Improved iterative water-filling algorithm in MU-MIMO system

In this paper, we first look at the achievable rate regions of the Gaussian Multiple Access Channel (G-MAC) and Gaussian Broadcast Channel (G-BC) when discrete constellations are transmitted. Focusing on the two-user case and assuming uncoded Pulse Amplitude Modulation (PAM), we show that the rate regions of G-MAC and G-BC can be improved by power conservation at the transmitter, a factor ignored in the earlier derived rate regions. We then further investigate duality between the G-MAC and the G-BC and show that a rate pair achieved in the G-MAC can be translated to a rate pair in the dual G-BC, such that the equal sum power constraint be satisfied. Due to the similarity of the rate expressions to Shannon's capacity formula, for an appropriate choice of signal to noise ratio (SNR) gap, we show that when finite constellations are used for transmission, rate regions of these two channels also have a dual relationship (the known for Gaussian alphabets). The rate region of the G-BC can therefore be characterized from the rate region of the dual G-MAC and vice versa.

This paper provides a novel low complexity and provably convergent algorithm to find the sum capacity for vector Gaussian broadcast channels. We formulate the problem in the context of a MIMO-OFDM system and discuss the simplifications provided by the block diagonal channel structure. The algorithm also provides the optimum set of covariance matrices for the dual multiple access channel, from which the transmit covariance matrices for the broadcast channel are easy to compute. The key idea of the algorithm is to iteratively maximize the sum capacity for randomly selected pairs of users whilst considering the other users' signals as noise. The proposed algorithm can be considered dual to the iterative water filling (IWF) algorithm used to maximize the sum capacity for the multiple access channel with individual power constraints, but unlike the recently proposed sum power constraint IWF, our proposed algorithm has lower complexity and does not require additional precautions to ensure the convergence. We have proved analytically that the proposed algorithm is convergent in probability and the computer simulations clearly show that the proposed algorithm converges faster than other known algorithms. Index Terms—Broadcast channels, MIMO systems, orthogonal frequency division multiplexing, iterative water-filling.

We study the Gaussian multiple-input multiple-output (MIMO) broadcast channel with common and private messages. We first obtain an outer bound for the capacity region of the two-user discrete memoryless broadcast channel with common and private messages. We next show that if jointly Gaussian random variables are sufficient to evaluate this outer bound for the Gaussian MIMO broadcast channel, the dirty-paper coding (DPC) region is the capacity region of the Gaussian MIMO broadcast channel with common and private messages. However, we can evaluate only a loosened version of this outer bound, which yields the result that extending the DPC region in the common message rate direction by a fixed amount is an outer bound for the capacity region of the Gaussian MIMO broadcast channel with common and private messages. However, this fixed amount, i.e., the gap, is not finite for all channels. We derive the necessary and sufficient conditions for this gap to be finite.

Analog transmission of correlated information over Gaussian broadcast channels (BCs) using analog joint source–channel coding (JSCC) is addressed. This communication strategy has attractive advantages, such as low complexity, minimal delay, graceful degradation, and adaptation to time-varying environments. In this paper, we focus on the optimization of parametric continuous mappings that satisfy individual quality of service requirements over Gaussian BCs. This optimization is based on the balancing of the user distortions to ensure the feasibility of the resulting optimization problems. An analysis of the overall distortion corresponding to the considered mappings is carried out to design algorithms that determine the optimal values for the mappings parameters. Results show that the proposed analog JSCC scheme provides near optimal performance and an adequate balancing of the individual distortions.

We propose a scalar upper bound on the capacity region of the isotropic fading vector broadcast channel in terms of the capacity region of a scalar fading broadcast channel. The scalar upper bound is applicable to the broad class of isotropic fading broadcast channels regardless of the distribution of the users' channel magnitudes, the distribution of the additive noise experienced by each user, or the amount of channel knowledge available at the receiver. Using this upper bound, we prove the optimality of the Alamouti scheme in a broadcast setting, extend the recent results on the capacity of nondegraded, fading scalar broadcast channels to nondegraded fading vector broadcast channels, and determine the capacity region of a fading vector Gaussian broadcast channel with channel magnitude feedback. We also provide an example of a Rayleigh-fading broadcast channel with no channel state information available to the receiver (CSIR), where the bound on the capacity region obtained by a naive application of the scalar upper bound is provably loose, because it fails to account for the additional loss in degrees of freedom due to lack of channel knowledge at the receiver. A tighter upper bound is obtained by separately accounting for the loss in degrees of freedom due to lack of CSIR before applying the scalar upper bound.

It has long been observed that cooperation between users in a communication network can improve its performance. Unfortunately, in practical ad-hoc networks, cooperation links can be unreliable, and in many cases part of the users in the system cannot be updated about their availability. In such a case we need robust coding schemes that exploit the cooperation links if they are present, but can still operate if cooperation is not possible. In this work we study the general broadcast channel with degraded message sets and cooperation link that may be absent, and derive its capacity region under such uncertainty conditions. A generalization of this model is studied, where the cooperation link capacity is one of k possible values, and its capacity region is derived. We examine the situation where the cooperation link capacity is random and suggest the following performance criterion: maximize the average rate of one user, subject to a constraint on the rate of the other user and the requirement that the system will operate in any realization of the (random) cooperation link. As examples to illustrate our results, the Gaussian broadcast channel is extensively examined, and its capacity is derived for the various cooperation models and assumptions suggested throughout.

Recently [16], we have proposed using faster than Nyquist (FTN) signaling to achieve transmission over continuous-time broadcast channels and shown that it can achieve the capacity region of the two-user Gaussian broadcast channel. Benefits of FTN broadcasting include separate encoding and explicit transmission of all users' data, i.e., unlike the previously proposed broadcast coding schemes, no joint encoding is needed. This paper presents a design of a Turbo-coded broadcast transmitter based on the FTN signaling. The proposed receiver architecture has a low implementation complexity and is based on Turbo decoding and successive cancellation of FTN-induced intersymbol interference. The presented simulation results indicate that the designed FTN broadcast architecture can be superior to the time-sharing broadcasting used in practice, and shows the potential to perform close to the capacity boundaries of the Gaussian broadcast channel.

In a multi-user channel, completion time refers to the number of channel uses required for users, each with some given fixed bit pool, to complete the transmission of all their data bits. This paper extends the information theoretic formulation of multi-access completion time to broadcast channel and interference channel, enabling us to obtain the so-called completion time region (CTR), which, analogous to capacity region, characterizes all possible trade-offs between users' completion times. Specifically, for Gaussian broadcast channel (GBC) and Gaussian interference channel (GIC) in the strong/very strong regime, the exact CTR is obtained. For GIC in the weak/mixed regime, an achievable CTR based on the Etkin-Tse-Wang scheme and an outer-bound are obtained.

This paper considers the problem of the multiple-input multiple-output (MIMO) Gaussian broadcast channel with two receivers (receivers 1 and 2) and two messages: a common message intended for both receivers and a confidential message intended only for receiver 1 but needing to be kept asymptotically perfectly secure from receiver 2. A matrix characterization of the secrecy capacity region is established via a channel enhancement argument. The enhanced channel is constructed by first splitting receiver 1 into two virtual receivers and then enhancing only the virtual receiver that decodes the confidential message. The secrecy capacity region of the enhanced channel is characterized using an extremal entropy inequality previously established for characterizing the capacity region of a degraded compound MIMO Gaussian broadcast channel.

A deterministic coding scheme is presented for additive white Gaussian broadcast channels with two receivers and feedback from the receivers to the transmitter. The region of data rates at which reliable communication is possible is larger than that of the corresponding channel without feedback. This is the first example showing that the capacity region of degraded broadcast channels can be enlarged with feedback.

In a broadcast channel, a single transmitter communicates to receivers with different channel capacities, a typical example of which is the over-the-air television broadcasting. A natural question that arises is evaluation of the optimal information transfer rate in such an environment. For the two-receiver case, we examine various transmission scenarios in this environment and focus on the theoretically optimal superposition scheme, where the information intended for the better channel is superimposed on the portion of information common to both receivers. As a result, a basic grade of service is maintained throughout the entire coverage area in addition to a higher quality service offered to the receivers with better reception conditions. Using end-to-end distortion and coverage channel signal-to-noise ratio threshold measures, three specific embedded signaling modes are introduced. We demonstrate that a generalized embedding scheme provides a practical trade-off between distortion and coverage radius. The scheme is also formulated in terms of an optimization problem, seeking the best embedding factor for a given application. To verify the theoretical results, we idealize a dual rate transmission system over a Gaussian broadcast channel, in which receivers are distributed according to a circularly symmetric exponential pdf. The numerical results indicate that this model offers a higher per capita data rate comparing to the conventional single rate transmission systems. Application of this multirate broadcast holds promise for multiresolution transmission of digital audio and high definition television.

Precoding schemes in the framework of vector perturbation (VP) for the multiple-input multiple-output (MIMO) Gaussian broadcast channel (GBC) are investigated. The VP scheme, originally a “one-shot” technique, is generalized to encompass processing over multiple time instances. Using lattice-based extended alphabets (“perturbations”), and considering the infinite time-span extension limit, a lower bound on the achievable sum-rate using the generalized VP scheme is analytically obtained, by which it is shown to achieve the optimum sum-rate in the high signal-to-noise ratio (SNR) regime (both in terms of degrees-of-freedom and power offset). The above lower bound is constructively obtained by means of an efficient practically oriented suboptimum transmit energy minimization algorithm, which has merits of its own, and it demonstrates the significant performance enhancement that can be obtained by preprocessing over multiple symbol instances, potentially eliminating the gap to the ultimate performance at high SNRs. For the 2×2 MIMO GBC, the VP scheme is generalized further, and an inner bound for the entire achievable rate region is obtained, by which an interesting correspondence is identified to the ultimate capacity region, as obtained by “dirty paper” coding (DPC).

Recent information-theoretic results show the optimality of dirty-paper coding (DPC) in achieving the full capacity region of the Gaussian multiple-input multiple-output (MIMO) broadcast channel (BC).This paper presents a DPC based code design for BCs.We consider the case in which there is an individual rate/signal-to-interference-plus-noise ratio (SINR) constraint for each user.For a fixed transmitter power, we choose the linear transmit precoding matrix such that the SINRs at users are uniformly maximized, thus ensuring the best bit-error rate performance.We start with Cover's simplest two-user Gaussian BC and present a coding scheme that operates 1.44 dB from the boundary of the capacity region at the rate of one bit per real sample (b/s) for each user.We then extend the coding strategy to a two-user MIMO Gaussian BC with two transmit antennas at the base-station and develop the first limit-approaching code design using nested turbo codes for DPC.At the rate of 1 b/s for each user, our design operates 1.48 dB from the capacity region boundary.We also consider the performance of our scheme over a slow fading BC.For two transmit antennas, simulation results indicate a performance loss of only 1.4 dB, 1.64 dB and 1.99 dB from the theoretical limit in terms of the total transmission power for the two, three and four user case, respectively.

Consider a multi-user channel, where each user has a large but non-replenishable bit pool to transmit. Completion time refers to the number of channel uses spent by each user to complete its transmission. In this paper, an information-theoretic formulation of completion time is based on the concept of constrained rates, which are defined over possibly different number of channel uses. Analogous to the capacity region, the completion time region characterizes all possible trade-offs among users’ completion times. For a two-user multi-access channel, it is shown that the completion time region is achieved by operating the channel in two independent phases: a multi-access phase when both users are transmitting, and a point-to-point phase when one user has finished and the other is still transmitting. Using a similar two-phase approach, the completion time regions (or inner and outer bounds) are established for a two-user Gaussian broadcast channel and a two-user Gaussian interference channel. It is observed that although consisting of two convex subregions, the completion time region may not be convex in general. Finally, optimization problems of minimizing the weighted sum completion time for a Gaussian multi-access channel and a Gaussian broadcast channel are solved, demonstrating the utility of the completion time approach.

We study delay-limited (also called zero-outage) capacity region of the fading multi-access channel (MAC) with Gaussian noise and perfect channel state information (CSI) at the receiver and at the transmitters (CSI-TR), in the low-power regime. We show that for fading channels where the MAC capacity region is strictly positive, it has a multidimensional rectangle structure and thus is simply characterized by single user capacity points. More specifically, we show that at low power, the boundary surface of the capacity region shrinks to a single point corresponding to the sum-rate maximizer and that the coordinates of this point coincide with single user capacity bounds. Using the duality of the Gaussian MAC and broadcast channels (BC), we show that time-sharing (or time division multiple access (TDMA)) is asymptotically optimal.