Abstract-Full Duplex or Simultaneous transmission and reception (STR) in the same frequency at the same time can potentially double the physical layer capacity. However, high power transmit signal will appear at receive chain as echoes with powers much higher than the desired received signal. Therefore, in order to achieve the potential gain, it is imperative to cancel these echoes. As these high power echoes can saturate low noise amplifier (LNA) and also digital domain echo cancellation requires unrealistically high resolution analog-to-digital converter (ADC), the echoes should be cancelled or suppressed sufficiently before LNA. In this paper we present a closed-loop echo cancellation technique which can be implemented purely in analogue domain. The advantages of our method are multiplefold: it is robust to phase noise, does not require additional set of antennas, can be applied to wideband signals and the performance is irrelevant to radio frequency (RF) impairments in transmit chain. Next, we study a few protocols for STR systems in carrier sense multiple access (CSMA) network and investigate MAC level throughput with realistic assumptions in both single cell and multiple cells. We show that STR can reduce hidden node problem in CSMA network and produce gains of up to 279% in maximum throughput in such networks. Moreover, at high traffic load, the gain of STR system can be tremendously large since the throughput of non-STR system is close to zero at heavy traffic due to severe collisions. Finally, we investigate the application of STR in cellular systems and study two new unique interferences introduced to the system due to STR, namely BS-BS interference and UE-UE interference. We show that these two new interferences will hugely degrade system performance if not treated appropriately. We propose novel methods to reduce both interferences and investigate the performances in system level. We show that BS-BS interference can be suppressed sufficiently enough to be less than thermal noise power, and with favorable UE-UE channel model, capacities close to double are observed both in downlink (DL) and uplink (UL). When UE-UE interference is larger than DL co-channel interferences, we propose a simple and "non-cooperative" technique in order to reduce UE-UE interference.

Abstract-Downlink scheduling schemes are well-known and widely investigated. In the multiuser MIMO (broadcast) case, downlink scheduling in the presence of non-perfect CSI is only scantly treated. In this paper we provide a general framework within which the problem can be addressed systematically. Then, we focus on the special case of proportional fairness and "hard fairness", with Gaussian coding and linear beamforming. We find that the naive scheduler that ignores the quality of the channel state information may be very suboptimal. We propose novel simple schemes that perform very well in practice. Also, we illuminate the key role played by the channel state prediction error: our schemes treat in a fundamentally different way users with "predictable" or "non-predictable" channels, and allocate these classes of users over time in a near-optimal fashion. I. SYSTEM SET-UPWe consider the standard MIMO Broadcast Channel (BC) model where the transmitter (indicated as "base station" (BS) in the following) has M antennas and K receivers have one antenna each. The channel is assumed frequency flat 1 and constant over "slots" of length T ≫ 1 (block-fading model). One channel use at block t is given byAs said, t tics at the slot rate, k is the user index,is the channel vector from the BS antenna array to the k-th receiver antenna, x(t) ∈ C M is the transmit signal vector andWe collect all channel vectors into a channel state matrixM×K . This is assumed to vary in time, from slot to slot, according to an ergodic stationary process.At the beginning of each slot t, the BS has knowledge of the channel state information (CSI) H(t), obtained by some form of downlink training and feedback (see for example [1] and references therein). We add the following technical condition: we assume that at any t, the actual channel state H(t) is conditionally independent of the past CSI { H(τ ) : τ < t} given the present CSI H(t). This condition holds, for example, when H(t) and H(t) are jointly Gaussian, and H(t) is the optimal MMSE estimator of H(t) given (noisy) measurements of the past/present channel state. Although our algorithms 1 The generalization to MIMO-OFDM and frequency selective fading is trivial.2 Notice that we omit the channel use index within each slot since this is not needed throughout the paper, and we indicate only the slot index.do not require this condition in practice , the theoretical framework of Section II does.While the capacity region of the MIMO-BC in the perfect CSI case H(t) = H(t) is now well-known [2], the case of imperfect CSI is still open although outer bounds and achievability lower bounds exist. Here, we focus on a simple achievability strategy based on zero-forcing beamforming (ZFBF) and independently Generated Gaussian user codes. Based on H(t), the BS computes a beamforming matrix V(t) ∈ C M×K of unit-norm vectors, the transmit powers p(t) = { p k (t) : k = 1, . . . , K} and the user coding rates R(t) = { R k (t) : k = 1, . . . , K}. Then, the user codewords are multiplexed on the channel such that...

Downlink scheduling schemes are well-known and widely investigated under the assumption that the channel state is perfectly known to the scheduler. In the multiuser MIMO (broadcast) case, downlink scheduling in the presence of non-perfect channel state information (CSI) is only scantly treated. In this paper we provide a general framework that addresses the problem systematically. Also, we illuminate the key role played by the channel state prediction error: our scheme treats in a fundamentally different way users with small channel prediction error ("predictable" users) and users with large channel prediction error ("non-predictable" users), and can be interpreted as a near-optimal opportunistic time-sharing strategy between MIMO downlink beamforming to predictable users and space-time coding to nonpredictable users. Our results, based on a realistic MIMO channel model used in 3GPP standardization, show that the proposed algorithms can significantly outperform a conventional "mismatched" scheduling scheme that treats the available CSI as if it was perfect. Index TermsMultiuser MIMO, Downlink Scheduling, Channel Estimation.The authors are with the Ming Hsieh

Channel state feedback schemes for the MIMO broadcast downlink have been widely studied in the frequency-flat case. This work focuses on the more relevant frequency selective case, where some important new aspects emerge. We consider a MIMO-OFDM broadcast channel and compare achievable ergodic rates under three channel state feedback schemes: analog feedback, direction quantized feedback and "time-domain" channel quantized feedback. The first two schemes are direct extensions of previously proposed schemes. The third scheme is novel, and it is directly inspired by rate-distortion theory of Gaussian correlated sources. For each scheme we derive the conditions under which the system achieves full multiplexing gain. The key difference with respect to the widely treated frequency-flat case is that in MIMO-OFDM the frequency-domain channel transfer function is a Gaussian correlated source. The new time-domain quantization scheme takes advantage of the channel frequency correlation structure and outperforms the other schemes. Furthermore, it is by far simpler to implement than complicated spherical vector quantization. In particular, we observe that no structured codebook design and vector quantization is actually needed for efficient channel state information feedback. Index TermsMIMO Broadcast Channel, OFDM, Channel State Feedback, Quantization.H. Shirani-Mehr and G. Caire are with the Ming Hsieh

User scheduling and multiuser multi-antenna (MU-MIMO) transmission are at the core of highrate data-oriented downlink schemes of the next-generation of cellular systems (e.g., LTE-Advanced).Scheduling selects groups of users according to their channels vector directions and SINR levels.However, when scheduling is applied independently in each cell, the inter-cell interference (ICI) power at each user receiver is not known in advance since it changes at each new scheduling slot depending on the scheduling decisions of all interfering base stations. In order to cope with this uncertainty, we consider the joint operation of scheduling, MU-MIMO beamforming and Automatic Repeat reQuest (ARQ). We develop a game-theoretic framework for this problem and build on stochastic optimization techniques in order to find optimal scheduling and ARQ schemes. Particularizing our framework to the case of "outage service rates", we obtain a scheme based on adaptive variable-rate coding at the physical layer, combined with ARQ at the Logical Link Control (ARQ-LLC). Then, we present a novel scheme based on incremental redundancy Hybrid ARQ (HARQ) that is able to achieve a throughput performance arbitrarily close to the "genie-aided service rates", with no need for a genie that provides non-causally the ICI power levels. The novel HARQ scheme is both easier to implement and superior in performance with respect to the conventional combination of adaptive variable-rate coding and ARQ-LLC.