We consider the downlink of a wireless cellular network where the base stations are equipped with multiple antennas and operate in the same frequency band. Since scheduling changes the spatial transmit signal processing with each time slot, information from neighboring base stations is required for data encoding. This can, in theory, be accomplished by a high-capacity backhaul network through which the base stations exchange channel state information (CSI) and other control signals. In reality, however, the temporal granularity of the scheduler does not allow for timely distribution of CSI among base stations. We propose a two-phase scheduler which optimizes the precoding in the first phase and allows the users to feed back their instantaneous interference power in the second phase. For the single-user case, we present a practical scheme that combines two-phase scheduling with precoders that maximize the signal-to-leakage-plus-noise ratio. If the users feed back the interference power together with a supported rate, communication between base stations can be limited to integers. By comparing the performance to multi-user two-phase scheduling with dirty paper coding and to algorithms that share CSI among base stations we show that two-phase scheduling is a technically and practically feasible solution to deal with non-stationary intercell interference.

In signal processing, system theory, an in information theory signals are either complex valued waveforms or sequences of dimensionless complex numbers. The »power« of such signals is usually said to be the squared magnitude of these complex numbers. In an electrical circuit, power is always the product of voltage and current, both present at a port, i.e., at a pair of terminals. Here we ask the question: what is the relation between signal power and physical power? There are special cases, where the two notions of power are strictly proportional and, therefore, no conflict occurs. But in general, especially when we deal with vector signals, the commonly used squared Euclidean norm of the signal vector may not be a measure for the physical power associated with the voltages and currents, which correspond to the signal vector. In addition to the physically consistent computation of signal power, physically consistent modeling of the noise is crucial in all information processing systems. Again circuit theory provides with a methodology to model how the noise comes into the system. Modeling is one the most important tasks in engineering and, therefore, physically consistent modeling is very important for the education of electrical engineers. Circuit Theory is the essential framework to ensure physical consistency across several levels of abstraction.

We report on our investigation of the capacity region of a Gaussian multiple access channel with two independent transmitters for the case where the receiver's antenna spacing is very small (compared to the wavelength). In contrast to common belief, we find that a rectangular capacity region can be maintained even as the distance of the antennas approaches zero. Moreover, the size of the capacity region even increases as the antenna separation is reduced. Therefore, high-performance multiple access is perfectly possible in confined space situations such as in hand-held mobile devices using standard frequencies for mobile communications.

We consider the downlink of a cellular wireless network where the base stations are equipped with multiple transmit antennas and operate in the same frequency band. Each base station serves one user per orthogonal frequency-division multiplexing (OFDM) sub-carrier by means of spatial precoding. Due to temporal scheduling, the active users change rapidly in time and consequently, intercell interference becomes non-stationary limiting the achievable network sum-rate. Under the assumption of perfect channel knowledge at each base station, we optimize both precoding and scheduling in order to maximize the achievable network sum-rate. The solution, however, unveils that both precoding and scheduling can be performed locally at each base station without the need for CSI to be exchanged between base stations if they are solely based on average channel measurements.

Both fast scheduling and spatial signal processing have proven to be capacity-increasing methods in wireless communication systems. However, when applied in the downlink of a cellular network, the combination of both leads to non- stationary intercell interference. If the base stations do not cooperate, either they have to encode the data very conservatively to gain robustness or the non-stationary fluctuations of the interference powers lead to frequent outages, both of which strongly impair the average achievable throughput. On the other hand, base station cooperation increases complexity and delays, contradicting the desire for fast scheduling algorithms. In this paper, we propose a scheme that makes average channel state information available to all base stations via low-rate back haul communication, whereas high-rate inter-base-station communication is limited to B lceillog2Krceil-bit integers, K being the number of users in each of the B cells. Simulations show that for slow fading channels, the proposed algorithm preserves most of the per cell sum-rate of other beamforming and dirty- paper coding approaches that have unlimited-capacity back haul links. Furthermore, when out-of-cell information is outdated the proposed algorithm even outperforms those.

We comment on the famous work GtOpportunistic beamforming using dumb antennasLt by P. Viswanath, D.N.C. Tse, and R. Laroia, from 2002. In that paper, it is argued that in an independent and fast fading environment, the opportunistic beamforming technique provides no performance gain. This assessment is based on the argument that the fading distribution of the equivalent channel, which is obtained through opportunistic beamforming, does not depend on the number of transmit antennas in independent and fast fading scenarios. In this paper, we show that this argument of the original work is based on a non-physical model of Rayleigh fading, and as a consequence, results in a wrong conclusion. In contrast, we show that there is beamforming gain to be obtained by the opportunistic beamforming technique even for independent and fast fading environments. For the case of uncoupled antennas, the amount of obtainable beamforming gain approaches - with probability one - the number of transmit antennas from below as the number of users approaches infinity.

The receive antenna gain of an antenna array critically depends on the receiver noise covariance. Receiver noise essentially originates from two sources: the receive low-noise amplifiers (LNA), and background radiation that is received by the array. In case that the LNAs are the sole origin of noise, it is state of the art to argue that the receiver noise is spatially uncorrelated, for noise originates in components of physically separate LNAs. However, this argument ignores coupling between antennas due to their spatial proximity, and moreover the coupling introduced by the impedance matching network which is located between the antenna outputs and the LNA inputs. Because of these coupling effects, the receiver noise is usually spatially correlated even when independent LNAs are the sole source of noise in the system. The noise covariance, depends on the following four factors: 1) antenna spacing of the array, 2) properties of the impedance matching network, 3) noise-resistance of the LNAs, 4) intensity of received background noise with respect to noise generated by the LNAs. Taking these issues into account, we derive, in this paper, the receive antenna gain of a uniform linear antenna array of isotrops in closed form. It turns out that the receive antenna gain can become much larger than the number of antennas. For the case of low noise-resistance, and low relative intensity of received background noise, we show that the receive antenna gain can even grow exponentially with the number of antennas. These results are exciting, because they imply that the performance of communication systems which use multiple receive antennas can be much better than previously reported.

It is common in information theoretic channel models to rely on the average squared Euclidean norm of the channel input as being proportional to transmit power. Likewise, it is common to assume noise that is additive, Gaussian, and white. It is a legitimate question to ask, whether such a modeling approach has enough degrees of freedom to capture the physical constraints that are imposed on implementations of a communication system. In this paper, we show that in many, though not all, situations it is indeed possible to obtain a complete physical model, while nevertheless sticking with average squared Euclidean norm as power, and white Gaussian noise. Our systematic approach works in two steps. First, all channel inputs and outputs are replaced by ports, which are de.ned by two conjugated variables (like voltage and current). By this multi-port modeling approach, we can obtain a complete physical model. Secondly, we introduce linear transformations between the inputs and outputs of the information theoretic channel model on the one hand, and the physical inputs and physical outputs of the communication system, on the other. This approach gives us enough degrees of freedom to obtain a complete information theoretic model, which correctly reflects the physical constraints that are imposed upon the communication system by its environment. We apply the proposed approach to a multi-antenna communication system, and show that it is indeed possible that the channel capacity of multi-antenna systems can grow super-linearly with the number of antennas for large signal to noise ratios.

The major difference between a non-cellular system, i.e. a single isolated cell, and a cellular system is the intercell interference (ICI). In the uplink, the base station can measure the users' signal to noise and interference ratio (SINR) and through a feedforward channel it can inform the users which coding and modulation scheme to apply in order to perform link adaptation (LA). However, a user's SINR observed in the uplink by the base station when determining the link adaptation decision might no longer be the same when the link adaptation is effected by the user due to fluctuations of the intercell interference. By then, the intercell interference could have greatly changed even if the users are static, due to changes in the scheduling decisions in the interfering cells. Hence, the uplink transmission would no longer have the correct link adaptation for the current SINR, since we are to some extent blind with respect to the ICI. In this work, we quantify this degree of ICI blindness by the correlation between the measured ICI and the actual experienced ICI. Furthermore, we analyze the degradation in throughput for different degrees of ICI correlation which depends on the scheduling in the interfering cells. Additionally, we show how much benefit correct link adaptation provides in a cellular environment over outdated link adaptation. In this work, we assume that there is no intracell interference as a consequence of an orthogonal multiple access scheme.

We present a model for multiuser multi-input multi-output (MIMO) high speed downlink packet access (HSDPA) with covariance based linear precoders. The linear procoders, which are designed for single stream detection with rake receivers, are independent of the equalizers employed in multiple antenna receivers to support multistream detection. These symbol based equalizers are designed to minimize the mean square error (MSE) of the signal estimates. Both theoretical analysis and numerical results show the applicability of the proposed approach in HSDPA. There is no limitation on the number of users as long as enough code channels are available. Also, all the users have free choice on how many antennas they can deploy. This approach extends the covariance based precoding concept from MISO to MIMO systems.

Intercell interference (ICI) is the substantial difference between a cellular and a non-cellular communication system. Effective modeling of the cellular downlink as a Gaussian broadcast channel requires that the ICI powers at the user positions are known to the basestation (BS), as it otherwise, cannot attempt to approach (or even know) its capacity region. However, ICI depends on the transmit processing of the BSs in the neighboring cells, which furthermore is subject to change quickly due to temporal scheduling. The BS therefore only has limited knowledge about the true ICI powers. In this paper, the implications of this lack of knowledge about ICI power on the achievable sum- rate of a Gaussian MISO (multi-input, single-output) broadcast channel is examined. Four different approaches on dealing with unpredictable ICI are discussed and their performance compared to the single-cell (or non-cellular) Gaussian broadcast channel.

The main difference between a non-cellular and a cellular communication system is the intercell interference. Therefore, modelling the intercell interference and analyzing its effects is of particular interest for cellular communication systems. On the one hand, the intercell interference can be modeled by system level simulations. On the other hand, it is also meaningful to assess the intercell interference without performing exhaustive simulations which nonetheless at the same time still capture the major effects that determine the interference. To this end, we consider the intercell interference as a random variable composed of many other random variables. In this paper, we present a semi-analytical method to analyze the downlink intercell interference in a cellular system. Through such an approach a quick and reliable assessment of the downlink inter-cell interference can be obtained. Our focus is on the methodology and we consider basic access schemes: WCDMA, TDMA, FDMA, and random OFDMA. However, our model can be extended to include other access schemes and other features.

A new semi-analytical method to analyze intercell interference in a cellular system is introduced. A sound comprehension of the properties of intercell interference is the key to a meaningful assessment of communication systems without exhaustive simulation campaigns. We consider the basic access schemes TDMA, WCDMA and random OFDMA for uplink transmission. We will also give hints, how the methods can be extended to capture other access schemes, and/or additional features. The focus of this work is more on the introduction of the new methodology. In principle, we describe the intercell interference as a random variable which is composed of many other random variables. The distributions, and in particular the mutual dependencies of those have to be carefully studied. Applications and extensions of the ideas will be addressed in future work, only first examples are given here.

In this paper, we compare the performance of the diversity approach at the application layer and that at the physical layer for H.264/AVC encoded streaming video transmission in a wireless system with two independent channels. The application layer diversity is achieved by using multiple description source coding, while the physical layer diversity is obtained by channel coding over the two channels. Numerical results show that PHY layer diversity always outperforms the application layer diversity.

This paper provides analysis of binary space-time block codes with optimum decoding for multi-input multi-output (MIMO) systems with one-bit receive signal quantization. Exhaustive investigation of short binary space-time block codes with unity code rate shows some remarkable results. For instance, almost all codes perform poorly, except one optimum channel-dependent code which can achieve large coding gain. There are no binary 2×2 space-time block codes (including the Alamouti codes) which can achieve transmit diversity without some channel knowledge. However, there exist a few semi-universal codes which are optimum for almost all MIMO channels and can be selected by feedback from the receiver. Design of longer and more powerful codes remains a challenge and requires further research activity.

In this paper, the effects of receive signal quantization on the channel capacity and the performance of error control coding in multi-input multi-output (MIMO) systems are investigated. The receive antennas of a MIMO system experience a channel-dependent superposition of modulated signals originating from all transmit antennas. A fine-granular analog to digital conversion of the resulting irregular constellation is difficult to obtain in practice. The quantization is therefore likely to be rather coarse. It turns out, however, that the loss in channel capacity due to coarse quantization is surprisingly small. On the other hand, existing coding schemes do not seem to tolerate coarse quantization gracefully, producing rather high error floors. Closing the huge gap between information theoretic opportunities offered by coarse quantized MIMO systems on the one hand, and the actual poor performance of coding schemes which are designed without signal quantization in mind, remains a challenging task.

In this paper, we provide an accurate and fully analytical model for the distortion due to lost frames in wireless video transmission. Our analysis combines the properties of the video sequence and those of the wireless transmission link. Built on the long-term average properties of the video source, we first develop a model for the average distortion due to the loss of frames, and then derive a mathematical model for analysis of transmission errors occurring during wireless transmission. Experimental results show a surprisingly accurate behaviour of the proposed model.

In this paper, two empirical models for the sequence-level distortion-rate performance of predictive video source encoding are proposed. They require very limited amount of empirical data, namely three pairs of rate and distortion, in order to set up the model parameters. The advantages of these proposed models are the robustness towards measurement noise, low number of model parameters with a closed form setup solution, and high accuracy. Experimental validation using H.264/AVC encoded video test sequences reports high accuracy of these two proposed models.

In this letter, we introduce five different strategies of linear transmit signal processing for multiuser multiple-input multiple-output (MIMO) systems and provide performance comparisons in terms of maximum throughput in both uncorrelated and correlated channels when the number of transmit antennas is much larger than the number of receive antennas. It is shown that the multiuser MIMO schemes are preferable to time-division multiple-access (TDMA)-based MIMO schemes, hence demonstrating the power of multiuser MIMO signal processing. Our work also indicates possibilities for future research in finding efficient suboptimal algorithms. As an example, we show that our multiuser MIMO decomposition scheme can improve the maximum throughput compared to TDMA-based MIMO schemes for large number of transmit antennas or high transmit power.

We investigate the effects of fading correlations on wireless communication systems employing multiple antennas at both the receiver and the transmitter side of the link, so called multiple-input multiple-output (MIMO) systems. It turns out that the amount of transmitter sided channel knowledge plays an important part when dealing with fading correlations. Furthermore, the possible availability of time diversity in a time-selective channel can have essential influence on performance. To study the influence of time-selectivity, the concept of sample-mean outage is introduced and applied to information theoretic measures, like capacity or cutoff rate. It will be shown, that in some cases correlated fading may offer better performance than uncorrelated fading permits, which is due to exploitable antenna gain, that will also be defined in a general form for MIMO systems.

In a wireless communication link with one transmit and multiple receive antennas we optimally reduce the spatio-temporal channel rank at the receiver based on long-term (average) channel properties. The channel is estimated and symbols are detected using this reduced rank approximation of the received signal. Examples for this receiver architecture are the temporal/spatio-temporal RAKE, space-time eigenRAKE, or beamspace processing. We discuss the fundamental trade-offs in reduced rank channel estimation and detection and propose an appropriate model for describing the spatio-temporal channel structure. Based on these insights and definitions, we derive an analytical expression for the minimum receiver SNR, which is necessary for channel estimation. Furthermore, we state under which conditions reduced rank channel estimation is asymptotically optimum.

In this article we introduce a novel multiple-input-multiple-output (MIMO) spatial filter (SF) which can be applied as a preprocessing scheme to uniform linear arrays in mobile communications, preserving the Vandermonde structure of the steering vectors while changing the amplitude and the phase gradient of the steering vector in a nonlinear fashion. The new scheme is therefore titled Vandermonde invariance transformation. The introduced degrees of freedom due to this preprocessing transformation can be used to beneficially influence the properties of the channel to achieve an enhanced performance of the subsequent signal processing algorithm.

We investigate the effects of both fading correlations and transmitter channel knowledge in multiple element antenna (MEA) communication systems. While, for independent and identically distributed fades between receive and transmit antennas, pioneering work showed that a huge increase in capacity is possible for MEA compared to a single antenna system, recent contributions warn that fading correlations destroy most of this advantage. While this is true for zero transmitter channel knowledge, we show however that long-term average channel state information enables the transmitter to efficiently use the fading correlations to its advantage and offers the potential to even increase capacity beyond the one possible for independent fading. A conceived transmit technique is presented that efficiently makes use of fading correlations, and also provides optimum choice of digital modulation schemes that carry the information.