser MIMO two-way relaying for cellular communications

Abstract: Two-way relaying, which enables bidirectional simultaneous data transmission between two nodes, is an efficient means to reduce the spectral efficiency loss observed in conventional half-duplex relaying schemes. In this paper, we consider a multiuser cellular two-way relaying scenario with several mobile stations (MSs) at one end of the bidirectional link and a single base station (BS) serving all MSs at the other end. Both the BS and the MSs exchange private messages simultaneously via a single relay node, i.e., concurrent uplink and downlink, in only two time slots, independent of the number of MSs. In the downlink, while the relay separates different MSs spatially, e.g., using either zero-forcing beamforming or zero-forcing dirty paper coding, it benefits from XOR precoding followed by self-interference cancellation, in order to separate messages within a message pair to be exchanged between the BS and each MS. The corresponding sum rate optimization problem is solved with an iterative algorithm based on semidefinite programming.

On the Fading-Paper Achievable Region of the Fading MIMO Broadcast Channel

Abstract: We consider transmission over the ergodic fading multiple-antenna broadcast (MIMO-BC) channel with partial channel state information at the transmitter and full information at the receiver. Over the equivalent non-fading channel, capacity has recently been shown to be achievable using transmission schemes that were designed for the "dirty paper" channel. We focus on a similar "fading paper" model. The evaluation of the fading paper capacity is difficult to obtain. We confine ourselves to the linear-assignment capacity, which we define, and use convex analysis methods to prove that its maximizing distribution is Gaussian. We compare our fading-paper transmission to an application of dirty paper coding that ignores the partial state information and assumes the channel is fixed at the average fade. We show that a gain is easily achieved by appropriately exploiting the information. We also consider a cooperative upper bound on the sum-rate capacity as suggested by Sato. We present a numeric example that indicates that our scheme is capable of realizing much of this upper bound.

Beam Selection Strategies for Orthogonal Random Beamforming in Sparse Networks

Abstract: Orthogonal random beamforming (ORB) constitutes a mean to exploit spatial multiplexing and multi-user diversity (MUD) gains in multi-antenna broadcast channels. To do so, as many random beamformers as transmit antennas (M) are generated and on each beam the user experiencing the most favorable channel conditions is scheduled. Whereas for a large number of users the sum-rate of ORB exhibits an identical growth rate as that of dirty paper coding, performance in sparse networks (or in networks with an uneven spatial distribution of users) is known to be severely impaired. To circumvent that, in this paper we modify the scheduling process in ORB in order to select a subset out of the M available beams. We propose several beam selection algorithms and assess their performance in terms of sum-rate and aggregated throughput (i.e., rate achieved with practical modulation and coding schemes), along with an analysis of their computational complexity. Since ORB schemes require partial channel state information (CSI) to be fed back to the transmitter, we finally investigate the impact of CSI quantization on system performance. More specifically, we prove that most of the MUD can be still exploited with very few quantization bits and we derive a beam selection approach trading-off system performance vs. feedback channel requirements.

MIMO Spatial Spectrum Sharing for High Efficiency Mesh Network

Abstract: In this paper, an architecture of MIMO mesh network which avoids co-channel interference and supplies link multiplexing simultaneously, namely MIMO spatial spectrum sharing, is proposed. As a MIMO transmission scheme, linear (such as zero-forcing) and nonlinear (such as dirty paper coding and successive interference cancellation) MIMO algorithm are developed for the proposed mesh network. It is found from numerical analysis that the proposed MIMO mesh network achieves significantly higher channel capacity than that of conventional mesh networks.

Cooperative relaying with state available at the relay

Abstract: We consider a state-dependent full-duplex relay channel with the state of the channel non-causally available at only the relay. In the framework of cooperative wireless networks, some specific terminals can be equipped with cognition capabilities, i.e, the relay in our model. In the discrete memoryless (DM) case, we derive lower and upper bounds on channel capacity. The lower bound is obtained by a coding scheme at the relay that consists in a combination of codeword splitting, Gelpsilafand-Pinsker binning, and a decode-and-forward scheme. The upper bound is better than that obtained by assuming the availability of state at the source, the relay, and the destination. For the Gaussian case, we also derive lower and upper bounds on channel capacity. The lower bound, obtained by a coding scheme based on combination of codeword splitting and generalized dirty paper coding, is tight in some cases if the channel is physically degraded. The upper bound is also better than that obtained by assuming that the channel state is available at the source, the relay, and the destination.

Weighted max-min fair beamforming, power control, and scheduling for a MISO downlink

Abstract: In this paper, we consider the joint beamforming, power control and scheduling problem in a multiple-input single- output (MISO) downlink for maximizing the minimum weighted rate among all users. We solve this problem by formulating it as a convex optimization problem whose function evaluations require maximization of a difference of convex functions (D.C. Programming). We also propose a simpler heuristic that finds the best policy under restricted set of power vectors. We then compare the performance of these policies against the dirty paper coding (DPC) policy to quantify the performance gap between an optimal point-to-point coding approach and an optimal joint encoding/decoding approach.

When network coding and dirty paper coding meet in a cooperative ad hoc network

Abstract: We develop and analyze new cooperative strategies for ad hoc networks that are more spectrally efficient than classical decode & forward (DF) protocols. Using analog network coding, our strategies preserve the practical half-duplex assumption but relax the orthogonality constraint. The introduction of interference due to non-orthogonality is mitigated thanks to precoding, in particular dirty paper coding. Combined with smart power allocation, our cooperation strategies allow to save time and lead to a more efficient use of the bandwidth and to improved network throughput with respect to classical repetition-DF and parallel-DF.

Sum Rate Maximization of MIMO Broadcast Channels with Coordination of Base Stations

Abstract: We consider cooperative downlink transmission in multiuser, multi-cell and multiple-antenna cellular networks. It has been shown that multi-base coordinated transmission has significant spectral efficiency gains over that without coordination. The capacity limits can be achieved using a non-linear preceding technique known as dirty paper coding, which is still infeasible to implement in practice. This motivates investigation of a simpler linear preceding technique based on generalized zero-forcing known as block diagonalization (BD). In this paper, an enhanced form of BD is proposed for multiple-input multiple-output (MIMO) multi-base coordinated network. It involves optimizing the precoding over the entire null space of other users' transmissions. The performance limits of the multiple-antenna downlink with multi-base coordination are studied using duality of MIMO broadcast channels (BC) and MIMO multiple-access channels (MAC) under per-antenna power constraint, which has been established recently.

Dirty Paper Coding for fading channels with partial transmitter side information

Abstract: The problem of dirty paper coding (DPC) over the fading dirty paper channel (FDPC) Y=H(X+S)+Z, a more general version of Costa's channel, is studied for the case in which there is partial and perfect knowledge of the fading process H at the transmitter (CSIT) and the receiver (CSIR), respectively. A key step in this problem is to determine the optimal inflation factor (under Costa's choice of auxiliary random variable) when there is only partial CSIT. Towards this end, two iterative numerical algorithms are proposed. Both of these algorithms are seen to yield a good choice for the inflation factor. Finally, the high-SNR (signal-to-noise ratio) behavior of the achievable rate over the FDPC is dealt with. It is proved that FDPC (with t transmit and r receive antennas) achieves the largest possible scaling factor of min(t,r) log SNR even with no CSIT. Furthermore, in the high SNR regime, the optimality of Costa's choice of auxiliary random variable is established even when there is partial (or no) CSIT in the special case of FDPC with t les r. Using the high-SNR scaling-law result of the FDPC (mentioned before), it is shown that a DPC-based multi-user transmission strategy, unlike other beamforming-based multi-user strategies, can achieve a single-user sum-rate scaling factor over the multiple-input multiple-output Gaussian Broadcast Channel with partial (or no) CSIT.

DPC-Based Hierarchical Broadcasting: Design and Implementation

Abstract: This paper discusses interference precancellation in digital hierarchical broadcasting (HB). In particular, we present the principles and implementation of structured dirty paper coding (SDPC) that approaches the capacity limit of dirty paper coding in multilayer broadcasting. As an alternative to Tomlinson-Harashima precoding (THP), SDPC eliminates the significant performance loss suffered by THP in the low signal-to-noise ratio (SNR) regime due to the modulo operation. The key idea behind the SDPC scheme is the exploitation of the modulation structure of interference, thereby simplifying the demodulation process in hierarchical reception. We exemplify the SDPC technique by implementing an SDPC-based HB system on a real-time test bed. The experimental results show that SDPC delivers the performance of ldquosuperposition coding with successive interference cancellationrdquo without extra computation or memory requirements at the receiver side.

Cognitive Radio with Partial Channel State Information at the Transmitter

Abstract: Cognitive radio (CR) has been proposed as an efficient method to reuse the licensed spectrum. It recognizes the primary (licensed) users' signals and adapts its own to minimize the interference it generates. When perfect channel state information is known at the transmitters, the capacity of CR system can be achieved by utilizing the dirty paper coding (DPC). In this paper, we consider the performance of the CR system under both fast and slow fading channels with only channel statistics known at the transmitters. Due to the limited channel state information, the original DPC fails and is replaced by the so-called linear-assignment Gel'fand-Pinsker coding. By carefully designing the parameters based on this preceding, this system has significant rate gains over naively treating primary users' signals as interference for fast and slow fading scenarios.

Rate bounds for MIMO relay channels

Abstract: This paper considers the multi-input multi-output (MIMO) relay channel where multiple antennas are employed by each terminal. Compared to single-input single-output (SISO) relay channels, MIMO relay channels introduce additional degrees of freedom, making the design and analysis of optimal cooperative strategies more complex. In this paper, a partial cooperation strategy that combines transmit-side message splitting and block-Markov encoding is presented. Lower bounds on capacity that improve on a previously proposed non-cooperative lower bound are derived for Gaussian MIMO relay channels.1

User Selection for Multiple-Antenna Broadcast Channel with Zero-Forcing Beamforming

Abstract: This paper investigates the zero-forcing (ZF) beamforming transmit strategy in the multiple-antenna multiuser downlink systems. We consider the case of mobile users equipped with multiple antennas. Although the capacity of such systems can be achieved by dirty paper coding (DPC), DPC is extremely difficult and challenging to implement. Thus, simple but suboptimal linear beamforming techniques like ZF beamforming can be deployed. However, the number of users that can be served using this strategy is limited by the number of transmit antennas at the base station. The solution for this limitation is user selection (scheduling), which also exploits multiuser diversity. Therefore, user selection can be used to enhance the throughput of the system. Recently, it has been shown that ZF beamforming strategy with user selection is asymptotically optimal for a large number of users. In this paper, a semi-orthogonal user selection (SUS) algorithm is extended to the system with multiple-antenna mobile users. This algorithm aims to select users, which are semi-orthogonal. The optimal ZF beamforming matrices are obtained and it is shown that the optimal ZF beamforming throughput is related to the eigenvalues of the user channels. Therefore, SUS is aimed to select the proper group of users based on maximizing the channel eigenvalues and therefore improving the optimal ZF beamforming throughput of the system.

Arbitrarily dirty paper coding and applications

Abstract: A deterministic dirty-paper coding strategy for communication over an arbitrarily varying channel with an interference signal known to the transmitter is investigated. The presence of a known interference signal at the transmitter is shown to provide some protection against jamming interference. For some values of the parameters the scheme is capacity- achieving. Applications to watermarking and spectrum-sharing channels are described.

Cooperative strategies for the half-duplex Gaussian parallel relay channel: Simultaneous relaying versus successive relaying

Abstract: We consider the problem of cooperative communication for a network composed of two half-duplex parallel relays with additive white Gaussian noise. Two protocols, i.e., Simultaneous and Successive relaying, associated with two possible relay orderings are proposed. The simultaneous relaying protocol is based on dynamic decode and forward (DDF) scheme. For the successive relaying protocol, a Non-Cooperative Coding based on dirty paper coding (DPC) is proposed. We also propose a general achievable rate based on the combination of the proposed simultaneous and successive relaying schemes. The optimum ordering of the relays and hence the capacity of the half-duplex Gaussian parallel relay channel in low and high SNR scenarios is derived. In low SNR scenario, we show that under certain conditions for the channel coefficients the ratio of the achievable rate of the simultaneous relaying protocol, based on the DDF scheme, to the cut-set bound of the half-duplex Gaussian parallel relay channel tends to 1. On the other hand, as SNR goes to infinity, we prove that successive relaying protocol, based on the DPC scheme, asymptotically achieves the capacity of the network.

Efficient linear successive allocation for the MIMO broadcast channel

Abstract: To avoid the complexity of nearly optimum implementations for dirty paper coding (DPC) linear zero-forcing approaches are often preferred. Finding the optimum user allocation, transmit and receive filters for maximizing sum rate in the multiple-input multiple-output (MIMO) broadcast channel constitutes a non-convex combinatorial optimization problem. Here we present an efficient linear zero-forcing algorithm for this problem, which is derived from maximizing a lower bound for the sum rate. It successively allocates data streams to users and in contrast to state of the art approaches thereby also determines the corresponding receive filters. Compared to existing approaches drastic complexity reductions can be achieved even with slight performance gains.

Gaussian Degraded Relay Broadcast Channel

Abstract: The relay broadcast channel (RBC) models a system where a transmitter sends information to multiple receivers, aided by the presence of a dedicated relay node. In the Gaussian case with two receivers, under the assumption that both receivers are degraded with respect to the relay, it is shown that the capacity region is achieved by a superposition strategy. This strategy is also shown to be optimal in the case where there is feedback from the receivers to the relay and one receiver assumed to be degraded with respect to the other in an appropriate sense. We also present an achievable region for a more general Gaussian RBC (GRBC) model.

A New Achievable Rate Region for the Cognitive Radio Channel

Abstract: The cognitive radio channel (CRC) refers to a communication model in which two senders attempt to communicate with their respective receivers simultaneously through a common medium, and one of the senders has complete and a priori (non-causal) knowledge about the message being transmitted by the other. A coding scheme that collectively has advantages of cooperative coding, collaborative coding, and dirty paper coding, is developed for such a channel. With resorting to this coding scheme, a new achievable rate region for the CRC is derived, which includes several previously known rate regions. Furthermore, it is demonstrated by Gaussian numerical examples that the new achievable rate region offers strict improvements over the existing results in the high-interference-gain regime.

Cognitive Radio with Partial Channel State Information at the Transmitter

Abstract: In this paper, we present the cognitive radio system design with partial channel state information known at the transmitter (CSIT).We replace the dirty paper coding (DPC) used in the cognitive radio with full CSIT by the linear assignment Gel'fand-Pinsker coding (LA-GPC), which can utilize the limited knowledge of the channel more efficiently. Based on the achievable rate derived from the LA-GPC, two optimization problems under the fast and slow fading channels are formulated. We derive semianalytical solutions to find the relaying ratios and precoding coefficients. The critical observation is that the complex rate functions in these problems are closely related to ratios of quadratic form. Simulation results show that the proposed semi-analytical solutions perform close to the optimal solutions found by brute-force search, and outperform the systems based on naive DPC. Asymptotic analysis also shows that these solutions converge to the optimal ones solved with full CSIT when the K-factor of Rician channel approaches infinity. Moreover, a new coding scheme is proposed to implement the LA-GPC in practice. Simulation results show that the proposed practical coding scheme can efficiently reach the theoretical rate performance.

Wyner-Ziv coding over broadcast channels

Abstract: This paper deals with the design of coding schemes for lossy transmission of a source over a broadcast channel when there is correlated side information at the receivers. Using ideas from Slepian-Wolf coding over broadcast channels and dirty paper coding, new schemes are presented and their rate-distortion performance is derived. For the binary Hamming and quadratic Gaussian scenarios, when the source and the channel bandwidths are equal, it is shown that these schemes are sometimes optimal and that they can outperform both separate source and channel coding, and uncoded transmission.