On the achievable rate region of gaussian cognitive multiple access channel

We consider the communication scenario where multiple cognitive users wish to communicate to the same receiver through AWGN channels, in the presence of primary transmission. The cognitive users are assumed to have the side information about the primary transmission. The achievable rate region of cognitive users is formulated under the constraint that the rate of primary transmission is not changed as if no cognitive users existed. Moreover, the maximum achievable sum-rate point of the rate region is characterized     

Sum Rate Characterization of Joint Multiple Cell-Site Processing

The sum-rate capacity of a cellular system model is analyzed, considering the uplink and downlink channels, while addressing both nonfading and flat-fading channels. The focus is on a simple Wyner-like multicell model, where the system cells are arranged on a circle, and the cell sites are located at the boundaries of the cells. For the uplink channel, analytical expressions of the sum-rate capacities are derived for intra-cell time-division multiple-access (TDMA) scheduling, and a “wideband” (WB) scheme (where all users are active simultaneously utilizing all bandwidths for coding). Assuming individual equal per-cell power constraints, and using the Lagrangian uplink–downlink duality principle, an analytical expression for the sum-rate capacity of the downlink channel is derived for nonfading channels, and shown to coincide with the corresponding uplink result. Introducing flat-fading, lower and upper bounds on the average per-cell ergodic sum-rate capacity are derived. The bounds exhibit an $O(log _{e} K)$ multiuser diversity factor for a number of users per cell $Kgg 1$ , in addition to the array diversity gain. Joint multicell processing is shown to eliminate out-of-cell interference, which is traditionally considered to be a limiting factor in high-rate reliable communications.      

Power Control and Allocation for MIMO Broadcast Channels in Cognitive Radio Networks

This paper considers multiple-input multiple-output broadcast channels in cognitive radio networks which consist of a cognitive base station (CBS), K secondary users (SUs) and N primary users (PUs). The multiantenna-based CBS concurrently operates with the PUs. The channel state information for SUs is assumed to be perfectly known at the CBS. To ensure the quality of service of PUs and maximize sum-rate capacity of SUs, two problems are considered: (1) What is the optimal power control of CBS? (2) What are the optimal power allocations of SUs? A two-level game is presented to jointly consider the benefits of power control of CBS and power allocations of SUs. Under this game model, the corresponding game algorithms are also proposed. Finally, numerical simulation results are provided to examine the performance of our proposed algorithms.     

Cooperative Multicell Zero-Forcing Beamforming in Cellular Downlink Channels

In this work, a multicell cooperative zero-forcing beamforming (ZFBF) scheme combined with a simple user selection procedure is considered for the Wyner cellular downlink channel. The approach is to transmit to the user with the ldquobestrdquo local channel in each cell. The performance of this suboptimal scheme is investigated in terms of the conventional sum-rate scaling law and the sum-rate offset for an increasing number of users per cell. We term this characterization of the sum-rate for large number of users as high-load regime characterization, and point out the similarity of this approach to the standard affine approximation used in the high-signal-to-noise ratio (SNR) regime. It is shown that, under an overall power constraint, the suboptimal cooperative multicell ZFBF scheme achieves the same sum-rate growth rate and slightly degraded offset law, when compared to an optimal scheme deploying joint multicell dirty-paper coding (DPC), asymptotically with the number of users per cell. Moreover, the overall power constraint is shown to ensure in probability, equal per-cell power constraints when the number of users per-cell increases.     

Optimization of Training and Scheduling in the Non-Coherent SIMO Multiple Access Channel

Channel state information (CSI) is important for achieving large rates in MIMO channels. However, in time-varying MIMO channels, there is a tradeoff between the time/energy spent acquiring channel state information (CSI) and the time/energy remaining for data transmission. This tradeoff is accentuated in the MIMO multiple access channel (MAC), since the number of channel vectors to be estimated increases with the number of users. Furthermore, the problem of acquiring CSI is tightly coupled with the problem of exploiting CSI through multiuser scheduling. This paper considers a block-fading MAC with coherence time T, n uncoordinated users-each with one transmit antenna and the same average power constraint, and a base station with M receive antennas and no a priori CSI. For this scenario, a training-based communication scheme is proposed and the training and multiuser-scheduling aspects of the scheme are jointly optimized. In the high-SNR regime, the sum capacity of the non-coherent SIMO MAC is characterized and used to establish the SNR-scaling-law optimality of the proposed scheme. In the low-SNR regime, the sum-rate of the proposed scheme is found to decay linearly with vanishing SNR when flash signaling is incorporated. Furthermore, this linear decay is shown to be order-optimal through comparison to the low-SNR sum capacity of the non-coherent SIMO MAC. A by product of these SNR-asymptotic analyses is the observation that non-trivial scheduling (i.e., scheduling a strict subset of trained users) is advantageous at low SNR, but not at high SNR. The sum-rate and per-user throughput are also explored in the large-n and large-M regimes. Non-coherent capacity, training, multiple access channel, multiuser scheduling, opportunistic scheduling.     

Asymptotic Analysis of Spatially Correlated MIMO Multiple-Access Channels With Arbitrary Signaling Inputs for Joint and Separate Decoding

While the capacity of a single-user, point-to-point, multiple-input multiple-output (MIMO) channel has been well known, the achievable capacity of a MIMO channel in the presence of other co-channel users is much less understood. One such important scenario is the multiple-access (MA) channel where communication occurs from many uncoordinated mobile users to a common base station receiver (i.e., multipoint-to-point). Unlike previous studies whose emphases were on the idealized spatially uncorrelated channels with Gaussian signaling inputs from users, this paper derives a general analytical expression for the asymptotic (in the sense of large-system limit) sum-rate of a MIMO-MA system where the transmitters and the receiver can have different spatial correlations, and the users' inputs are not necessarily Gaussian. In addition to the sum-rate formula that assumes optimal joint decoding at the base station, we also derive the asymptotic sum-rate of a more practical system which performs separate decoding (multiuser detection followed by a bank of temporal error-correction decoders). Our analytic formulae are important in that they reveal the sum-rate one's system can achieve given the spatial correlation structures at the transmitters and receiver, and the input signal distributions. For special cases that users are homogeneous or users have Gaussian inputs, our results degenerate to previously published results. Furthermore, through computer simulations, we see that the proposed asymptotic solution gives good estimates for the ergodic sum-rate of the systems even with only a few antenna elements at each transmitter and receiver     

Joint Beamforming and Power Allocation for Multiple Access Channels in Cognitive Radio Networks

A cognitive radio (CR) network refers to a secondary network operating in a frequency band originally licensed/allocated to a primary network consisting of one or multiple primary users (PUs). A fundamental challenge for realizing such a system is to ensure the quality of service (QoS) of the PUs as well as to maximize the throughput or ensure the QoS, such as signal-to-interference-plus-noise ratios (SINRs), of the secondary users (SUs). In this paper, we study single-input multiple output multiple access channels (SIMO-MAC) for the CR network. Subject to interference constraints for the PUs as well as peak power constraints for the SUs, two optimization problems involving a joint beamforming and power allocation for the CR network are considered: the sum-rate maximization problem and the SINR balancing problem. For the sum-rate maximization problem, zero-forcing based decision feedback equalizers are used to decouple the SIMO-MAC, and a capped multi-level (CML) water-filling algorithm is proposed to maximize the achievable sum-rate of the SUs for the single PU case. When multiple PUs exist, a recursive decoupled power allocation algorithm is proposed to derive the optimal power allocation solution. For the SINR balancing problem, it is shown that, using linear minimum mean-square-error receivers, each of the interference constraints and peak power constraints can be completely decoupled, and thus the multi-constraint optimization problem can be solved through multiple single-constraint sub-problems. Theoretical analysis for the proposed algorithms is presented, together with numerical simulations which compare the performances of different power allocation schemes.     

Fundamental Limits in MIMO Broadcast Channels

This paper studies the fundamental limits of MIMO broadcast channels from a high level, determining the sum-rate capacity of the system as a function of system parameters, such as the number of transmit antennas, the number of users, the number of receive antennas, and the total transmit power. The crucial role of channel state information at the transmitter is emphasized, as well as the emergence of opportunistic transmission schemes. The effects of channel estimation errors, training, and spatial correlation are studied, as well as issues related to fairness, delay and differentiated rate scheduling.     

Achieving Multi-user Diversity Gain using User-Identity Feedback

A user-identity feedback method is proposed to achieve multi-user diversity in broadcast channels. This method associates the feedback slots with pre-determined thresholds that diminish with time, and allows feedback from those users whose channel states exceed the threshold assigned to the current slot. Since the threshold can approximate the channel state, this method requires only user-identity feedback. In Rayleigh fading channels, this method is mathematically shown to achieve the sum-rate capacity asymptotically with a large number of users, while requiring only a few feedback slots and little transmission power.     

Sum-Rate Analysis of Downlink Channels with 1-Bit Feedback

The sum-rate capacity of a single-input single-output (SISO) downlink with Rayleigh flat fading channels and K users, grows as log log K when optimal scheduling is employed. However, the optimal scheduling requires that the full channel state information (CSI) for all users be available to the transmitter. In this work it is shown that the same rate growth holds even if the feedback rate from the users to the transmitter is reduced to 1-bit per fading block. A simple analysis for this setup is presented, resulting in a closed form expression for the achievable ergodic sum-rate. The mechanism of setting a sub-optimal threshold is elucidated by simple lower and upper bounds to the sum-rate. Among the insights afforded by the sum-rate expression and the bounds, is that application of the sub-optimal threshold demonstrates the same scaling law as the optimal full CSI scheme, asymptotically with the number of users K     

The Water-Filling Game in Fading Multiple-Access Channels

A game-theoretic framework is developed to design and analyze the resource allocation algorithms in fading multiple-access channels (MACs), where the users are assumed to be selfish, rational, and limited by average power constraints. The maximum sum-rate point on the boundary of the MAC capacity region is shown to be the unique Nash equilibrium of the corresponding water-filling game. This result sheds a new light on the opportunistic communication principle. The base station is then introduced as a player interested in maximizing a weighted sum of the individual rates. A Stackelberg formulation is proposed in which the base station is the designated game leader. In this setup, the base station announces first its strategy defined as the decoding order of the different users, in the successive cancellation receiver, as a function of the channel state. In the second stage, the users compete conditioned on this particular decoding strategy. This formulation is shown to be able to achieve all the corner points of the capacity region, in addition to the maximum sum-rate point. On the negative side, it is shown that there does not exist a base station strategy in this formulation that achieves the rest of the boundary points. To overcome this limitation, a repeated game approach, which achieves the capacity region of the fading MAC, is presented. Finally, the study is extended to vector channels highlighting interesting differences between this scenario and the scalar channel case.     

一种新的认知无线电功率分配算法（英文）

Most resource allocation algorithms are based on interference power constraint in cognitive radio networks.Instead of using conventional primary user interference constraint,we give a new criterion called allowable signal to interference plus noise ratio(SINR) loss constraint in cognitive transmission to protect primary users.Considering power allocation problem for cognitive users over flat fading channels,in order to maximize throughput of cognitive users subject to the allowable SINR loss constraint and maximum transmit power for each cognitive user,we propose a new power allocation algorithm.The comparison of computer simulation between our proposed algorithm and the algorithm based on interference power constraint is provided to show that it gets more throughput and provides stability to cognitive radio networks.     

Opportunistic power allocation strategies and fair subcarrier allocation in OFDM-based cognitive radio networks

In this paper we have studied the subcarrier and optimal power allocation strategy for OFDM-based cognitive radio (CR) networks. Firstly, in order to protect the primary user communication from the interference of the cognitive user transmissions in fading wireless channels, we design an opportunistic power control scheme to maximize the cognitive user capacity without degrading primary user’s QoS. The mathematical optimization problem is formulated as maximizing the capacity of the secondary users under the interference constraint at the primary receiver and the Lagrange method is applied to obtain the optimal solution. Secondly, in order to limit the outage probability within primary user’s tolerable range we analyze the outage probability of the primary user with respect to the interference power of the secondary user for imperfect CSI. Finally, in order to get the better tradeoff between fairness and system capacity in cognitive radio networks, we proposed an optimal algorithm of jointing subcarrier and power allocation scheme among multiple secondary users in OFDM-based cognitive radio networks. Simulation results demonstrate that our scheme can improve the capacity performance and efficiently guarantee the fairness of secondary users.     

How much time is needed for wideband spectrum sensing?

In this paper, we consider a wideband cognitive radio network (CRN) which can simultaneously sense multiple narrowband channels and thus aggregate the perceived available channels for transmission. We study the problem of designing the optimal spectrum sensing time and power allocation schemes so as to maximize the average achievable throughput of the CRN subject to the constraints of probability of detection and the total transmit power. The optimal sensing time and power allocation strategies are developed under two different total power constraints, namely, instantaneous power constraint and average power constraint. Finally, numerical results show that, under both cases, for a CRN with three 6MHz channels, if the frame duration is 100ms and the target probability of detection is 90% for the worst case signal-to-noise ratio of primary users being ?12dB, ?15dB and ?20dB, respectively, the optimal sensing time is around 6ms and it is almost insensitive to the total transmit power.     

Some results on the sum-rate capacity of MIMO fading broadcast channels

We study the ergodic sum-rate capacity of the fading MIMO broadcast channel which is used to model the downlink of a cellular system with N/sub t/ transmit antennas at the,base and K mobile users each having N/sub r/ receive antennas. Assuming perfect channel state information (CSI) for all users is available at the transmitter and the receivers, we evaluate the sum-rate capacity numerically using the duality between uplink and downlink. Assuming Nt K, we also derive both upper and lower bounds on the sum-rate capacity to study its increase rate due to multi-user diversity. Finally, we compare three transmission schemes which use the single-user-MIMO scheme (SU-MIMO), ranked known interference (RKI) and zero-forcing beamforming (ZFB), respectively, to transmit to a selected set of users in order to approach the sum-rate capacity. We show that both ZFB and RKI outperform SU-MIMO in a cellular downlink scenario. when many mobile users are present.     

一种多用户MIMO/OFDM下行链路保障QoS的自适应传输机制

在用户QoS参数限制下,该文提出一种在多用户MIMO/OFDM下行链路使系统总速率最大的资源分配机制。基站应用空分多址接入,使得每个子载波可支持多个用户,应用线性预编码方法抵消用户间的干扰,提出保障QoS的自适应功率、比特分配方案。该文并提出两种可应用到实际系统的低复杂度的比特加载和比特去除算法,仿真结果表明,该两种方法性能可非常接近最优遍历算法。     

Multicarrier multiple access is sum-rate optimal for block transmissions over circulant ISI channels

Multicarrier multiple access with channel knowledge and prescribed power at the transmitters is shown to maximize the sum-rate for circulant intersymbol-interference (ISI) channels. A low-complexity iterative algorithm is derived for optimal subcarrier allocation to multiple users, while power is loaded per user by specializing an existing iterative algorithm to circulant ISI channels. It is analytically shown that each subcarrier should be allocated to the user having relatively better subcarrier gain and that different users may share certain subcarriers.     

Joint effect of artificial noise and primary interference on security performance of cognitive radio networks

Underlay mechanism allows concurrent communications of primary users and secondary users in cognitive radio networks (CRNs), causing mutual interference between them. However, current literature neglects primary interference or considers it as Gaussian noise. In addition, artificial noise, which is intentionally generated to interfere eavesdroppers, can improve security performance of CRNs. This paper analyzes security performance of CRNs, accounting for artificial noise and considering primary interference as non-Gaussian noise, under maximum transmit power constraint, interference power constraint, and Rayleigh fading channels. The security performance is evaluated through proposed exact expressions of secrecy outage probability, non-zero achievable secrecy rate probability, and intercept probability, which are verified by Monte-Carlo simulations. Various results demonstrate that CRNs suffer security performance saturation in the range of large maximum transmit power or large maximum interference power, and primary interference significantly deteriorates security performance while artificial noise is useful in enhancing this performance.     

Maximizing the Sum-Rate and Minimizing the Sum-Power of a Broadcast 2-User 2-Input Multiple-Output Antenna System Using a Generalized Zeroforcing Approach

While information theory tells us that a broadcast multiple-input multiple-output (MIMO) channel may be shared spatially to maximize the utilization of the channel by dirty-paper coding (DPC) techniques as opposed to time-only or frequency-only division, the associated complexity of a DPC codec is problematic for some practical applications. A more feasible alternative is to use generalized zeroforcing (GZF) which beams the signals to the targeted receivers while ensuring no inter-user interference at all the receiver outputs. Our objective of this letter is to study the GZF optimization of a broadcast 2-user 2-input many-output antenna system for both 1) sum-rate maximization subject to a total transmit power constraint and 2) sum-power minimization subject to rate constraints of the users. We shall derive the optimal GZF solutions for both problems. The capacity and signal-to-noise ratio (SNR) regions for the optimized GZF systems are also derived, and results for DPC and time-division systems are provided for comparisons     

Feedback strategies for white Gaussian interference networks

A white Gaussian interference network is a channel with T transmitters and R receivers where the received symbols are linear combinations of the transmitted symbols and white Gaussian noise. This paper considers the case where K messages are transmitted through the network in a point-to-point manner, i.e., each message is encoded by exactly one transmitter and is destined for exactly one receiver. It is further assumed that feedback is available so that each transmitter sees the outputs of the receivers to which it is sending messages. Communication strategies based on the discrete Fourier transform (DFT) are developed that perform well for such networks. For multiple-access channels (K=T, R=1) with equal transmitter powers the strategies achieve the feedback sum-rate capacity if the powers are beyond some threshold. For the same channels with fixed transmitter powers and large K, the achievable sum-rate is approximately (log log K)/2 larger than the sum-rate capacity without feedback. For broadcast channels (T=1, K=R) with strong symmetries, the strategies achieve a monotonically increasing sum-rate with K. For interference channels (K=T=R) with strong interference, the strategies significantly enlarge the no-feedback capacity region by "correlation routing."